docs/Lectures/Theme_2-Data_Engineering/Lecture_10-SQL/Lecture_10-SQL.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {
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   },
   "source": [
    "# Lecture 10 - Databases and SQL"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "[![View notebook on Github](https://img.shields.io/static/v1.svg?logo=github&label=Repo&message=View%20On%20Github&color=lightgrey)](https://github.com/avakanski/Fall-2023-Python-Programming-for-Data-Science/blob/main/docs/Lectures/Theme_2-Data_Engineering/Lecture_10-SQL/Lecture_10-SQL.ipynb)\n",
    "[![Open In Collab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/avakanski/Fall-2023-Python-Programming-for-Data-Science/blob/main/docs/Lectures/Theme_2-Data_Engineering/Lecture_10-SQL/Lecture_10-SQL.ipynb) "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<a id='top'></a>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "iEkmemKte4Qv"
   },
   "source": [
    "- [10.1 Introduction to SQL](#10.1-introduction-to-sql)\n",
    "- [10.2 Using SQLite with Python](#10.2-using-sqlite-with-python)\n",
    "- [10.3 Create a New Table](#10.3-create-a-new-table)\n",
    "- [10.4 Database Example](#10.4-database-example)    \n",
    "- [10.5 Querying Databases with SELECT](#10.5-querying-databases-with-select)  \n",
    "- [10.6 Sorting Data with ORDER BY](#10.6-sorting-data-with-order-by) \n",
    "- [10.7 Filtering Data](#10.7-filtering-data) \n",
    "- [10.8 Conditional Expressions](#10.8-conditional-expressions) \n",
    "- [10.9 Joining Multiple Tables](#10.9-joining-multiple-tables) \n",
    "- [10.10 Return Data Statistics](#10.10-return-data-statistics) \n",
    "- [10.11 Grouping Data](#10.11-grouping-data) \n",
    "- [10.12 Modifying Data](#10.12-modifying-data) \n",
    "- [10.13 Working with Tables](#10.13-working-with-tables) \n",
    "- [10.14 Constraints](#10.14-constraints) \n",
    "- [10.15 Subqueries](#10.15-subqueries)\n",
    "- [10.16 Connect to an Existing Database](#10.16-connect-to-an-existing-database)  \n",
    "- [References](#references)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "gTFgm_bJe4Qw"
   },
   "source": [
    "<a name='10.1-introduction-to-sql'></a>\n",
    "\n",
    "## 10.1 Introduction to SQL"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "UFMFGCdwiw5k"
   },
   "source": [
    "**SQL (Structured Query Language)** is a programming language designed for managing data in Relational Data Base Management Systems (RDBMS), or for stream processing in Relational Data Stream Management Systems (RDSMS). A *relational database* is a database that stores related information across multiple tables, and allows to query information in more than one table at the same time. Within a table, the data is organized in a tabular format with rows and columns. \n",
    "\n",
    "SQL was initially developed in 1970, and since then different companies and vendors implemented SQL in their products with some variations. To bring greater conformity in the variants of SQL, the American National Standards Institute (ANSI) published the first SQL standard in 1986. The standard has been updated every few years since then. \n",
    "\n",
    "Today, there are several variants of SQL for database management systems available, some of which were developed by companies such as IBM and Oracle, as well as there are variants developed by communities, such as MySQL, PostgreSQL, MariaDB, etc. Although these variants of SQL have certain differences, they are based on the basic SQL syntax, and are quite similar.\n",
    "\n",
    "The main advantages of SQL include standardized syntax (since all relational database systems have an SQL query interpreter built-in), and is easy-to-understand due to using English-like commands and functions. "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "jzecVPPpneyL"
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   "source": [
    "### Relational Databases\n",
    "\n",
    "**Relational databases** store information in multiple tables, which allows to work with more complex data, and have flexibility in the way the data is organized. An example is shown in the next figure, where a database is shown that is used for managing the HR data of a small business. \n",
    "\n",
    "This database has seven tables:\n",
    "\n",
    "- Jobs table stores data related to job title and salary range.\n",
    "- Employees table stores the data of employees.\n",
    "- Dependents table stores the employee’s dependents.\n",
    "- Departments table stores department data.\n",
    "- Regions table stores the data of regions such as Asia, Europe, America, Middle East, and Africa. \n",
    "- Countries table stores the data of countries where the company is doing business.\n",
    "- Locations table stores the location of the departments of the company.\n",
    "\n",
    "Each table contains many records with rows and columns (similar to an Excel spreadsheet), and the records have relationships across the tables. Using multiple tables in a relational database allows us to avoid duplication of information, in comparison to using a single table to store all information. Also, it provides flexibility in how we work with the data. To establish relationships between the records in different tables we need to use an ID or identifier for each employee. The identifier for each employee, or in general for each record (row) in a relational database, is referred to as *primary key*. For instance, each employee can be assigned an ID value (such as employee 162), and each table would have an ID column (primary key column) to establish the relationship with the other tables in the database. \n",
    "\n",
    "\n",
    "<img src=\"images/SQL-Sample-Database.png\" width=\"600\">\n",
    "<em>Figure source: Reference [1].</em>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "_xVBgXO5uQkn"
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   "source": [
    "### SQL for Data Science\n",
    "\n",
    "SQL is a very important tool for data scientists, data analysts, developers, and database administrators. In particular, as many companies become data-driven, SQL becomes an essential tool for handling data stored in databases and performing various data analytics operations, such as calculating data statistics, updating records, removing duplicate columns, calculating correlations between records, and similar. \n",
    "\n",
    "### SQL versus Pandas\n",
    "\n",
    "SQL has similarities with the Pandas library, as it offers similar functionality to Pandas, which includes data manipulation over rows and columns, data merging, grouping, dealing with missing values, and similar. However, Pandas is not a relational database management library, but it is a data frame library. \n",
    "\n",
    "Still, Pandas offers additional functions and flexibility for handling and manipulating tabular data, and many users download databases to their local machine, and afterward use Pandas for data processing, rather than using SQL to process the data on the server.\n",
    "\n",
    "The benefits of using SQL over Pandas can depend on the task. Several considerations include:\n",
    "\n",
    "- In the case of a large database of information (e.g., GigaBytes of data), downloading the database to the local machine to be processed by Pandas may be slow or infeasible. Pandas is more suitable for processing small to medium size databases in Python. \n",
    "- Even if the user can download the data on the local machine for processing with Pandas, it may be required to apply some level of preprocessing or organizing the data on the server using SQL.\n",
    "- Some tasks can require that the data processing is done in the existing database. Also, when the tasks require fast data retrieval and processing, SQL can be more efficient than Pandas. \n",
    "\n",
    "\n",
    "### SQLite\n",
    "\n",
    "In this lecture, we will use **SQLite** which implements a self-contained, serverless SQL database engine. SQLite is lightweight in terms of setup and required recourses. Unlike most other SQL variants, SQLite does not have a separate server process, and it reads and writes directly to disk files. That is, it does not use the client/server model. Because it has no server managing access to it, SQLite is not suitable in multiuser environments where multiple people can simultaneously edit files."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "zvfWf2LnS5rS"
   },
   "source": [
    "## 10.2 Using SQLite with Python <a name='10.2-using-sqlite-with-python'></a>\n",
    "\n",
    "To demonstrate the use of SQLite with Python, in this lecture we will use *magic commands* in Jupyter Notebook. Magic commands are special commands which are not valid Python code, but perform certain actions in a Jupyter Notebook. They begin with the `%` symbol. \n",
    "\n",
    "The library `ipython-sql` offers the magic functions `%sql` and `%%sql`, which allow to connect to a database and use standard SQL commands in Jupyter Notebooks. To run `ipython-sql` on your computer, it needs to be installed (e.g., by `pip install ipython-sql`). If we run the notebooks on Google Colab, `ipython-sql` comes preinstalled.   \n",
    "\n",
    "To load the `ipython-sql` library we will use `%load_ext sql` as in the next code. `%load_ext` is a magic command that loads an external package that can add new magic commands. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "id": "hMeJOyz1K1mA"
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   "outputs": [],
   "source": [
    "%load_ext sql"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The magic command `%sql` is used to execute an SQL query that is contained in a single statement in a Jupyter notebook cell, and `%%sql` allows to execute an SQL query that is contained in multiple SQL statements in a single cell."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "weOcgGdx0PwM"
   },
   "source": [
    "## 10.3 Create a New Table <a name='10.3-create-a-new-table'></a>\n",
    "\n",
    "To create a new table we will use the SQL command `CREATE TABLE`, as shown in the next cell. If the table already exists in the database, an error message will show up. \n",
    "\n",
    "In order to establish a connection to the newly created table, we used `%%sql sqlite://` in the cell below. If we wanted to create a new table in an existing database to which we have already established a connection, we could have used only the magic command `%%sql`.\n",
    "\n",
    "SQL has many commands or keywords that have special meaning, such as SELECT, INSERT, DELETE, and these keywords cannot be used as names of tables, columns, or other objects. \n",
    "\n",
    "To make SQL language more readable, it is a convention to write the SQL commands with uppercase letters, and the other variables and identifiers with lowercase letters. However, this is not required, as the SQL commands are not case-sensitive.\n",
    "\n",
    "Let's create a table called `cars` which has 3 columns: `id`, `name`, and `price`. In the cell below, we specify that the values of `id` and `price` columns are integers, denoted by the `INTEGER` keyword. The names in the `name` column have a character string type (`VARCHAR`, i.e., variable-length character string) and should have at most 50 characters. We also specified with `NOT NULL` that the values should not be missing in the `id` and `name` columns, i.e., when we insert data into the table we have to specify the values for the `NON NULL` columns. \n",
    "\n",
    "Each table can have only one **PRIMARY KEY** column that uniquely identifies each row in the table, and prevents from inserting duplicate rows in the table. For the table below we set *PRIMARY KEY* to the `id` column. It is not required to define a primary key, however, it is a good practice to do it for every table. "
   ]
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  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "executionInfo": {
     "elapsed": 12,
     "status": "ok",
     "timestamp": 1668546497442,
     "user": {
      "displayName": "Aleksandar Vakanski",
      "userId": "07675307153279708378"
     },
     "user_tz": 420
    },
    "id": "oHRu6dxfafde",
    "outputId": "371a0d07-a3da-4067-bf9b-5621dbf1c15e"
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   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Done.\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "[]"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
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   ],
   "source": [
    "%%sql sqlite://\n",
    "CREATE TABLE cars(\n",
    "    id INTEGER NOT NULL PRIMARY KEY,\n",
    "    name VARCHAR(50) NOT NULL,  \n",
    "    price INTEGER);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "MpiDVSoLdDIM"
   },
   "source": [
    "The table that we just created is empty, and to add data to the table we will use the `INSERT` statement. In each row we provide values for `id`, `name`, and `price`.\n",
    "\n",
    "When using multiple statements in SQL, the statements in each line need to be separated with a semicolon `;`. The last statement in a cell does not have to be followed by a semicolon. \n",
    "\n",
    "Inline comments can be inserted by using two consecutive hyphens `--` that comment the rest of the line, as shown in the second line of the next cell. \n",
    "\n",
    "And also, comments that span multiple lines can be inserted by using the multiline C-style notation `/* comment */` as in the last lines in the cell.\n",
    "\n",
    "Note also that we used just the magic command `%%sql` in this cell, and we didn't need to write `%%sql sqlite://` as in the above cell. The reason is that in the above cell we used `%%sql sqlite://` to establish a connection to the newly created table. Once a connection is established, we can use only `%sql` or `%%sql` to work with the table."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "executionInfo": {
     "elapsed": 9,
     "status": "ok",
     "timestamp": 1668546497442,
     "user": {
      "displayName": "Aleksandar Vakanski",
      "userId": "07675307153279708378"
     },
     "user_tz": 420
    },
    "id": "mUgz3uE-cOer",
    "outputId": "2e2fb078-8087-441d-e886-e3c736a0d9fd"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " * sqlite://\n",
      "1 rows affected.\n",
      "1 rows affected.\n",
      "1 rows affected.\n",
      "1 rows affected.\n",
      "1 rows affected.\n",
      "1 rows affected.\n",
      "1 rows affected.\n",
      "1 rows affected.\n",
      "Done.\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "[]"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "%%sql \n",
    "INSERT INTO cars VALUES(1,'Audi',52642); --Two consecutive hyphens (--) comment the rest of the line\n",
    "INSERT INTO cars VALUES(2,'Mercedes',57127);\n",
    "INSERT INTO cars VALUES(3,'Skoda',9000);\n",
    "INSERT INTO cars VALUES(4,'Volvo',29000);\n",
    "INSERT INTO cars VALUES(5,'Bentley',350000);\n",
    "INSERT INTO cars VALUES(6,'Citroen',21000);\n",
    "INSERT INTO cars VALUES(7,'Hummer',41400);\n",
    "INSERT INTO cars VALUES(8,'Volkswagen',21600);\n",
    "/* A comment that spans\n",
    "more than one line */"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "R3JOV7fMdfAY"
   },
   "source": [
    "We can display the table with the following code. Notice again that we used a single `%` in the magic command `%sql`, since we have only one line of code. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 242
    },
    "executionInfo": {
     "elapsed": 272,
     "status": "ok",
     "timestamp": 1668546497709,
     "user": {
      "displayName": "Aleksandar Vakanski",
      "userId": "07675307153279708378"
     },
     "user_tz": 420
    },
    "id": "D5eyf0LwcOgs",
    "outputId": "d04ec49c-6e96-4d33-e32a-16812520a2ad"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " * sqlite://\n",
      "Done.\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<table>\n",
       "    <thead>\n",
       "        <tr>\n",
       "            <th>id</th>\n",
       "            <th>name</th>\n",
       "            <th>price</th>\n",
       "        </tr>\n",
       "    </thead>\n",
       "    <tbody>\n",
       "        <tr>\n",
       "            <td>1</td>\n",
       "            <td>Audi</td>\n",
       "            <td>52642</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>2</td>\n",
       "            <td>Mercedes</td>\n",
       "            <td>57127</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>3</td>\n",
       "            <td>Skoda</td>\n",
       "            <td>9000</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>4</td>\n",
       "            <td>Volvo</td>\n",
       "            <td>29000</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>5</td>\n",
       "            <td>Bentley</td>\n",
       "            <td>350000</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>6</td>\n",
       "            <td>Citroen</td>\n",
       "            <td>21000</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>7</td>\n",
       "            <td>Hummer</td>\n",
       "            <td>41400</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>8</td>\n",
       "            <td>Volkswagen</td>\n",
       "            <td>21600</td>\n",
       "        </tr>\n",
       "    </tbody>\n",
       "</table>"
      ],
      "text/plain": [
       "[(1, 'Audi', 52642),\n",
       " (2, 'Mercedes', 57127),\n",
       " (3, 'Skoda', 9000),\n",
       " (4, 'Volvo', 29000),\n",
       " (5, 'Bentley', 350000),\n",
       " (6, 'Citroen', 21000),\n",
       " (7, 'Hummer', 41400),\n",
       " (8, 'Volkswagen', 21600)]"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "%sql SELECT * from cars"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "zn1-QPcUdnY5"
   },
   "source": [
    "### Another Example of Creating a Table\n",
    "\n",
    "In the next simple example, we will create another table called `writer`, with columns `FirstName`, `LastName`, and `Year`. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "executionInfo": {
     "elapsed": 40,
     "status": "ok",
     "timestamp": 1668546497710,
     "user": {
      "displayName": "Aleksandar Vakanski",
      "userId": "07675307153279708378"
     },
     "user_tz": 420
    },
    "id": "M-CrMJ3w0PwT",
    "outputId": "9a4bbc66-0785-4f28-fae1-46da2384bd36"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Done.\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "[]"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "%%sql sqlite://\n",
    "CREATE TABLE writer(\n",
    "    FirstName VARCHAR(50) NOT NULL,\n",
    "    LastName VARCHAR(50) NOT NULL,  \n",
    "    Year INTEGER NOT NULL PRIMARY KEY);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "executionInfo": {
     "elapsed": 32,
     "status": "ok",
     "timestamp": 1668546497711,
     "user": {
      "displayName": "Aleksandar Vakanski",
      "userId": "07675307153279708378"
     },
     "user_tz": 420
    },
    "id": "OCNN60k90PwT",
    "outputId": "27303181-9606-4751-b5f8-9dfca42c96af"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " * sqlite://\n",
      "1 rows affected.\n",
      "1 rows affected.\n",
      "1 rows affected.\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "[]"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "%%sql \n",
    "INSERT INTO writer VALUES ('William', 'Shakespeare', 1616);\n",
    "INSERT INTO writer VALUES ('Lin', 'Han', 1996);\n",
    "INSERT INTO writer VALUES ('Peter', 'Brecht', 1978);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 137
    },
    "executionInfo": {
     "elapsed": 28,
     "status": "ok",
     "timestamp": 1668546497711,
     "user": {
      "displayName": "Aleksandar Vakanski",
      "userId": "07675307153279708378"
     },
     "user_tz": 420
    },
    "id": "qWFyb8PZ0PwU",
    "outputId": "93f9a888-a958-43e3-ace6-c5bb0003681f"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " * sqlite://\n",
      "Done.\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<table>\n",
       "    <thead>\n",
       "        <tr>\n",
       "            <th>FirstName</th>\n",
       "            <th>LastName</th>\n",
       "            <th>Year</th>\n",
       "        </tr>\n",
       "    </thead>\n",
       "    <tbody>\n",
       "        <tr>\n",
       "            <td>William</td>\n",
       "            <td>Shakespeare</td>\n",
       "            <td>1616</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>Peter</td>\n",
       "            <td>Brecht</td>\n",
       "            <td>1978</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>Lin</td>\n",
       "            <td>Han</td>\n",
       "            <td>1996</td>\n",
       "        </tr>\n",
       "    </tbody>\n",
       "</table>"
      ],
      "text/plain": [
       "[('William', 'Shakespeare', 1616),\n",
       " ('Peter', 'Brecht', 1978),\n",
       " ('Lin', 'Han', 1996)]"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "%sql SELECT * from writer"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "1QQ4GF4ZCppY"
   },
   "source": [
    "## 10.4 Database Example <a name='10.4-database-example'></a>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "E-5QpeTmCy_o"
   },
   "source": [
    "As an example of a database, let's create a database that was shown in the above section, related to managing the HR data of a small business. \n",
    "\n",
    "The cells below first create the tables (recall that the database has 7 tables), and afterward the information for each table is inserted."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "executionInfo": {
     "elapsed": 22,
     "status": "ok",
     "timestamp": 1668546497711,
     "user": {
      "displayName": "Aleksandar Vakanski",
      "userId": "07675307153279708378"
     },
     "user_tz": 420
    },
    "id": "0MdRe3Q4DXx3",
    "outputId": "d01d5e76-77f4-47cb-b035-8189ef7ca657"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Done.\n",
      "Done.\n",
      "Done.\n",
      "Done.\n",
      "Done.\n",
      "Done.\n",
      "Done.\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "[]"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "%%sql sqlite://\n",
    "\n",
    "CREATE TABLE regions (\n",
    "    region_id INTEGER PRIMARY KEY AUTOINCREMENT NOT NULL,\n",
    "    region_name TEXT NOT NULL);\n",
    "\n",
    "CREATE TABLE countries (\n",
    "    country_id TEXT NOT NULL,\n",
    "    country_name TEXT NOT NULL,\n",
    "    region_id INTEGER NOT NULL,\n",
    "    PRIMARY KEY (country_id ASC),\n",
    "    FOREIGN KEY (region_id) REFERENCES regions (region_id) ON DELETE CASCADE ON UPDATE CASCADE);\n",
    "\n",
    "CREATE TABLE locations (\n",
    "    location_id INTEGER PRIMARY KEY AUTOINCREMENT NOT NULL,\n",
    "    street_address TEXT,\n",
    "    postal_code TEXT,\n",
    "    city text NOT NULL,\n",
    "    state_province TEXT,\n",
    "    country_id INTEGER NOT NULL,\n",
    "    FOREIGN KEY (country_id) REFERENCES countries (country_id) ON DELETE CASCADE ON UPDATE CASCADE);\n",
    "\n",
    "CREATE TABLE departments (\n",
    "    department_id INTEGER PRIMARY KEY AUTOINCREMENT NOT NULL,\n",
    "    department_name TEXT NOT NULL,\n",
    "    location_id INTEGER NOT NULL,\n",
    "    FOREIGN KEY (location_id) REFERENCES locations (location_id) ON DELETE CASCADE ON UPDATE CASCADE);\n",
    "\n",
    "CREATE TABLE jobs (\n",
    "    job_id INTEGER PRIMARY KEY AUTOINCREMENT NOT NULL,\n",
    "    job_title TEXT NOT NULL,\n",
    "    min_salary DOUBLE NOT NULL,\n",
    "    max_salary DOUBLE NOT NULL);\n",
    "\n",
    "CREATE TABLE employees (\n",
    "    employee_id INTEGER PRIMARY KEY AUTOINCREMENT NOT NULL,\n",
    "    first_name TEXT,\n",
    "    last_name TEXT NOT NULL,\n",
    "    email TEXT NOT NULL,\n",
    "    phone_number TEXT,\n",
    "    hire_date TEXT NOT NULL,\n",
    "    job_id INTEGER NOT NULL,\n",
    "    salary DOUBLE NOT NULL,\n",
    "    manager_id INTEGER,\n",
    "    department_id INTEGER NOT NULL,\n",
    "    FOREIGN KEY (job_id) REFERENCES jobs (job_id) ON DELETE CASCADE ON UPDATE CASCADE,\n",
    "    FOREIGN KEY (department_id) REFERENCES departments (department_id) ON DELETE CASCADE ON UPDATE CASCADE,\n",
    "    FOREIGN KEY (manager_id) REFERENCES employees (employee_id) ON DELETE CASCADE ON UPDATE CASCADE);\n",
    "\n",
    "CREATE TABLE dependents (\n",
    "    dependent_id INTEGER PRIMARY KEY AUTOINCREMENT NOT NULL,\n",
    "    first_name TEXT NOT NULL,\n",
    "    last_name TEXT NOT NULL,\n",
    "    relationship TEXT NOT NULL,\n",
    "    employee_id INTEGER NOT NULL,\n",
    "    FOREIGN KEY (employee_id) REFERENCES employees (employee_id) ON DELETE CASCADE ON UPDATE CASCADE);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "executionInfo": {
     "elapsed": 522,
     "status": "ok",
     "timestamp": 1668546498217,
     "user": {
      "displayName": "Aleksandar Vakanski",
      "userId": "07675307153279708378"
     },
     "user_tz": 420
    },
    "id": "tHBt7diRDlCH",
    "outputId": "bc9dabb6-0d6b-4acd-a3a4-2a76ac40c1ff"
   },
   "outputs": [],
   "source": [
    "%%sql\n",
    "\n",
    "/*Data for the table regions */\n",
    "INSERT INTO regions(region_id,region_name) VALUES (1,'Europe');\n",
    "INSERT INTO regions(region_id,region_name) VALUES (2,'Americas');\n",
    "INSERT INTO regions(region_id,region_name) VALUES (3,'Asia');\n",
    "INSERT INTO regions(region_id,region_name) VALUES (4,'Middle East and Africa');\n",
    "\n",
    "/*Data for the table countries */\n",
    "INSERT INTO countries(country_id,country_name,region_id) VALUES ('AR','Argentina',2);\n",
    "INSERT INTO countries(country_id,country_name,region_id) VALUES ('AU','Australia',3);\n",
    "INSERT INTO countries(country_id,country_name,region_id) VALUES ('BE','Belgium',1);\n",
    "INSERT INTO countries(country_id,country_name,region_id) VALUES ('BR','Brazil',2);\n",
    "INSERT INTO countries(country_id,country_name,region_id) VALUES ('CA','Canada',2);\n",
    "INSERT INTO countries(country_id,country_name,region_id) VALUES ('CH','Switzerland',1);\n",
    "INSERT INTO countries(country_id,country_name,region_id) VALUES ('CN','China',3);\n",
    "INSERT INTO countries(country_id,country_name,region_id) VALUES ('DE','Germany',1);\n",
    "INSERT INTO countries(country_id,country_name,region_id) VALUES ('DK','Denmark',1);\n",
    "INSERT INTO countries(country_id,country_name,region_id) VALUES ('EG','Egypt',4);\n",
    "INSERT INTO countries(country_id,country_name,region_id) VALUES ('FR','France',1);\n",
    "INSERT INTO countries(country_id,country_name,region_id) VALUES ('HK','HongKong',3);\n",
    "INSERT INTO countries(country_id,country_name,region_id) VALUES ('IL','Israel',4);\n",
    "INSERT INTO countries(country_id,country_name,region_id) VALUES ('IN','India',3);\n",
    "INSERT INTO countries(country_id,country_name,region_id) VALUES ('IT','Italy',1);\n",
    "INSERT INTO countries(country_id,country_name,region_id) VALUES ('JP','Japan',3);\n",
    "INSERT INTO countries(country_id,country_name,region_id) VALUES ('KW','Kuwait',4);\n",
    "INSERT INTO countries(country_id,country_name,region_id) VALUES ('MX','Mexico',2);\n",
    "INSERT INTO countries(country_id,country_name,region_id) VALUES ('NG','Nigeria',4);\n",
    "INSERT INTO countries(country_id,country_name,region_id) VALUES ('NL','Netherlands',1);\n",
    "INSERT INTO countries(country_id,country_name,region_id) VALUES ('SG','Singapore',3);\n",
    "INSERT INTO countries(country_id,country_name,region_id) VALUES ('UK','United Kingdom',1);\n",
    "INSERT INTO countries(country_id,country_name,region_id) VALUES ('US','United States of America',2);\n",
    "INSERT INTO countries(country_id,country_name,region_id) VALUES ('ZM','Zambia',4);\n",
    "INSERT INTO countries(country_id,country_name,region_id) VALUES ('ZW','Zimbabwe',4);\n",
    "\n",
    "/*Data for the table locations */\n",
    "INSERT INTO locations(location_id,street_address,postal_code,city,state_province,country_id) VALUES (1400,'2014 Jabberwocky Rd','26192','Southlake','Texas','US');\n",
    "INSERT INTO locations(location_id,street_address,postal_code,city,state_province,country_id) VALUES (1500,'2011 Interiors Blvd','99236','South San Francisco','California','US');\n",
    "INSERT INTO locations(location_id,street_address,postal_code,city,state_province,country_id) VALUES (1700,'2004 Charade Rd','98199','Seattle','Washington','US');\n",
    "INSERT INTO locations(location_id,street_address,postal_code,city,state_province,country_id) VALUES (1800,'147 Spadina Ave','M5V 2L7','Toronto','Ontario','CA');\n",
    "INSERT INTO locations(location_id,street_address,postal_code,city,state_province,country_id) VALUES (2400,'8204 Arthur St',NULL,'London',NULL,'UK');\n",
    "INSERT INTO locations(location_id,street_address,postal_code,city,state_province,country_id) VALUES (2500,'Magdalen Centre, The Oxford Science Park','OX9 9ZB','Oxford','Oxford','UK');\n",
    "INSERT INTO locations(location_id,street_address,postal_code,city,state_province,country_id) VALUES (2700,'Schwanthalerstr. 7031','80925','Munich','Bavaria','DE');\n",
    "\n",
    "/*Data for the table jobs */\n",
    "INSERT INTO jobs(job_id,job_title,min_salary,max_salary) VALUES (1,'Public Accountant',4200.00,9000.00);\n",
    "INSERT INTO jobs(job_id,job_title,min_salary,max_salary) VALUES (2,'Accounting Manager',8200.00,16000.00);\n",
    "INSERT INTO jobs(job_id,job_title,min_salary,max_salary) VALUES (3,'Administration Assistant',3000.00,6000.00);\n",
    "INSERT INTO jobs(job_id,job_title,min_salary,max_salary) VALUES (4,'President',20000.00,40000.00);\n",
    "INSERT INTO jobs(job_id,job_title,min_salary,max_salary) VALUES (5,'Administration Vice President',15000.00,30000.00);\n",
    "INSERT INTO jobs(job_id,job_title,min_salary,max_salary) VALUES (6,'Accountant',4200.00,9000.00);\n",
    "INSERT INTO jobs(job_id,job_title,min_salary,max_salary) VALUES (7,'Finance Manager',8200.00,16000.00);\n",
    "INSERT INTO jobs(job_id,job_title,min_salary,max_salary) VALUES (8,'Human Resources Representative',4000.00,9000.00);\n",
    "INSERT INTO jobs(job_id,job_title,min_salary,max_salary) VALUES (9,'Programmer',4000.00,10000.00);\n",
    "INSERT INTO jobs(job_id,job_title,min_salary,max_salary) VALUES (10,'Marketing Manager',9000.00,15000.00);\n",
    "INSERT INTO jobs(job_id,job_title,min_salary,max_salary) VALUES (11,'Marketing Representative',4000.00,9000.00);\n",
    "INSERT INTO jobs(job_id,job_title,min_salary,max_salary) VALUES (12,'Public Relations Representative',4500.00,10500.00);\n",
    "INSERT INTO jobs(job_id,job_title,min_salary,max_salary) VALUES (13,'Purchasing Clerk',2500.00,5500.00);\n",
    "INSERT INTO jobs(job_id,job_title,min_salary,max_salary) VALUES (14,'Purchasing Manager',8000.00,15000.00);\n",
    "INSERT INTO jobs(job_id,job_title,min_salary,max_salary) VALUES (15,'Sales Manager',10000.00,20000.00);\n",
    "INSERT INTO jobs(job_id,job_title,min_salary,max_salary) VALUES (16,'Sales Representative',6000.00,12000.00);\n",
    "INSERT INTO jobs(job_id,job_title,min_salary,max_salary) VALUES (17,'Shipping Clerk',2500.00,5500.00);\n",
    "INSERT INTO jobs(job_id,job_title,min_salary,max_salary) VALUES (18,'Stock Clerk',2000.00,5000.00);\n",
    "INSERT INTO jobs(job_id,job_title,min_salary,max_salary) VALUES (19,'Stock Manager',5500.00,8500.00);\n",
    "\n",
    "/*Data for the table departments */\n",
    "INSERT INTO departments(department_id,department_name,location_id) VALUES (1,'Administration',1700);\n",
    "INSERT INTO departments(department_id,department_name,location_id) VALUES (2,'Marketing',1800);\n",
    "INSERT INTO departments(department_id,department_name,location_id) VALUES (3,'Purchasing',1700);\n",
    "INSERT INTO departments(department_id,department_name,location_id) VALUES (4,'Human Resources',2400);\n",
    "INSERT INTO departments(department_id,department_name,location_id) VALUES (5,'Shipping',1500);\n",
    "INSERT INTO departments(department_id,department_name,location_id) VALUES (6,'IT',1400);\n",
    "INSERT INTO departments(department_id,department_name,location_id) VALUES (7,'Public Relations',2700);\n",
    "INSERT INTO departments(department_id,department_name,location_id) VALUES (8,'Sales',2500);\n",
    "INSERT INTO departments(department_id,department_name,location_id) VALUES (9,'Executive',1700);\n",
    "INSERT INTO departments(department_id,department_name,location_id) VALUES (10,'Finance',1700);\n",
    "INSERT INTO departments(department_id,department_name,location_id) VALUES (11,'Accounting',1700);\n",
    "\n",
    "/*Data for the table employees */\n",
    "INSERT INTO employees(employee_id,first_name,last_name,email,phone_number,hire_date,job_id,salary,manager_id,department_id) VALUES (100,'Steven','King','steven.king@sqltutorial.org','515.123.4567','1987-06-17',4,24000.00,NULL,9);\n",
    "INSERT INTO employees(employee_id,first_name,last_name,email,phone_number,hire_date,job_id,salary,manager_id,department_id) VALUES (101,'Neena','Kochhar','neena.kochhar@sqltutorial.org','515.123.4568','1989-09-21',5,17000.00,100,9);\n",
    "INSERT INTO employees(employee_id,first_name,last_name,email,phone_number,hire_date,job_id,salary,manager_id,department_id) VALUES (102,'Lex','De Haan','lex.de haan@sqltutorial.org','515.123.4569','1993-01-13',5,17000.00,100,9);\n",
    "INSERT INTO employees(employee_id,first_name,last_name,email,phone_number,hire_date,job_id,salary,manager_id,department_id) VALUES (103,'Alexander','Hunold','alexander.hunold@sqltutorial.org','590.423.4567','1990-01-03',9,9000.00,102,6);\n",
    "INSERT INTO employees(employee_id,first_name,last_name,email,phone_number,hire_date,job_id,salary,manager_id,department_id) VALUES (104,'Bruce','Ernst','bruce.ernst@sqltutorial.org','590.423.4568','1991-05-21',9,6000.00,103,6);\n",
    "INSERT INTO employees(employee_id,first_name,last_name,email,phone_number,hire_date,job_id,salary,manager_id,department_id) VALUES (105,'David','Austin','david.austin@sqltutorial.org','590.423.4569','1997-06-25',9,4800.00,103,6);\n",
    "INSERT INTO employees(employee_id,first_name,last_name,email,phone_number,hire_date,job_id,salary,manager_id,department_id) VALUES (106,'Valli','Pataballa','valli.pataballa@sqltutorial.org','590.423.4560','1998-02-05',9,4800.00,103,6);\n",
    "INSERT INTO employees(employee_id,first_name,last_name,email,phone_number,hire_date,job_id,salary,manager_id,department_id) VALUES (107,'Diana','Lorentz','diana.lorentz@sqltutorial.org','590.423.5567','1999-02-07',9,4200.00,103,6);\n",
    "INSERT INTO employees(employee_id,first_name,last_name,email,phone_number,hire_date,job_id,salary,manager_id,department_id) VALUES (108,'Nancy','Greenberg','nancy.greenberg@sqltutorial.org','515.124.4569','1994-08-17',7,12000.00,101,10);\n",
    "INSERT INTO employees(employee_id,first_name,last_name,email,phone_number,hire_date,job_id,salary,manager_id,department_id) VALUES (109,'Daniel','Faviet','daniel.faviet@sqltutorial.org','515.124.4169','1994-08-16',6,9000.00,108,10);\n",
    "INSERT INTO employees(employee_id,first_name,last_name,email,phone_number,hire_date,job_id,salary,manager_id,department_id) VALUES (110,'John','Chen','john.chen@sqltutorial.org','515.124.4269','1997-09-28',6,8200.00,108,10);\n",
    "INSERT INTO employees(employee_id,first_name,last_name,email,phone_number,hire_date,job_id,salary,manager_id,department_id) VALUES (111,'Ismael','Sciarra','ismael.sciarra@sqltutorial.org','515.124.4369','1997-09-30',6,7700.00,108,10);\n",
    "INSERT INTO employees(employee_id,first_name,last_name,email,phone_number,hire_date,job_id,salary,manager_id,department_id) VALUES (112,'Jose Manuel','Urman','jose manuel.urman@sqltutorial.org','515.124.4469','1998-03-07',6,7800.00,108,10);\n",
    "INSERT INTO employees(employee_id,first_name,last_name,email,phone_number,hire_date,job_id,salary,manager_id,department_id) VALUES (113,'Luis','Popp','luis.popp@sqltutorial.org','515.124.4567','1999-12-07',6,6900.00,108,10);\n",
    "INSERT INTO employees(employee_id,first_name,last_name,email,phone_number,hire_date,job_id,salary,manager_id,department_id) VALUES (114,'Den','Raphaely','den.raphaely@sqltutorial.org','515.127.4561','1994-12-07',14,11000.00,100,3);\n",
    "INSERT INTO employees(employee_id,first_name,last_name,email,phone_number,hire_date,job_id,salary,manager_id,department_id) VALUES (115,'Alexander','Khoo','alexander.khoo@sqltutorial.org','515.127.4562','1995-05-18',13,3100.00,114,3);\n",
    "INSERT INTO employees(employee_id,first_name,last_name,email,phone_number,hire_date,job_id,salary,manager_id,department_id) VALUES (116,'Shelli','Baida','shelli.baida@sqltutorial.org','515.127.4563','1997-12-24',13,2900.00,114,3);\n",
    "INSERT INTO employees(employee_id,first_name,last_name,email,phone_number,hire_date,job_id,salary,manager_id,department_id) VALUES (117,'Sigal','Tobias','sigal.tobias@sqltutorial.org','515.127.4564','1997-07-24',13,2800.00,114,3);\n",
    "INSERT INTO employees(employee_id,first_name,last_name,email,phone_number,hire_date,job_id,salary,manager_id,department_id) VALUES (118,'Guy','Himuro','guy.himuro@sqltutorial.org','515.127.4565','1998-11-15',13,2600.00,114,3);\n",
    "INSERT INTO employees(employee_id,first_name,last_name,email,phone_number,hire_date,job_id,salary,manager_id,department_id) VALUES (119,'Karen','Colmenares','karen.colmenares@sqltutorial.org','515.127.4566','1999-08-10',13,2500.00,114,3);\n",
    "INSERT INTO employees(employee_id,first_name,last_name,email,phone_number,hire_date,job_id,salary,manager_id,department_id) VALUES (120,'Matthew','Weiss','matthew.weiss@sqltutorial.org','650.123.1234','1996-07-18',19,8000.00,100,5);\n",
    "INSERT INTO employees(employee_id,first_name,last_name,email,phone_number,hire_date,job_id,salary,manager_id,department_id) VALUES (121,'Adam','Fripp','adam.fripp@sqltutorial.org','650.123.2234','1997-04-10',19,8200.00,100,5);\n",
    "INSERT INTO employees(employee_id,first_name,last_name,email,phone_number,hire_date,job_id,salary,manager_id,department_id) VALUES (122,'Payam','Kaufling','payam.kaufling@sqltutorial.org','650.123.3234','1995-05-01',19,7900.00,100,5);\n",
    "INSERT INTO employees(employee_id,first_name,last_name,email,phone_number,hire_date,job_id,salary,manager_id,department_id) VALUES (123,'Shanta','Vollman','shanta.vollman@sqltutorial.org','650.123.4234','1997-10-10',19,6500.00,100,5);\n",
    "INSERT INTO employees(employee_id,first_name,last_name,email,phone_number,hire_date,job_id,salary,manager_id,department_id) VALUES (126,'Irene','Mikkilineni','irene.mikkilineni@sqltutorial.org','650.124.1224','1998-09-28',18,2700.00,120,5);\n",
    "INSERT INTO employees(employee_id,first_name,last_name,email,phone_number,hire_date,job_id,salary,manager_id,department_id) VALUES (145,'John','Russell','john.russell@sqltutorial.org',NULL,'1996-10-01',15,14000.00,100,8);\n",
    "INSERT INTO employees(employee_id,first_name,last_name,email,phone_number,hire_date,job_id,salary,manager_id,department_id) VALUES (146,'Karen','Partners','karen.partners@sqltutorial.org',NULL,'1997-01-05',15,13500.00,100,8);\n",
    "INSERT INTO employees(employee_id,first_name,last_name,email,phone_number,hire_date,job_id,salary,manager_id,department_id) VALUES (176,'Jonathon','Taylor','jonathon.taylor@sqltutorial.org',NULL,'1998-03-24',16,8600.00,100,8);\n",
    "INSERT INTO employees(employee_id,first_name,last_name,email,phone_number,hire_date,job_id,salary,manager_id,department_id) VALUES (177,'Jack','Livingston','jack.livingston@sqltutorial.org',NULL,'1998-04-23',16,8400.00,100,8);\n",
    "INSERT INTO employees(employee_id,first_name,last_name,email,phone_number,hire_date,job_id,salary,manager_id,department_id) VALUES (178,'Kimberely','Grant','kimberely.grant@sqltutorial.org',NULL,'1999-05-24',16,7000.00,100,8);\n",
    "INSERT INTO employees(employee_id,first_name,last_name,email,phone_number,hire_date,job_id,salary,manager_id,department_id) VALUES (179,'Charles','Johnson','charles.johnson@sqltutorial.org',NULL,'2000-01-04',16,6200.00,100,8);\n",
    "INSERT INTO employees(employee_id,first_name,last_name,email,phone_number,hire_date,job_id,salary,manager_id,department_id) VALUES (192,'Sarah','Bell','sarah.bell@sqltutorial.org','650.501.1876','1996-02-04',17,4000.00,123,5);\n",
    "INSERT INTO employees(employee_id,first_name,last_name,email,phone_number,hire_date,job_id,salary,manager_id,department_id) VALUES (193,'Britney','Everett','britney.everett@sqltutorial.org','650.501.2876','1997-03-03',17,3900.00,123,5);\n",
    "INSERT INTO employees(employee_id,first_name,last_name,email,phone_number,hire_date,job_id,salary,manager_id,department_id) VALUES (200,'Jennifer','Whalen','jennifer.whalen@sqltutorial.org','515.123.4444','1987-09-17',3,4400.00,101,1);\n",
    "INSERT INTO employees(employee_id,first_name,last_name,email,phone_number,hire_date,job_id,salary,manager_id,department_id) VALUES (201,'Michael','Hartstein','michael.hartstein@sqltutorial.org','515.123.5555','1996-02-17',10,13000.00,100,2);\n",
    "INSERT INTO employees(employee_id,first_name,last_name,email,phone_number,hire_date,job_id,salary,manager_id,department_id) VALUES (202,'Pat','Fay','pat.fay@sqltutorial.org','603.123.6666','1997-08-17',11,6000.00,201,2);\n",
    "INSERT INTO employees(employee_id,first_name,last_name,email,phone_number,hire_date,job_id,salary,manager_id,department_id) VALUES (203,'Susan','Mavris','susan.mavris@sqltutorial.org','515.123.7777','1994-06-07',8,6500.00,101,4);\n",
    "INSERT INTO employees(employee_id,first_name,last_name,email,phone_number,hire_date,job_id,salary,manager_id,department_id) VALUES (204,'Hermann','Baer','hermann.baer@sqltutorial.org','515.123.8888','1994-06-07',12,10000.00,101,7);\n",
    "INSERT INTO employees(employee_id,first_name,last_name,email,phone_number,hire_date,job_id,salary,manager_id,department_id) VALUES (205,'Shelley','Higgins','shelley.higgins@sqltutorial.org','515.123.8080','1994-06-07',2,12000.00,101,11);\n",
    "INSERT INTO employees(employee_id,first_name,last_name,email,phone_number,hire_date,job_id,salary,manager_id,department_id) VALUES (206,'William','Gietz','william.gietz@sqltutorial.org','515.123.8181','1994-06-07',1,8300.00,205,11);\n",
    "\n",
    "/*Data for the table dependents */\n",
    "INSERT INTO dependents(dependent_id,first_name,last_name,relationship,employee_id) VALUES (1,'Penelope','Gietz','Child',206);\n",
    "INSERT INTO dependents(dependent_id,first_name,last_name,relationship,employee_id) VALUES (2,'Nick','Higgins','Child',205);\n",
    "INSERT INTO dependents(dependent_id,first_name,last_name,relationship,employee_id) VALUES (3,'Ed','Whalen','Child',200);\n",
    "INSERT INTO dependents(dependent_id,first_name,last_name,relationship,employee_id) VALUES (4,'Jennifer','King','Child',100);\n",
    "INSERT INTO dependents(dependent_id,first_name,last_name,relationship,employee_id) VALUES (5,'Johnny','Kochhar','Child',101);\n",
    "INSERT INTO dependents(dependent_id,first_name,last_name,relationship,employee_id) VALUES (6,'Bette','De Haan','Child',102);\n",
    "INSERT INTO dependents(dependent_id,first_name,last_name,relationship,employee_id) VALUES (7,'Grace','Faviet','Child',109);\n",
    "INSERT INTO dependents(dependent_id,first_name,last_name,relationship,employee_id) VALUES (8,'Matthew','Chen','Child',110);\n",
    "INSERT INTO dependents(dependent_id,first_name,last_name,relationship,employee_id) VALUES (9,'Joe','Sciarra','Child',111);\n",
    "INSERT INTO dependents(dependent_id,first_name,last_name,relationship,employee_id) VALUES (10,'Christian','Urman','Child',112);\n",
    "INSERT INTO dependents(dependent_id,first_name,last_name,relationship,employee_id) VALUES (11,'Zero','Popp','Child',113);\n",
    "INSERT INTO dependents(dependent_id,first_name,last_name,relationship,employee_id) VALUES (12,'Karl','Greenberg','Child',108);\n",
    "INSERT INTO dependents(dependent_id,first_name,last_name,relationship,employee_id) VALUES (13,'Uma','Mavris','Child',203);\n",
    "INSERT INTO dependents(dependent_id,first_name,last_name,relationship,employee_id) VALUES (14,'Vivien','Hunold','Child',103);\n",
    "INSERT INTO dependents(dependent_id,first_name,last_name,relationship,employee_id) VALUES (15,'Cuba','Ernst','Child',104);\n",
    "INSERT INTO dependents(dependent_id,first_name,last_name,relationship,employee_id) VALUES (16,'Fred','Austin','Child',105);\n",
    "INSERT INTO dependents(dependent_id,first_name,last_name,relationship,employee_id) VALUES (17,'Helen','Pataballa','Child',106);\n",
    "INSERT INTO dependents(dependent_id,first_name,last_name,relationship,employee_id) VALUES (18,'Dan','Lorentz','Child',107);\n",
    "INSERT INTO dependents(dependent_id,first_name,last_name,relationship,employee_id) VALUES (19,'Bob','Hartstein','Child',201);\n",
    "INSERT INTO dependents(dependent_id,first_name,last_name,relationship,employee_id) VALUES (20,'Lucille','Fay','Child',202);\n",
    "INSERT INTO dependents(dependent_id,first_name,last_name,relationship,employee_id) VALUES (21,'Kirsten','Baer','Child',204);\n",
    "INSERT INTO dependents(dependent_id,first_name,last_name,relationship,employee_id) VALUES (22,'Elvis','Khoo','Child',115);\n",
    "INSERT INTO dependents(dependent_id,first_name,last_name,relationship,employee_id) VALUES (23,'Sandra','Baida','Child',116);\n",
    "INSERT INTO dependents(dependent_id,first_name,last_name,relationship,employee_id) VALUES (24,'Cameron','Tobias','Child',117);\n",
    "INSERT INTO dependents(dependent_id,first_name,last_name,relationship,employee_id) VALUES (25,'Kevin','Himuro','Child',118);\n",
    "INSERT INTO dependents(dependent_id,first_name,last_name,relationship,employee_id) VALUES (26,'Rip','Colmenares','Child',119);\n",
    "INSERT INTO dependents(dependent_id,first_name,last_name,relationship,employee_id) VALUES (27,'Julia','Raphaely','Child',114);\n",
    "INSERT INTO dependents(dependent_id,first_name,last_name,relationship,employee_id) VALUES (28,'Woody','Russell','Child',145);\n",
    "INSERT INTO dependents(dependent_id,first_name,last_name,relationship,employee_id) VALUES (29,'Alec','Partners','Child',146);\n",
    "INSERT INTO dependents(dependent_id,first_name,last_name,relationship,employee_id) VALUES (30,'Sandra','Taylor','Child',176);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "Qw0BNTykEFoU"
   },
   "source": [
    "## 10.5 Querying Databases with SELECT <a name='10.5-querying-databases-with-select'></a>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "VtbDRnddUVhA"
   },
   "source": [
    "The most common SQL task is to retrieve data from one or more tables. The data is returned in the form of a result table, called *result set*. This is accomplished with the `SELECT` statement, which has the following general syntax. \n",
    "\n",
    "```\n",
    "SELECT \n",
    "    column1, column2, columnN \n",
    "FROM \n",
    "    table_name\n",
    "```\n",
    "\n",
    "To run the code in this Jupyter Notebook, we will just insert the magic commands `%sql` or `%%sql` in front of each SQL code.  \n",
    "\n",
    "For example, in the next cell we retrieved the columns `employee_id, first_name, last_name, hire_date` from the `employees` table. When the statement is evaluated, the database system first evaluates the `FROM` clause and the `SELECT` clause afterward. I.e., from the table named `employees` select the listed columns.\n",
    "\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 912
    },
    "executionInfo": {
     "elapsed": 43,
     "status": "ok",
     "timestamp": 1668546498219,
     "user": {
      "displayName": "Aleksandar Vakanski",
      "userId": "07675307153279708378"
     },
     "user_tz": 420
    },
    "id": "kE7T_NrIiALM",
    "outputId": "9b6ebb17-e4a4-4e55-e535-4f0a3d635a2e"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " * sqlite://\n",
      "Done.\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<table>\n",
       "    <thead>\n",
       "        <tr>\n",
       "            <th>employee_id</th>\n",
       "            <th>first_name</th>\n",
       "            <th>last_name</th>\n",
       "            <th>hire_date</th>\n",
       "        </tr>\n",
       "    </thead>\n",
       "    <tbody>\n",
       "        <tr>\n",
       "            <td>100</td>\n",
       "            <td>Steven</td>\n",
       "            <td>King</td>\n",
       "            <td>1987-06-17</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>101</td>\n",
       "            <td>Neena</td>\n",
       "            <td>Kochhar</td>\n",
       "            <td>1989-09-21</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>102</td>\n",
       "            <td>Lex</td>\n",
       "            <td>De Haan</td>\n",
       "            <td>1993-01-13</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>103</td>\n",
       "            <td>Alexander</td>\n",
       "            <td>Hunold</td>\n",
       "            <td>1990-01-03</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>104</td>\n",
       "            <td>Bruce</td>\n",
       "            <td>Ernst</td>\n",
       "            <td>1991-05-21</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>105</td>\n",
       "            <td>David</td>\n",
       "            <td>Austin</td>\n",
       "            <td>1997-06-25</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>106</td>\n",
       "            <td>Valli</td>\n",
       "            <td>Pataballa</td>\n",
       "            <td>1998-02-05</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>107</td>\n",
       "            <td>Diana</td>\n",
       "            <td>Lorentz</td>\n",
       "            <td>1999-02-07</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>108</td>\n",
       "            <td>Nancy</td>\n",
       "            <td>Greenberg</td>\n",
       "            <td>1994-08-17</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>109</td>\n",
       "            <td>Daniel</td>\n",
       "            <td>Faviet</td>\n",
       "            <td>1994-08-16</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>110</td>\n",
       "            <td>John</td>\n",
       "            <td>Chen</td>\n",
       "            <td>1997-09-28</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>111</td>\n",
       "            <td>Ismael</td>\n",
       "            <td>Sciarra</td>\n",
       "            <td>1997-09-30</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>112</td>\n",
       "            <td>Jose Manuel</td>\n",
       "            <td>Urman</td>\n",
       "            <td>1998-03-07</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>113</td>\n",
       "            <td>Luis</td>\n",
       "            <td>Popp</td>\n",
       "            <td>1999-12-07</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>114</td>\n",
       "            <td>Den</td>\n",
       "            <td>Raphaely</td>\n",
       "            <td>1994-12-07</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>115</td>\n",
       "            <td>Alexander</td>\n",
       "            <td>Khoo</td>\n",
       "            <td>1995-05-18</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>116</td>\n",
       "            <td>Shelli</td>\n",
       "            <td>Baida</td>\n",
       "            <td>1997-12-24</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>117</td>\n",
       "            <td>Sigal</td>\n",
       "            <td>Tobias</td>\n",
       "            <td>1997-07-24</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>118</td>\n",
       "            <td>Guy</td>\n",
       "            <td>Himuro</td>\n",
       "            <td>1998-11-15</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>119</td>\n",
       "            <td>Karen</td>\n",
       "            <td>Colmenares</td>\n",
       "            <td>1999-08-10</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>120</td>\n",
       "            <td>Matthew</td>\n",
       "            <td>Weiss</td>\n",
       "            <td>1996-07-18</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>121</td>\n",
       "            <td>Adam</td>\n",
       "            <td>Fripp</td>\n",
       "            <td>1997-04-10</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>122</td>\n",
       "            <td>Payam</td>\n",
       "            <td>Kaufling</td>\n",
       "            <td>1995-05-01</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>123</td>\n",
       "            <td>Shanta</td>\n",
       "            <td>Vollman</td>\n",
       "            <td>1997-10-10</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>126</td>\n",
       "            <td>Irene</td>\n",
       "            <td>Mikkilineni</td>\n",
       "            <td>1998-09-28</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>145</td>\n",
       "            <td>John</td>\n",
       "            <td>Russell</td>\n",
       "            <td>1996-10-01</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>146</td>\n",
       "            <td>Karen</td>\n",
       "            <td>Partners</td>\n",
       "            <td>1997-01-05</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>176</td>\n",
       "            <td>Jonathon</td>\n",
       "            <td>Taylor</td>\n",
       "            <td>1998-03-24</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>177</td>\n",
       "            <td>Jack</td>\n",
       "            <td>Livingston</td>\n",
       "            <td>1998-04-23</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>178</td>\n",
       "            <td>Kimberely</td>\n",
       "            <td>Grant</td>\n",
       "            <td>1999-05-24</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>179</td>\n",
       "            <td>Charles</td>\n",
       "            <td>Johnson</td>\n",
       "            <td>2000-01-04</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>192</td>\n",
       "            <td>Sarah</td>\n",
       "            <td>Bell</td>\n",
       "            <td>1996-02-04</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>193</td>\n",
       "            <td>Britney</td>\n",
       "            <td>Everett</td>\n",
       "            <td>1997-03-03</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>200</td>\n",
       "            <td>Jennifer</td>\n",
       "            <td>Whalen</td>\n",
       "            <td>1987-09-17</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>201</td>\n",
       "            <td>Michael</td>\n",
       "            <td>Hartstein</td>\n",
       "            <td>1996-02-17</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>202</td>\n",
       "            <td>Pat</td>\n",
       "            <td>Fay</td>\n",
       "            <td>1997-08-17</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>203</td>\n",
       "            <td>Susan</td>\n",
       "            <td>Mavris</td>\n",
       "            <td>1994-06-07</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>204</td>\n",
       "            <td>Hermann</td>\n",
       "            <td>Baer</td>\n",
       "            <td>1994-06-07</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>205</td>\n",
       "            <td>Shelley</td>\n",
       "            <td>Higgins</td>\n",
       "            <td>1994-06-07</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>206</td>\n",
       "            <td>William</td>\n",
       "            <td>Gietz</td>\n",
       "            <td>1994-06-07</td>\n",
       "        </tr>\n",
       "    </tbody>\n",
       "</table>"
      ],
      "text/plain": [
       "[(100, 'Steven', 'King', '1987-06-17'),\n",
       " (101, 'Neena', 'Kochhar', '1989-09-21'),\n",
       " (102, 'Lex', 'De Haan', '1993-01-13'),\n",
       " (103, 'Alexander', 'Hunold', '1990-01-03'),\n",
       " (104, 'Bruce', 'Ernst', '1991-05-21'),\n",
       " (105, 'David', 'Austin', '1997-06-25'),\n",
       " (106, 'Valli', 'Pataballa', '1998-02-05'),\n",
       " (107, 'Diana', 'Lorentz', '1999-02-07'),\n",
       " (108, 'Nancy', 'Greenberg', '1994-08-17'),\n",
       " (109, 'Daniel', 'Faviet', '1994-08-16'),\n",
       " (110, 'John', 'Chen', '1997-09-28'),\n",
       " (111, 'Ismael', 'Sciarra', '1997-09-30'),\n",
       " (112, 'Jose Manuel', 'Urman', '1998-03-07'),\n",
       " (113, 'Luis', 'Popp', '1999-12-07'),\n",
       " (114, 'Den', 'Raphaely', '1994-12-07'),\n",
       " (115, 'Alexander', 'Khoo', '1995-05-18'),\n",
       " (116, 'Shelli', 'Baida', '1997-12-24'),\n",
       " (117, 'Sigal', 'Tobias', '1997-07-24'),\n",
       " (118, 'Guy', 'Himuro', '1998-11-15'),\n",
       " (119, 'Karen', 'Colmenares', '1999-08-10'),\n",
       " (120, 'Matthew', 'Weiss', '1996-07-18'),\n",
       " (121, 'Adam', 'Fripp', '1997-04-10'),\n",
       " (122, 'Payam', 'Kaufling', '1995-05-01'),\n",
       " (123, 'Shanta', 'Vollman', '1997-10-10'),\n",
       " (126, 'Irene', 'Mikkilineni', '1998-09-28'),\n",
       " (145, 'John', 'Russell', '1996-10-01'),\n",
       " (146, 'Karen', 'Partners', '1997-01-05'),\n",
       " (176, 'Jonathon', 'Taylor', '1998-03-24'),\n",
       " (177, 'Jack', 'Livingston', '1998-04-23'),\n",
       " (178, 'Kimberely', 'Grant', '1999-05-24'),\n",
       " (179, 'Charles', 'Johnson', '2000-01-04'),\n",
       " (192, 'Sarah', 'Bell', '1996-02-04'),\n",
       " (193, 'Britney', 'Everett', '1997-03-03'),\n",
       " (200, 'Jennifer', 'Whalen', '1987-09-17'),\n",
       " (201, 'Michael', 'Hartstein', '1996-02-17'),\n",
       " (202, 'Pat', 'Fay', '1997-08-17'),\n",
       " (203, 'Susan', 'Mavris', '1994-06-07'),\n",
       " (204, 'Hermann', 'Baer', '1994-06-07'),\n",
       " (205, 'Shelley', 'Higgins', '1994-06-07'),\n",
       " (206, 'William', 'Gietz', '1994-06-07')]"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "%%sql \n",
    "SELECT \n",
    "    employee_id, first_name, last_name, hire_date \n",
    "FROM \n",
    "    employees"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "XVloOe3kh8S1"
   },
   "source": [
    "If we want to query all columns in a table we can use the asterisk operator `*` instead of the columns names. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 912
    },
    "executionInfo": {
     "elapsed": 40,
     "status": "ok",
     "timestamp": 1668546498219,
     "user": {
      "displayName": "Aleksandar Vakanski",
      "userId": "07675307153279708378"
     },
     "user_tz": 420
    },
    "id": "hvkAE1EzhTfG",
    "outputId": "30b008b8-9250-46aa-9386-4b8bb67e8a84"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " * sqlite://\n",
      "Done.\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<table>\n",
       "    <thead>\n",
       "        <tr>\n",
       "            <th>employee_id</th>\n",
       "            <th>first_name</th>\n",
       "            <th>last_name</th>\n",
       "            <th>email</th>\n",
       "            <th>phone_number</th>\n",
       "            <th>hire_date</th>\n",
       "            <th>job_id</th>\n",
       "            <th>salary</th>\n",
       "            <th>manager_id</th>\n",
       "            <th>department_id</th>\n",
       "        </tr>\n",
       "    </thead>\n",
       "    <tbody>\n",
       "        <tr>\n",
       "            <td>100</td>\n",
       "            <td>Steven</td>\n",
       "            <td>King</td>\n",
       "            <td>steven.king@sqltutorial.org</td>\n",
       "            <td>515.123.4567</td>\n",
       "            <td>1987-06-17</td>\n",
       "            <td>4</td>\n",
       "            <td>24000.0</td>\n",
       "            <td>None</td>\n",
       "            <td>9</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>101</td>\n",
       "            <td>Neena</td>\n",
       "            <td>Kochhar</td>\n",
       "            <td>neena.kochhar@sqltutorial.org</td>\n",
       "            <td>515.123.4568</td>\n",
       "            <td>1989-09-21</td>\n",
       "            <td>5</td>\n",
       "            <td>17000.0</td>\n",
       "            <td>100</td>\n",
       "            <td>9</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>102</td>\n",
       "            <td>Lex</td>\n",
       "            <td>De Haan</td>\n",
       "            <td>lex.de haan@sqltutorial.org</td>\n",
       "            <td>515.123.4569</td>\n",
       "            <td>1993-01-13</td>\n",
       "            <td>5</td>\n",
       "            <td>17000.0</td>\n",
       "            <td>100</td>\n",
       "            <td>9</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>103</td>\n",
       "            <td>Alexander</td>\n",
       "            <td>Hunold</td>\n",
       "            <td>alexander.hunold@sqltutorial.org</td>\n",
       "            <td>590.423.4567</td>\n",
       "            <td>1990-01-03</td>\n",
       "            <td>9</td>\n",
       "            <td>9000.0</td>\n",
       "            <td>102</td>\n",
       "            <td>6</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>104</td>\n",
       "            <td>Bruce</td>\n",
       "            <td>Ernst</td>\n",
       "            <td>bruce.ernst@sqltutorial.org</td>\n",
       "            <td>590.423.4568</td>\n",
       "            <td>1991-05-21</td>\n",
       "            <td>9</td>\n",
       "            <td>6000.0</td>\n",
       "            <td>103</td>\n",
       "            <td>6</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>105</td>\n",
       "            <td>David</td>\n",
       "            <td>Austin</td>\n",
       "            <td>david.austin@sqltutorial.org</td>\n",
       "            <td>590.423.4569</td>\n",
       "            <td>1997-06-25</td>\n",
       "            <td>9</td>\n",
       "            <td>4800.0</td>\n",
       "            <td>103</td>\n",
       "            <td>6</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>106</td>\n",
       "            <td>Valli</td>\n",
       "            <td>Pataballa</td>\n",
       "            <td>valli.pataballa@sqltutorial.org</td>\n",
       "            <td>590.423.4560</td>\n",
       "            <td>1998-02-05</td>\n",
       "            <td>9</td>\n",
       "            <td>4800.0</td>\n",
       "            <td>103</td>\n",
       "            <td>6</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>107</td>\n",
       "            <td>Diana</td>\n",
       "            <td>Lorentz</td>\n",
       "            <td>diana.lorentz@sqltutorial.org</td>\n",
       "            <td>590.423.5567</td>\n",
       "            <td>1999-02-07</td>\n",
       "            <td>9</td>\n",
       "            <td>4200.0</td>\n",
       "            <td>103</td>\n",
       "            <td>6</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>108</td>\n",
       "            <td>Nancy</td>\n",
       "            <td>Greenberg</td>\n",
       "            <td>nancy.greenberg@sqltutorial.org</td>\n",
       "            <td>515.124.4569</td>\n",
       "            <td>1994-08-17</td>\n",
       "            <td>7</td>\n",
       "            <td>12000.0</td>\n",
       "            <td>101</td>\n",
       "            <td>10</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>109</td>\n",
       "            <td>Daniel</td>\n",
       "            <td>Faviet</td>\n",
       "            <td>daniel.faviet@sqltutorial.org</td>\n",
       "            <td>515.124.4169</td>\n",
       "            <td>1994-08-16</td>\n",
       "            <td>6</td>\n",
       "            <td>9000.0</td>\n",
       "            <td>108</td>\n",
       "            <td>10</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>110</td>\n",
       "            <td>John</td>\n",
       "            <td>Chen</td>\n",
       "            <td>john.chen@sqltutorial.org</td>\n",
       "            <td>515.124.4269</td>\n",
       "            <td>1997-09-28</td>\n",
       "            <td>6</td>\n",
       "            <td>8200.0</td>\n",
       "            <td>108</td>\n",
       "            <td>10</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>111</td>\n",
       "            <td>Ismael</td>\n",
       "            <td>Sciarra</td>\n",
       "            <td>ismael.sciarra@sqltutorial.org</td>\n",
       "            <td>515.124.4369</td>\n",
       "            <td>1997-09-30</td>\n",
       "            <td>6</td>\n",
       "            <td>7700.0</td>\n",
       "            <td>108</td>\n",
       "            <td>10</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>112</td>\n",
       "            <td>Jose Manuel</td>\n",
       "            <td>Urman</td>\n",
       "            <td>jose manuel.urman@sqltutorial.org</td>\n",
       "            <td>515.124.4469</td>\n",
       "            <td>1998-03-07</td>\n",
       "            <td>6</td>\n",
       "            <td>7800.0</td>\n",
       "            <td>108</td>\n",
       "            <td>10</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>113</td>\n",
       "            <td>Luis</td>\n",
       "            <td>Popp</td>\n",
       "            <td>luis.popp@sqltutorial.org</td>\n",
       "            <td>515.124.4567</td>\n",
       "            <td>1999-12-07</td>\n",
       "            <td>6</td>\n",
       "            <td>6900.0</td>\n",
       "            <td>108</td>\n",
       "            <td>10</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>114</td>\n",
       "            <td>Den</td>\n",
       "            <td>Raphaely</td>\n",
       "            <td>den.raphaely@sqltutorial.org</td>\n",
       "            <td>515.127.4561</td>\n",
       "            <td>1994-12-07</td>\n",
       "            <td>14</td>\n",
       "            <td>11000.0</td>\n",
       "            <td>100</td>\n",
       "            <td>3</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>115</td>\n",
       "            <td>Alexander</td>\n",
       "            <td>Khoo</td>\n",
       "            <td>alexander.khoo@sqltutorial.org</td>\n",
       "            <td>515.127.4562</td>\n",
       "            <td>1995-05-18</td>\n",
       "            <td>13</td>\n",
       "            <td>3100.0</td>\n",
       "            <td>114</td>\n",
       "            <td>3</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>116</td>\n",
       "            <td>Shelli</td>\n",
       "            <td>Baida</td>\n",
       "            <td>shelli.baida@sqltutorial.org</td>\n",
       "            <td>515.127.4563</td>\n",
       "            <td>1997-12-24</td>\n",
       "            <td>13</td>\n",
       "            <td>2900.0</td>\n",
       "            <td>114</td>\n",
       "            <td>3</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>117</td>\n",
       "            <td>Sigal</td>\n",
       "            <td>Tobias</td>\n",
       "            <td>sigal.tobias@sqltutorial.org</td>\n",
       "            <td>515.127.4564</td>\n",
       "            <td>1997-07-24</td>\n",
       "            <td>13</td>\n",
       "            <td>2800.0</td>\n",
       "            <td>114</td>\n",
       "            <td>3</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>118</td>\n",
       "            <td>Guy</td>\n",
       "            <td>Himuro</td>\n",
       "            <td>guy.himuro@sqltutorial.org</td>\n",
       "            <td>515.127.4565</td>\n",
       "            <td>1998-11-15</td>\n",
       "            <td>13</td>\n",
       "            <td>2600.0</td>\n",
       "            <td>114</td>\n",
       "            <td>3</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>119</td>\n",
       "            <td>Karen</td>\n",
       "            <td>Colmenares</td>\n",
       "            <td>karen.colmenares@sqltutorial.org</td>\n",
       "            <td>515.127.4566</td>\n",
       "            <td>1999-08-10</td>\n",
       "            <td>13</td>\n",
       "            <td>2500.0</td>\n",
       "            <td>114</td>\n",
       "            <td>3</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>120</td>\n",
       "            <td>Matthew</td>\n",
       "            <td>Weiss</td>\n",
       "            <td>matthew.weiss@sqltutorial.org</td>\n",
       "            <td>650.123.1234</td>\n",
       "            <td>1996-07-18</td>\n",
       "            <td>19</td>\n",
       "            <td>8000.0</td>\n",
       "            <td>100</td>\n",
       "            <td>5</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>121</td>\n",
       "            <td>Adam</td>\n",
       "            <td>Fripp</td>\n",
       "            <td>adam.fripp@sqltutorial.org</td>\n",
       "            <td>650.123.2234</td>\n",
       "            <td>1997-04-10</td>\n",
       "            <td>19</td>\n",
       "            <td>8200.0</td>\n",
       "            <td>100</td>\n",
       "            <td>5</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>122</td>\n",
       "            <td>Payam</td>\n",
       "            <td>Kaufling</td>\n",
       "            <td>payam.kaufling@sqltutorial.org</td>\n",
       "            <td>650.123.3234</td>\n",
       "            <td>1995-05-01</td>\n",
       "            <td>19</td>\n",
       "            <td>7900.0</td>\n",
       "            <td>100</td>\n",
       "            <td>5</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>123</td>\n",
       "            <td>Shanta</td>\n",
       "            <td>Vollman</td>\n",
       "            <td>shanta.vollman@sqltutorial.org</td>\n",
       "            <td>650.123.4234</td>\n",
       "            <td>1997-10-10</td>\n",
       "            <td>19</td>\n",
       "            <td>6500.0</td>\n",
       "            <td>100</td>\n",
       "            <td>5</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>126</td>\n",
       "            <td>Irene</td>\n",
       "            <td>Mikkilineni</td>\n",
       "            <td>irene.mikkilineni@sqltutorial.org</td>\n",
       "            <td>650.124.1224</td>\n",
       "            <td>1998-09-28</td>\n",
       "            <td>18</td>\n",
       "            <td>2700.0</td>\n",
       "            <td>120</td>\n",
       "            <td>5</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>145</td>\n",
       "            <td>John</td>\n",
       "            <td>Russell</td>\n",
       "            <td>john.russell@sqltutorial.org</td>\n",
       "            <td>None</td>\n",
       "            <td>1996-10-01</td>\n",
       "            <td>15</td>\n",
       "            <td>14000.0</td>\n",
       "            <td>100</td>\n",
       "            <td>8</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>146</td>\n",
       "            <td>Karen</td>\n",
       "            <td>Partners</td>\n",
       "            <td>karen.partners@sqltutorial.org</td>\n",
       "            <td>None</td>\n",
       "            <td>1997-01-05</td>\n",
       "            <td>15</td>\n",
       "            <td>13500.0</td>\n",
       "            <td>100</td>\n",
       "            <td>8</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>176</td>\n",
       "            <td>Jonathon</td>\n",
       "            <td>Taylor</td>\n",
       "            <td>jonathon.taylor@sqltutorial.org</td>\n",
       "            <td>None</td>\n",
       "            <td>1998-03-24</td>\n",
       "            <td>16</td>\n",
       "            <td>8600.0</td>\n",
       "            <td>100</td>\n",
       "            <td>8</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>177</td>\n",
       "            <td>Jack</td>\n",
       "            <td>Livingston</td>\n",
       "            <td>jack.livingston@sqltutorial.org</td>\n",
       "            <td>None</td>\n",
       "            <td>1998-04-23</td>\n",
       "            <td>16</td>\n",
       "            <td>8400.0</td>\n",
       "            <td>100</td>\n",
       "            <td>8</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>178</td>\n",
       "            <td>Kimberely</td>\n",
       "            <td>Grant</td>\n",
       "            <td>kimberely.grant@sqltutorial.org</td>\n",
       "            <td>None</td>\n",
       "            <td>1999-05-24</td>\n",
       "            <td>16</td>\n",
       "            <td>7000.0</td>\n",
       "            <td>100</td>\n",
       "            <td>8</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>179</td>\n",
       "            <td>Charles</td>\n",
       "            <td>Johnson</td>\n",
       "            <td>charles.johnson@sqltutorial.org</td>\n",
       "            <td>None</td>\n",
       "            <td>2000-01-04</td>\n",
       "            <td>16</td>\n",
       "            <td>6200.0</td>\n",
       "            <td>100</td>\n",
       "            <td>8</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>192</td>\n",
       "            <td>Sarah</td>\n",
       "            <td>Bell</td>\n",
       "            <td>sarah.bell@sqltutorial.org</td>\n",
       "            <td>650.501.1876</td>\n",
       "            <td>1996-02-04</td>\n",
       "            <td>17</td>\n",
       "            <td>4000.0</td>\n",
       "            <td>123</td>\n",
       "            <td>5</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>193</td>\n",
       "            <td>Britney</td>\n",
       "            <td>Everett</td>\n",
       "            <td>britney.everett@sqltutorial.org</td>\n",
       "            <td>650.501.2876</td>\n",
       "            <td>1997-03-03</td>\n",
       "            <td>17</td>\n",
       "            <td>3900.0</td>\n",
       "            <td>123</td>\n",
       "            <td>5</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>200</td>\n",
       "            <td>Jennifer</td>\n",
       "            <td>Whalen</td>\n",
       "            <td>jennifer.whalen@sqltutorial.org</td>\n",
       "            <td>515.123.4444</td>\n",
       "            <td>1987-09-17</td>\n",
       "            <td>3</td>\n",
       "            <td>4400.0</td>\n",
       "            <td>101</td>\n",
       "            <td>1</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>201</td>\n",
       "            <td>Michael</td>\n",
       "            <td>Hartstein</td>\n",
       "            <td>michael.hartstein@sqltutorial.org</td>\n",
       "            <td>515.123.5555</td>\n",
       "            <td>1996-02-17</td>\n",
       "            <td>10</td>\n",
       "            <td>13000.0</td>\n",
       "            <td>100</td>\n",
       "            <td>2</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>202</td>\n",
       "            <td>Pat</td>\n",
       "            <td>Fay</td>\n",
       "            <td>pat.fay@sqltutorial.org</td>\n",
       "            <td>603.123.6666</td>\n",
       "            <td>1997-08-17</td>\n",
       "            <td>11</td>\n",
       "            <td>6000.0</td>\n",
       "            <td>201</td>\n",
       "            <td>2</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>203</td>\n",
       "            <td>Susan</td>\n",
       "            <td>Mavris</td>\n",
       "            <td>susan.mavris@sqltutorial.org</td>\n",
       "            <td>515.123.7777</td>\n",
       "            <td>1994-06-07</td>\n",
       "            <td>8</td>\n",
       "            <td>6500.0</td>\n",
       "            <td>101</td>\n",
       "            <td>4</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>204</td>\n",
       "            <td>Hermann</td>\n",
       "            <td>Baer</td>\n",
       "            <td>hermann.baer@sqltutorial.org</td>\n",
       "            <td>515.123.8888</td>\n",
       "            <td>1994-06-07</td>\n",
       "            <td>12</td>\n",
       "            <td>10000.0</td>\n",
       "            <td>101</td>\n",
       "            <td>7</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>205</td>\n",
       "            <td>Shelley</td>\n",
       "            <td>Higgins</td>\n",
       "            <td>shelley.higgins@sqltutorial.org</td>\n",
       "            <td>515.123.8080</td>\n",
       "            <td>1994-06-07</td>\n",
       "            <td>2</td>\n",
       "            <td>12000.0</td>\n",
       "            <td>101</td>\n",
       "            <td>11</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>206</td>\n",
       "            <td>William</td>\n",
       "            <td>Gietz</td>\n",
       "            <td>william.gietz@sqltutorial.org</td>\n",
       "            <td>515.123.8181</td>\n",
       "            <td>1994-06-07</td>\n",
       "            <td>1</td>\n",
       "            <td>8300.0</td>\n",
       "            <td>205</td>\n",
       "            <td>11</td>\n",
       "        </tr>\n",
       "    </tbody>\n",
       "</table>"
      ],
      "text/plain": [
       "[(100, 'Steven', 'King', 'steven.king@sqltutorial.org', '515.123.4567', '1987-06-17', 4, 24000.0, None, 9),\n",
       " (101, 'Neena', 'Kochhar', 'neena.kochhar@sqltutorial.org', '515.123.4568', '1989-09-21', 5, 17000.0, 100, 9),\n",
       " (102, 'Lex', 'De Haan', 'lex.de haan@sqltutorial.org', '515.123.4569', '1993-01-13', 5, 17000.0, 100, 9),\n",
       " (103, 'Alexander', 'Hunold', 'alexander.hunold@sqltutorial.org', '590.423.4567', '1990-01-03', 9, 9000.0, 102, 6),\n",
       " (104, 'Bruce', 'Ernst', 'bruce.ernst@sqltutorial.org', '590.423.4568', '1991-05-21', 9, 6000.0, 103, 6),\n",
       " (105, 'David', 'Austin', 'david.austin@sqltutorial.org', '590.423.4569', '1997-06-25', 9, 4800.0, 103, 6),\n",
       " (106, 'Valli', 'Pataballa', 'valli.pataballa@sqltutorial.org', '590.423.4560', '1998-02-05', 9, 4800.0, 103, 6),\n",
       " (107, 'Diana', 'Lorentz', 'diana.lorentz@sqltutorial.org', '590.423.5567', '1999-02-07', 9, 4200.0, 103, 6),\n",
       " (108, 'Nancy', 'Greenberg', 'nancy.greenberg@sqltutorial.org', '515.124.4569', '1994-08-17', 7, 12000.0, 101, 10),\n",
       " (109, 'Daniel', 'Faviet', 'daniel.faviet@sqltutorial.org', '515.124.4169', '1994-08-16', 6, 9000.0, 108, 10),\n",
       " (110, 'John', 'Chen', 'john.chen@sqltutorial.org', '515.124.4269', '1997-09-28', 6, 8200.0, 108, 10),\n",
       " (111, 'Ismael', 'Sciarra', 'ismael.sciarra@sqltutorial.org', '515.124.4369', '1997-09-30', 6, 7700.0, 108, 10),\n",
       " (112, 'Jose Manuel', 'Urman', 'jose manuel.urman@sqltutorial.org', '515.124.4469', '1998-03-07', 6, 7800.0, 108, 10),\n",
       " (113, 'Luis', 'Popp', 'luis.popp@sqltutorial.org', '515.124.4567', '1999-12-07', 6, 6900.0, 108, 10),\n",
       " (114, 'Den', 'Raphaely', 'den.raphaely@sqltutorial.org', '515.127.4561', '1994-12-07', 14, 11000.0, 100, 3),\n",
       " (115, 'Alexander', 'Khoo', 'alexander.khoo@sqltutorial.org', '515.127.4562', '1995-05-18', 13, 3100.0, 114, 3),\n",
       " (116, 'Shelli', 'Baida', 'shelli.baida@sqltutorial.org', '515.127.4563', '1997-12-24', 13, 2900.0, 114, 3),\n",
       " (117, 'Sigal', 'Tobias', 'sigal.tobias@sqltutorial.org', '515.127.4564', '1997-07-24', 13, 2800.0, 114, 3),\n",
       " (118, 'Guy', 'Himuro', 'guy.himuro@sqltutorial.org', '515.127.4565', '1998-11-15', 13, 2600.0, 114, 3),\n",
       " (119, 'Karen', 'Colmenares', 'karen.colmenares@sqltutorial.org', '515.127.4566', '1999-08-10', 13, 2500.0, 114, 3),\n",
       " (120, 'Matthew', 'Weiss', 'matthew.weiss@sqltutorial.org', '650.123.1234', '1996-07-18', 19, 8000.0, 100, 5),\n",
       " (121, 'Adam', 'Fripp', 'adam.fripp@sqltutorial.org', '650.123.2234', '1997-04-10', 19, 8200.0, 100, 5),\n",
       " (122, 'Payam', 'Kaufling', 'payam.kaufling@sqltutorial.org', '650.123.3234', '1995-05-01', 19, 7900.0, 100, 5),\n",
       " (123, 'Shanta', 'Vollman', 'shanta.vollman@sqltutorial.org', '650.123.4234', '1997-10-10', 19, 6500.0, 100, 5),\n",
       " (126, 'Irene', 'Mikkilineni', 'irene.mikkilineni@sqltutorial.org', '650.124.1224', '1998-09-28', 18, 2700.0, 120, 5),\n",
       " (145, 'John', 'Russell', 'john.russell@sqltutorial.org', None, '1996-10-01', 15, 14000.0, 100, 8),\n",
       " (146, 'Karen', 'Partners', 'karen.partners@sqltutorial.org', None, '1997-01-05', 15, 13500.0, 100, 8),\n",
       " (176, 'Jonathon', 'Taylor', 'jonathon.taylor@sqltutorial.org', None, '1998-03-24', 16, 8600.0, 100, 8),\n",
       " (177, 'Jack', 'Livingston', 'jack.livingston@sqltutorial.org', None, '1998-04-23', 16, 8400.0, 100, 8),\n",
       " (178, 'Kimberely', 'Grant', 'kimberely.grant@sqltutorial.org', None, '1999-05-24', 16, 7000.0, 100, 8),\n",
       " (179, 'Charles', 'Johnson', 'charles.johnson@sqltutorial.org', None, '2000-01-04', 16, 6200.0, 100, 8),\n",
       " (192, 'Sarah', 'Bell', 'sarah.bell@sqltutorial.org', '650.501.1876', '1996-02-04', 17, 4000.0, 123, 5),\n",
       " (193, 'Britney', 'Everett', 'britney.everett@sqltutorial.org', '650.501.2876', '1997-03-03', 17, 3900.0, 123, 5),\n",
       " (200, 'Jennifer', 'Whalen', 'jennifer.whalen@sqltutorial.org', '515.123.4444', '1987-09-17', 3, 4400.0, 101, 1),\n",
       " (201, 'Michael', 'Hartstein', 'michael.hartstein@sqltutorial.org', '515.123.5555', '1996-02-17', 10, 13000.0, 100, 2),\n",
       " (202, 'Pat', 'Fay', 'pat.fay@sqltutorial.org', '603.123.6666', '1997-08-17', 11, 6000.0, 201, 2),\n",
       " (203, 'Susan', 'Mavris', 'susan.mavris@sqltutorial.org', '515.123.7777', '1994-06-07', 8, 6500.0, 101, 4),\n",
       " (204, 'Hermann', 'Baer', 'hermann.baer@sqltutorial.org', '515.123.8888', '1994-06-07', 12, 10000.0, 101, 7),\n",
       " (205, 'Shelley', 'Higgins', 'shelley.higgins@sqltutorial.org', '515.123.8080', '1994-06-07', 2, 12000.0, 101, 11),\n",
       " (206, 'William', 'Gietz', 'william.gietz@sqltutorial.org', '515.123.8181', '1994-06-07', 1, 8300.0, 205, 11)]"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "%sql SELECT * FROM employees"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "96c7vRn1_oCv"
   },
   "source": [
    "### List Tables in a Database\n",
    "\n",
    "We can also use the `SELECT` statement to display a list of all tables in the current database. Every SQLite database has an `sqlite_master` table that defines the schema for the database. The following statement uses `sqlite_master` with the `type` field set to 'table' to return the names of all tables in the current database."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 284
    },
    "executionInfo": {
     "elapsed": 37,
     "status": "ok",
     "timestamp": 1668546498219,
     "user": {
      "displayName": "Aleksandar Vakanski",
      "userId": "07675307153279708378"
     },
     "user_tz": 420
    },
    "id": "7f0samvo86cs",
    "outputId": "01c0cc65-1afe-4389-b05b-cefad48eead5"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " * sqlite://\n",
      "Done.\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<table>\n",
       "    <thead>\n",
       "        <tr>\n",
       "            <th>name</th>\n",
       "        </tr>\n",
       "    </thead>\n",
       "    <tbody>\n",
       "        <tr>\n",
       "            <td>cars</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>writer</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>regions</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>sqlite_sequence</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>countries</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>locations</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>departments</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>jobs</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>employees</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>dependents</td>\n",
       "        </tr>\n",
       "    </tbody>\n",
       "</table>"
      ],
      "text/plain": [
       "[('cars',),\n",
       " ('writer',),\n",
       " ('regions',),\n",
       " ('sqlite_sequence',),\n",
       " ('countries',),\n",
       " ('locations',),\n",
       " ('departments',),\n",
       " ('jobs',),\n",
       " ('employees',),\n",
       " ('dependents',)]"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "%sql SELECT name FROM sqlite_master WHERE type='table'"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Here is the entire `sqlite_master` table for the current database. It stores metadata about the tables and other objects (e.g., indexes and views) in an SQLite database. It contains the columns `type`, `name`, `tbl_name`, `rootpage` (the root page of the object withing the SQL database file), and `sql` (the SQL CREATE statement that was used to create the database).\n",
    "\n",
    "The `sqlite_master` table is automatically created and maintained by SQLite, and it is typically queried to inspect the schema of a database or retrieve information about its tables and other objects."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " * sqlite://\n",
      "Done.\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<table>\n",
       "    <thead>\n",
       "        <tr>\n",
       "            <th>type</th>\n",
       "            <th>name</th>\n",
       "            <th>tbl_name</th>\n",
       "            <th>rootpage</th>\n",
       "            <th>sql</th>\n",
       "        </tr>\n",
       "    </thead>\n",
       "    <tbody>\n",
       "        <tr>\n",
       "            <td>table</td>\n",
       "            <td>cars</td>\n",
       "            <td>cars</td>\n",
       "            <td>2</td>\n",
       "            <td>CREATE TABLE cars(<br>    id INTEGER NOT NULL PRIMARY KEY,<br>    name VARCHAR(50) NOT NULL,  <br>    price INTEGER)</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>table</td>\n",
       "            <td>writer</td>\n",
       "            <td>writer</td>\n",
       "            <td>3</td>\n",
       "            <td>CREATE TABLE writer(<br>    FirstName VARCHAR(50) NOT NULL,<br>    LastName VARCHAR(50) NOT NULL,  <br>    Year INTEGER NOT NULL PRIMARY KEY)</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>table</td>\n",
       "            <td>regions</td>\n",
       "            <td>regions</td>\n",
       "            <td>4</td>\n",
       "            <td>CREATE TABLE regions (<br>    region_id INTEGER PRIMARY KEY AUTOINCREMENT NOT NULL,<br>    region_name TEXT NOT NULL)</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>table</td>\n",
       "            <td>sqlite_sequence</td>\n",
       "            <td>sqlite_sequence</td>\n",
       "            <td>5</td>\n",
       "            <td>CREATE TABLE sqlite_sequence(name,seq)</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>table</td>\n",
       "            <td>countries</td>\n",
       "            <td>countries</td>\n",
       "            <td>6</td>\n",
       "            <td>CREATE TABLE countries (<br>    country_id TEXT NOT NULL,<br>    country_name TEXT NOT NULL,<br>    region_id INTEGER NOT NULL,<br>    PRIMARY KEY (country_id ASC),<br>    FOREIGN KEY (region_id) REFERENCES regions (region_id) ON DELETE CASCADE ON UPDATE CASCADE)</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>index</td>\n",
       "            <td>sqlite_autoindex_countries_1</td>\n",
       "            <td>countries</td>\n",
       "            <td>7</td>\n",
       "            <td>None</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>table</td>\n",
       "            <td>locations</td>\n",
       "            <td>locations</td>\n",
       "            <td>8</td>\n",
       "            <td>CREATE TABLE locations (<br>    location_id INTEGER PRIMARY KEY AUTOINCREMENT NOT NULL,<br>    street_address TEXT,<br>    postal_code TEXT,<br>    city text NOT NULL,<br>    state_province TEXT,<br>    country_id INTEGER NOT NULL,<br>    FOREIGN KEY (country_id) REFERENCES countries (country_id) ON DELETE CASCADE ON UPDATE CASCADE)</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>table</td>\n",
       "            <td>departments</td>\n",
       "            <td>departments</td>\n",
       "            <td>9</td>\n",
       "            <td>CREATE TABLE departments (<br>    department_id INTEGER PRIMARY KEY AUTOINCREMENT NOT NULL,<br>    department_name TEXT NOT NULL,<br>    location_id INTEGER NOT NULL,<br>    FOREIGN KEY (location_id) REFERENCES locations (location_id) ON DELETE CASCADE ON UPDATE CASCADE)</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>table</td>\n",
       "            <td>jobs</td>\n",
       "            <td>jobs</td>\n",
       "            <td>10</td>\n",
       "            <td>CREATE TABLE jobs (<br>    job_id INTEGER PRIMARY KEY AUTOINCREMENT NOT NULL,<br>    job_title TEXT NOT NULL,<br>    min_salary DOUBLE NOT NULL,<br>    max_salary DOUBLE NOT NULL)</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>table</td>\n",
       "            <td>employees</td>\n",
       "            <td>employees</td>\n",
       "            <td>11</td>\n",
       "            <td>CREATE TABLE employees (<br>    employee_id INTEGER PRIMARY KEY AUTOINCREMENT NOT NULL,<br>    first_name TEXT,<br>    last_name TEXT NOT NULL,<br>    email TEXT NOT NULL,<br>    phone_number TEXT,<br>    hire_date TEXT NOT NULL,<br>    job_id INTEGER NOT NULL,<br>    salary DOUBLE NOT NULL,<br>    manager_id INTEGER,<br>    department_id INTEGER NOT NULL,<br>    FOREIGN KEY (job_id) REFERENCES jobs (job_id) ON DELETE CASCADE ON UPDATE CASCADE,<br>    FOREIGN KEY (department_id) REFERENCES departments (department_id) ON DELETE CASCADE ON UPDATE CASCADE,<br>    FOREIGN KEY (manager_id) REFERENCES employees (employee_id) ON DELETE CASCADE ON UPDATE CASCADE)</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>table</td>\n",
       "            <td>dependents</td>\n",
       "            <td>dependents</td>\n",
       "            <td>12</td>\n",
       "            <td>CREATE TABLE dependents (<br>    dependent_id INTEGER PRIMARY KEY AUTOINCREMENT NOT NULL,<br>    first_name TEXT NOT NULL,<br>    last_name TEXT NOT NULL,<br>    relationship TEXT NOT NULL,<br>    employee_id INTEGER NOT NULL,<br>    FOREIGN KEY (employee_id) REFERENCES employees (employee_id) ON DELETE CASCADE ON UPDATE CASCADE)</td>\n",
       "        </tr>\n",
       "    </tbody>\n",
       "</table>"
      ],
      "text/plain": [
       "[('table', 'cars', 'cars', 2, 'CREATE TABLE cars(\\n    id INTEGER NOT NULL PRIMARY KEY,\\n    name VARCHAR(50) NOT NULL,  \\n    price INTEGER)'),\n",
       " ('table', 'writer', 'writer', 3, 'CREATE TABLE writer(\\n    FirstName VARCHAR(50) NOT NULL,\\n    LastName VARCHAR(50) NOT NULL,  \\n    Year INTEGER NOT NULL PRIMARY KEY)'),\n",
       " ('table', 'regions', 'regions', 4, 'CREATE TABLE regions (\\n    region_id INTEGER PRIMARY KEY AUTOINCREMENT NOT NULL,\\n    region_name TEXT NOT NULL)'),\n",
       " ('table', 'sqlite_sequence', 'sqlite_sequence', 5, 'CREATE TABLE sqlite_sequence(name,seq)'),\n",
       " ('table', 'countries', 'countries', 6, 'CREATE TABLE countries (\\n    country_id TEXT NOT NULL,\\n    country_name TEXT NOT NULL,\\n    region_id INTEGER NOT NULL,\\n    PRIMARY KEY (country_id ASC),\\n    FOREIGN KEY (region_id) REFERENCES regions (region_id) ON DELETE CASCADE ON UPDATE CASCADE)'),\n",
       " ('index', 'sqlite_autoindex_countries_1', 'countries', 7, None),\n",
       " ('table', 'locations', 'locations', 8, 'CREATE TABLE locations (\\n    location_id INTEGER PRIMARY KEY AUTOINCREMENT NOT NULL,\\n    street_address TEXT,\\n    postal_code TEXT,\\n    city text ... (22 characters truncated) ... province TEXT,\\n    country_id INTEGER NOT NULL,\\n    FOREIGN KEY (country_id) REFERENCES countries (country_id) ON DELETE CASCADE ON UPDATE CASCADE)'),\n",
       " ('table', 'departments', 'departments', 9, 'CREATE TABLE departments (\\n    department_id INTEGER PRIMARY KEY AUTOINCREMENT NOT NULL,\\n    department_name TEXT NOT NULL,\\n    location_id INTEGER NOT NULL,\\n    FOREIGN KEY (location_id) REFERENCES locations (location_id) ON DELETE CASCADE ON UPDATE CASCADE)'),\n",
       " ('table', 'jobs', 'jobs', 10, 'CREATE TABLE jobs (\\n    job_id INTEGER PRIMARY KEY AUTOINCREMENT NOT NULL,\\n    job_title TEXT NOT NULL,\\n    min_salary DOUBLE NOT NULL,\\n    max_salary DOUBLE NOT NULL)'),\n",
       " ('table', 'employees', 'employees', 11, 'CREATE TABLE employees (\\n    employee_id INTEGER PRIMARY KEY AUTOINCREMENT NOT NULL,\\n    first_name TEXT,\\n    last_name TEXT NOT NULL,\\n    email  ... (339 characters truncated) ... rtment_id) ON DELETE CASCADE ON UPDATE CASCADE,\\n    FOREIGN KEY (manager_id) REFERENCES employees (employee_id) ON DELETE CASCADE ON UPDATE CASCADE)'),\n",
       " ('table', 'dependents', 'dependents', 12, 'CREATE TABLE dependents (\\n    dependent_id INTEGER PRIMARY KEY AUTOINCREMENT NOT NULL,\\n    first_name TEXT NOT NULL,\\n    last_name TEXT NOT NULL,\\ ... (21 characters truncated) ... T NOT NULL,\\n    employee_id INTEGER NOT NULL,\\n    FOREIGN KEY (employee_id) REFERENCES employees (employee_id) ON DELETE CASCADE ON UPDATE CASCADE)')]"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "%sql SELECT * FROM sqlite_master"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "For instance, we can use the following code to retrieve the `CREATE` statement for the table `cars`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " * sqlite://\n",
      "Done.\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<table>\n",
       "    <thead>\n",
       "        <tr>\n",
       "            <th>sql</th>\n",
       "        </tr>\n",
       "    </thead>\n",
       "    <tbody>\n",
       "        <tr>\n",
       "            <td>CREATE TABLE cars(<br>    id INTEGER NOT NULL PRIMARY KEY,<br>    name VARCHAR(50) NOT NULL,  <br>    price INTEGER)</td>\n",
       "        </tr>\n",
       "    </tbody>\n",
       "</table>"
      ],
      "text/plain": [
       "[('CREATE TABLE cars(\\n    id INTEGER NOT NULL PRIMARY KEY,\\n    name VARCHAR(50) NOT NULL,  \\n    price INTEGER)',)]"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "%sql SELECT sql FROM sqlite_master WHERE type='table' AND name='cars';"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "BkKksHQ1l88_"
   },
   "source": [
    "### Perform Simple Calculations in SELECT Statements\n",
    "\n",
    "We can use standard math operators such as `+`, `*`, `/`, `%` in `SELECT` statements to perform simple mathematical calculations. The following expression creates a new column `salary * 1.05` from the `salary` column and adds 5% to the salary of every employee."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 912
    },
    "executionInfo": {
     "elapsed": 35,
     "status": "ok",
     "timestamp": 1668546498220,
     "user": {
      "displayName": "Aleksandar Vakanski",
      "userId": "07675307153279708378"
     },
     "user_tz": 420
    },
    "id": "svQGtukx86eo",
    "outputId": "2d0ffb9a-4500-468b-c4bd-172caee97ce0"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " * sqlite://\n",
      "Done.\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<table>\n",
       "    <thead>\n",
       "        <tr>\n",
       "            <th>employee_id</th>\n",
       "            <th>first_name</th>\n",
       "            <th>salary</th>\n",
       "            <th>salary*1.05</th>\n",
       "        </tr>\n",
       "    </thead>\n",
       "    <tbody>\n",
       "        <tr>\n",
       "            <td>100</td>\n",
       "            <td>Steven</td>\n",
       "            <td>24000.0</td>\n",
       "            <td>25200.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>101</td>\n",
       "            <td>Neena</td>\n",
       "            <td>17000.0</td>\n",
       "            <td>17850.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>102</td>\n",
       "            <td>Lex</td>\n",
       "            <td>17000.0</td>\n",
       "            <td>17850.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>103</td>\n",
       "            <td>Alexander</td>\n",
       "            <td>9000.0</td>\n",
       "            <td>9450.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>104</td>\n",
       "            <td>Bruce</td>\n",
       "            <td>6000.0</td>\n",
       "            <td>6300.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>105</td>\n",
       "            <td>David</td>\n",
       "            <td>4800.0</td>\n",
       "            <td>5040.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>106</td>\n",
       "            <td>Valli</td>\n",
       "            <td>4800.0</td>\n",
       "            <td>5040.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>107</td>\n",
       "            <td>Diana</td>\n",
       "            <td>4200.0</td>\n",
       "            <td>4410.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>108</td>\n",
       "            <td>Nancy</td>\n",
       "            <td>12000.0</td>\n",
       "            <td>12600.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>109</td>\n",
       "            <td>Daniel</td>\n",
       "            <td>9000.0</td>\n",
       "            <td>9450.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>110</td>\n",
       "            <td>John</td>\n",
       "            <td>8200.0</td>\n",
       "            <td>8610.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>111</td>\n",
       "            <td>Ismael</td>\n",
       "            <td>7700.0</td>\n",
       "            <td>8085.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>112</td>\n",
       "            <td>Jose Manuel</td>\n",
       "            <td>7800.0</td>\n",
       "            <td>8190.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>113</td>\n",
       "            <td>Luis</td>\n",
       "            <td>6900.0</td>\n",
       "            <td>7245.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>114</td>\n",
       "            <td>Den</td>\n",
       "            <td>11000.0</td>\n",
       "            <td>11550.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>115</td>\n",
       "            <td>Alexander</td>\n",
       "            <td>3100.0</td>\n",
       "            <td>3255.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>116</td>\n",
       "            <td>Shelli</td>\n",
       "            <td>2900.0</td>\n",
       "            <td>3045.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>117</td>\n",
       "            <td>Sigal</td>\n",
       "            <td>2800.0</td>\n",
       "            <td>2940.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>118</td>\n",
       "            <td>Guy</td>\n",
       "            <td>2600.0</td>\n",
       "            <td>2730.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>119</td>\n",
       "            <td>Karen</td>\n",
       "            <td>2500.0</td>\n",
       "            <td>2625.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>120</td>\n",
       "            <td>Matthew</td>\n",
       "            <td>8000.0</td>\n",
       "            <td>8400.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>121</td>\n",
       "            <td>Adam</td>\n",
       "            <td>8200.0</td>\n",
       "            <td>8610.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>122</td>\n",
       "            <td>Payam</td>\n",
       "            <td>7900.0</td>\n",
       "            <td>8295.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>123</td>\n",
       "            <td>Shanta</td>\n",
       "            <td>6500.0</td>\n",
       "            <td>6825.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>126</td>\n",
       "            <td>Irene</td>\n",
       "            <td>2700.0</td>\n",
       "            <td>2835.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>145</td>\n",
       "            <td>John</td>\n",
       "            <td>14000.0</td>\n",
       "            <td>14700.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>146</td>\n",
       "            <td>Karen</td>\n",
       "            <td>13500.0</td>\n",
       "            <td>14175.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>176</td>\n",
       "            <td>Jonathon</td>\n",
       "            <td>8600.0</td>\n",
       "            <td>9030.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>177</td>\n",
       "            <td>Jack</td>\n",
       "            <td>8400.0</td>\n",
       "            <td>8820.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>178</td>\n",
       "            <td>Kimberely</td>\n",
       "            <td>7000.0</td>\n",
       "            <td>7350.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>179</td>\n",
       "            <td>Charles</td>\n",
       "            <td>6200.0</td>\n",
       "            <td>6510.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>192</td>\n",
       "            <td>Sarah</td>\n",
       "            <td>4000.0</td>\n",
       "            <td>4200.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>193</td>\n",
       "            <td>Britney</td>\n",
       "            <td>3900.0</td>\n",
       "            <td>4095.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>200</td>\n",
       "            <td>Jennifer</td>\n",
       "            <td>4400.0</td>\n",
       "            <td>4620.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>201</td>\n",
       "            <td>Michael</td>\n",
       "            <td>13000.0</td>\n",
       "            <td>13650.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>202</td>\n",
       "            <td>Pat</td>\n",
       "            <td>6000.0</td>\n",
       "            <td>6300.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>203</td>\n",
       "            <td>Susan</td>\n",
       "            <td>6500.0</td>\n",
       "            <td>6825.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>204</td>\n",
       "            <td>Hermann</td>\n",
       "            <td>10000.0</td>\n",
       "            <td>10500.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>205</td>\n",
       "            <td>Shelley</td>\n",
       "            <td>12000.0</td>\n",
       "            <td>12600.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>206</td>\n",
       "            <td>William</td>\n",
       "            <td>8300.0</td>\n",
       "            <td>8715.0</td>\n",
       "        </tr>\n",
       "    </tbody>\n",
       "</table>"
      ],
      "text/plain": [
       "[(100, 'Steven', 24000.0, 25200.0),\n",
       " (101, 'Neena', 17000.0, 17850.0),\n",
       " (102, 'Lex', 17000.0, 17850.0),\n",
       " (103, 'Alexander', 9000.0, 9450.0),\n",
       " (104, 'Bruce', 6000.0, 6300.0),\n",
       " (105, 'David', 4800.0, 5040.0),\n",
       " (106, 'Valli', 4800.0, 5040.0),\n",
       " (107, 'Diana', 4200.0, 4410.0),\n",
       " (108, 'Nancy', 12000.0, 12600.0),\n",
       " (109, 'Daniel', 9000.0, 9450.0),\n",
       " (110, 'John', 8200.0, 8610.0),\n",
       " (111, 'Ismael', 7700.0, 8085.0),\n",
       " (112, 'Jose Manuel', 7800.0, 8190.0),\n",
       " (113, 'Luis', 6900.0, 7245.0),\n",
       " (114, 'Den', 11000.0, 11550.0),\n",
       " (115, 'Alexander', 3100.0, 3255.0),\n",
       " (116, 'Shelli', 2900.0, 3045.0),\n",
       " (117, 'Sigal', 2800.0, 2940.0),\n",
       " (118, 'Guy', 2600.0, 2730.0),\n",
       " (119, 'Karen', 2500.0, 2625.0),\n",
       " (120, 'Matthew', 8000.0, 8400.0),\n",
       " (121, 'Adam', 8200.0, 8610.0),\n",
       " (122, 'Payam', 7900.0, 8295.0),\n",
       " (123, 'Shanta', 6500.0, 6825.0),\n",
       " (126, 'Irene', 2700.0, 2835.0),\n",
       " (145, 'John', 14000.0, 14700.0),\n",
       " (146, 'Karen', 13500.0, 14175.0),\n",
       " (176, 'Jonathon', 8600.0, 9030.0),\n",
       " (177, 'Jack', 8400.0, 8820.0),\n",
       " (178, 'Kimberely', 7000.0, 7350.0),\n",
       " (179, 'Charles', 6200.0, 6510.0),\n",
       " (192, 'Sarah', 4000.0, 4200.0),\n",
       " (193, 'Britney', 3900.0, 4095.0),\n",
       " (200, 'Jennifer', 4400.0, 4620.0),\n",
       " (201, 'Michael', 13000.0, 13650.0),\n",
       " (202, 'Pat', 6000.0, 6300.0),\n",
       " (203, 'Susan', 6500.0, 6825.0),\n",
       " (204, 'Hermann', 10000.0, 10500.0),\n",
       " (205, 'Shelley', 12000.0, 12600.0),\n",
       " (206, 'William', 8300.0, 8715.0)]"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "%%sql \n",
    "SELECT\n",
    "    employee_id, first_name, salary, salary*1.05 \n",
    "FROM \n",
    "    employees;"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "4oTNY6Ftm2Rz"
   },
   "source": [
    "We can use `AS new_salary` to assign a different name for the newly created column."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 912
    },
    "executionInfo": {
     "elapsed": 32,
     "status": "ok",
     "timestamp": 1668546498220,
     "user": {
      "displayName": "Aleksandar Vakanski",
      "userId": "07675307153279708378"
     },
     "user_tz": 420
    },
    "id": "RQ_oeGMa86g_",
    "outputId": "19101010-1769-4c60-8f30-58a78ec36dfc"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " * sqlite://\n",
      "Done.\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<table>\n",
       "    <thead>\n",
       "        <tr>\n",
       "            <th>employee_id</th>\n",
       "            <th>first_name</th>\n",
       "            <th>salary</th>\n",
       "            <th>new_salary</th>\n",
       "        </tr>\n",
       "    </thead>\n",
       "    <tbody>\n",
       "        <tr>\n",
       "            <td>100</td>\n",
       "            <td>Steven</td>\n",
       "            <td>24000.0</td>\n",
       "            <td>25200.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>101</td>\n",
       "            <td>Neena</td>\n",
       "            <td>17000.0</td>\n",
       "            <td>17850.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>102</td>\n",
       "            <td>Lex</td>\n",
       "            <td>17000.0</td>\n",
       "            <td>17850.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>103</td>\n",
       "            <td>Alexander</td>\n",
       "            <td>9000.0</td>\n",
       "            <td>9450.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>104</td>\n",
       "            <td>Bruce</td>\n",
       "            <td>6000.0</td>\n",
       "            <td>6300.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>105</td>\n",
       "            <td>David</td>\n",
       "            <td>4800.0</td>\n",
       "            <td>5040.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>106</td>\n",
       "            <td>Valli</td>\n",
       "            <td>4800.0</td>\n",
       "            <td>5040.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>107</td>\n",
       "            <td>Diana</td>\n",
       "            <td>4200.0</td>\n",
       "            <td>4410.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>108</td>\n",
       "            <td>Nancy</td>\n",
       "            <td>12000.0</td>\n",
       "            <td>12600.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>109</td>\n",
       "            <td>Daniel</td>\n",
       "            <td>9000.0</td>\n",
       "            <td>9450.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>110</td>\n",
       "            <td>John</td>\n",
       "            <td>8200.0</td>\n",
       "            <td>8610.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>111</td>\n",
       "            <td>Ismael</td>\n",
       "            <td>7700.0</td>\n",
       "            <td>8085.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>112</td>\n",
       "            <td>Jose Manuel</td>\n",
       "            <td>7800.0</td>\n",
       "            <td>8190.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>113</td>\n",
       "            <td>Luis</td>\n",
       "            <td>6900.0</td>\n",
       "            <td>7245.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>114</td>\n",
       "            <td>Den</td>\n",
       "            <td>11000.0</td>\n",
       "            <td>11550.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>115</td>\n",
       "            <td>Alexander</td>\n",
       "            <td>3100.0</td>\n",
       "            <td>3255.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>116</td>\n",
       "            <td>Shelli</td>\n",
       "            <td>2900.0</td>\n",
       "            <td>3045.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>117</td>\n",
       "            <td>Sigal</td>\n",
       "            <td>2800.0</td>\n",
       "            <td>2940.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>118</td>\n",
       "            <td>Guy</td>\n",
       "            <td>2600.0</td>\n",
       "            <td>2730.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>119</td>\n",
       "            <td>Karen</td>\n",
       "            <td>2500.0</td>\n",
       "            <td>2625.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>120</td>\n",
       "            <td>Matthew</td>\n",
       "            <td>8000.0</td>\n",
       "            <td>8400.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>121</td>\n",
       "            <td>Adam</td>\n",
       "            <td>8200.0</td>\n",
       "            <td>8610.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>122</td>\n",
       "            <td>Payam</td>\n",
       "            <td>7900.0</td>\n",
       "            <td>8295.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>123</td>\n",
       "            <td>Shanta</td>\n",
       "            <td>6500.0</td>\n",
       "            <td>6825.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>126</td>\n",
       "            <td>Irene</td>\n",
       "            <td>2700.0</td>\n",
       "            <td>2835.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>145</td>\n",
       "            <td>John</td>\n",
       "            <td>14000.0</td>\n",
       "            <td>14700.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>146</td>\n",
       "            <td>Karen</td>\n",
       "            <td>13500.0</td>\n",
       "            <td>14175.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>176</td>\n",
       "            <td>Jonathon</td>\n",
       "            <td>8600.0</td>\n",
       "            <td>9030.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>177</td>\n",
       "            <td>Jack</td>\n",
       "            <td>8400.0</td>\n",
       "            <td>8820.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>178</td>\n",
       "            <td>Kimberely</td>\n",
       "            <td>7000.0</td>\n",
       "            <td>7350.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>179</td>\n",
       "            <td>Charles</td>\n",
       "            <td>6200.0</td>\n",
       "            <td>6510.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>192</td>\n",
       "            <td>Sarah</td>\n",
       "            <td>4000.0</td>\n",
       "            <td>4200.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>193</td>\n",
       "            <td>Britney</td>\n",
       "            <td>3900.0</td>\n",
       "            <td>4095.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>200</td>\n",
       "            <td>Jennifer</td>\n",
       "            <td>4400.0</td>\n",
       "            <td>4620.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>201</td>\n",
       "            <td>Michael</td>\n",
       "            <td>13000.0</td>\n",
       "            <td>13650.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>202</td>\n",
       "            <td>Pat</td>\n",
       "            <td>6000.0</td>\n",
       "            <td>6300.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>203</td>\n",
       "            <td>Susan</td>\n",
       "            <td>6500.0</td>\n",
       "            <td>6825.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>204</td>\n",
       "            <td>Hermann</td>\n",
       "            <td>10000.0</td>\n",
       "            <td>10500.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>205</td>\n",
       "            <td>Shelley</td>\n",
       "            <td>12000.0</td>\n",
       "            <td>12600.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>206</td>\n",
       "            <td>William</td>\n",
       "            <td>8300.0</td>\n",
       "            <td>8715.0</td>\n",
       "        </tr>\n",
       "    </tbody>\n",
       "</table>"
      ],
      "text/plain": [
       "[(100, 'Steven', 24000.0, 25200.0),\n",
       " (101, 'Neena', 17000.0, 17850.0),\n",
       " (102, 'Lex', 17000.0, 17850.0),\n",
       " (103, 'Alexander', 9000.0, 9450.0),\n",
       " (104, 'Bruce', 6000.0, 6300.0),\n",
       " (105, 'David', 4800.0, 5040.0),\n",
       " (106, 'Valli', 4800.0, 5040.0),\n",
       " (107, 'Diana', 4200.0, 4410.0),\n",
       " (108, 'Nancy', 12000.0, 12600.0),\n",
       " (109, 'Daniel', 9000.0, 9450.0),\n",
       " (110, 'John', 8200.0, 8610.0),\n",
       " (111, 'Ismael', 7700.0, 8085.0),\n",
       " (112, 'Jose Manuel', 7800.0, 8190.0),\n",
       " (113, 'Luis', 6900.0, 7245.0),\n",
       " (114, 'Den', 11000.0, 11550.0),\n",
       " (115, 'Alexander', 3100.0, 3255.0),\n",
       " (116, 'Shelli', 2900.0, 3045.0),\n",
       " (117, 'Sigal', 2800.0, 2940.0),\n",
       " (118, 'Guy', 2600.0, 2730.0),\n",
       " (119, 'Karen', 2500.0, 2625.0),\n",
       " (120, 'Matthew', 8000.0, 8400.0),\n",
       " (121, 'Adam', 8200.0, 8610.0),\n",
       " (122, 'Payam', 7900.0, 8295.0),\n",
       " (123, 'Shanta', 6500.0, 6825.0),\n",
       " (126, 'Irene', 2700.0, 2835.0),\n",
       " (145, 'John', 14000.0, 14700.0),\n",
       " (146, 'Karen', 13500.0, 14175.0),\n",
       " (176, 'Jonathon', 8600.0, 9030.0),\n",
       " (177, 'Jack', 8400.0, 8820.0),\n",
       " (178, 'Kimberely', 7000.0, 7350.0),\n",
       " (179, 'Charles', 6200.0, 6510.0),\n",
       " (192, 'Sarah', 4000.0, 4200.0),\n",
       " (193, 'Britney', 3900.0, 4095.0),\n",
       " (200, 'Jennifer', 4400.0, 4620.0),\n",
       " (201, 'Michael', 13000.0, 13650.0),\n",
       " (202, 'Pat', 6000.0, 6300.0),\n",
       " (203, 'Susan', 6500.0, 6825.0),\n",
       " (204, 'Hermann', 10000.0, 10500.0),\n",
       " (205, 'Shelley', 12000.0, 12600.0),\n",
       " (206, 'William', 8300.0, 8715.0)]"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "%%sql \n",
    "SELECT \n",
    "    employee_id, first_name, salary, salary*1.05 AS new_salary \n",
    "FROM\n",
    "    employees;"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "HN7FLZZHA3LA"
   },
   "source": [
    "## 10.6 Sorting Data with ORDER BY <a name='10.6-sorting-data-with-order-by'></a>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "q3OhOiA-BBP-"
   },
   "source": [
    "The clause `ORDER BY` can be used within a `SELECT` statement to sort the returned rows.\n",
    "\n",
    "The general syntax is: \n",
    "\n",
    "```\n",
    "SELECT \n",
    "    column1, column2, columnN \n",
    "FROM\n",
    "    table_name\n",
    "ORDER BY sort_expression [ASC | DESC];\n",
    "```\n",
    "\n",
    "The `sort_expression` specifies the sort criteria, whereas `ASC` or `DESC` indicates whether to sort the result set into ascending (default) or descending order.\n",
    "\n",
    "The following example uses the clause `ORDER BY` to sort employees by first names in alphabetical order."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 912
    },
    "executionInfo": {
     "elapsed": 30,
     "status": "ok",
     "timestamp": 1668546498221,
     "user": {
      "displayName": "Aleksandar Vakanski",
      "userId": "07675307153279708378"
     },
     "user_tz": 420
    },
    "id": "dumPr60JK_lY",
    "outputId": "cb104743-c7c3-423a-ae48-602b82cce936"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " * sqlite://\n",
      "Done.\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<table>\n",
       "    <thead>\n",
       "        <tr>\n",
       "            <th>employee_id</th>\n",
       "            <th>first_name</th>\n",
       "            <th>last_name</th>\n",
       "            <th>hire_date</th>\n",
       "            <th>salary</th>\n",
       "        </tr>\n",
       "    </thead>\n",
       "    <tbody>\n",
       "        <tr>\n",
       "            <td>121</td>\n",
       "            <td>Adam</td>\n",
       "            <td>Fripp</td>\n",
       "            <td>1997-04-10</td>\n",
       "            <td>8200.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>103</td>\n",
       "            <td>Alexander</td>\n",
       "            <td>Hunold</td>\n",
       "            <td>1990-01-03</td>\n",
       "            <td>9000.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>115</td>\n",
       "            <td>Alexander</td>\n",
       "            <td>Khoo</td>\n",
       "            <td>1995-05-18</td>\n",
       "            <td>3100.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>193</td>\n",
       "            <td>Britney</td>\n",
       "            <td>Everett</td>\n",
       "            <td>1997-03-03</td>\n",
       "            <td>3900.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>104</td>\n",
       "            <td>Bruce</td>\n",
       "            <td>Ernst</td>\n",
       "            <td>1991-05-21</td>\n",
       "            <td>6000.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>179</td>\n",
       "            <td>Charles</td>\n",
       "            <td>Johnson</td>\n",
       "            <td>2000-01-04</td>\n",
       "            <td>6200.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>109</td>\n",
       "            <td>Daniel</td>\n",
       "            <td>Faviet</td>\n",
       "            <td>1994-08-16</td>\n",
       "            <td>9000.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>105</td>\n",
       "            <td>David</td>\n",
       "            <td>Austin</td>\n",
       "            <td>1997-06-25</td>\n",
       "            <td>4800.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>114</td>\n",
       "            <td>Den</td>\n",
       "            <td>Raphaely</td>\n",
       "            <td>1994-12-07</td>\n",
       "            <td>11000.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>107</td>\n",
       "            <td>Diana</td>\n",
       "            <td>Lorentz</td>\n",
       "            <td>1999-02-07</td>\n",
       "            <td>4200.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>118</td>\n",
       "            <td>Guy</td>\n",
       "            <td>Himuro</td>\n",
       "            <td>1998-11-15</td>\n",
       "            <td>2600.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>204</td>\n",
       "            <td>Hermann</td>\n",
       "            <td>Baer</td>\n",
       "            <td>1994-06-07</td>\n",
       "            <td>10000.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>126</td>\n",
       "            <td>Irene</td>\n",
       "            <td>Mikkilineni</td>\n",
       "            <td>1998-09-28</td>\n",
       "            <td>2700.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>111</td>\n",
       "            <td>Ismael</td>\n",
       "            <td>Sciarra</td>\n",
       "            <td>1997-09-30</td>\n",
       "            <td>7700.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>177</td>\n",
       "            <td>Jack</td>\n",
       "            <td>Livingston</td>\n",
       "            <td>1998-04-23</td>\n",
       "            <td>8400.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>200</td>\n",
       "            <td>Jennifer</td>\n",
       "            <td>Whalen</td>\n",
       "            <td>1987-09-17</td>\n",
       "            <td>4400.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>110</td>\n",
       "            <td>John</td>\n",
       "            <td>Chen</td>\n",
       "            <td>1997-09-28</td>\n",
       "            <td>8200.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>145</td>\n",
       "            <td>John</td>\n",
       "            <td>Russell</td>\n",
       "            <td>1996-10-01</td>\n",
       "            <td>14000.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>176</td>\n",
       "            <td>Jonathon</td>\n",
       "            <td>Taylor</td>\n",
       "            <td>1998-03-24</td>\n",
       "            <td>8600.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>112</td>\n",
       "            <td>Jose Manuel</td>\n",
       "            <td>Urman</td>\n",
       "            <td>1998-03-07</td>\n",
       "            <td>7800.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>119</td>\n",
       "            <td>Karen</td>\n",
       "            <td>Colmenares</td>\n",
       "            <td>1999-08-10</td>\n",
       "            <td>2500.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>146</td>\n",
       "            <td>Karen</td>\n",
       "            <td>Partners</td>\n",
       "            <td>1997-01-05</td>\n",
       "            <td>13500.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>178</td>\n",
       "            <td>Kimberely</td>\n",
       "            <td>Grant</td>\n",
       "            <td>1999-05-24</td>\n",
       "            <td>7000.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>102</td>\n",
       "            <td>Lex</td>\n",
       "            <td>De Haan</td>\n",
       "            <td>1993-01-13</td>\n",
       "            <td>17000.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>113</td>\n",
       "            <td>Luis</td>\n",
       "            <td>Popp</td>\n",
       "            <td>1999-12-07</td>\n",
       "            <td>6900.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>120</td>\n",
       "            <td>Matthew</td>\n",
       "            <td>Weiss</td>\n",
       "            <td>1996-07-18</td>\n",
       "            <td>8000.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>201</td>\n",
       "            <td>Michael</td>\n",
       "            <td>Hartstein</td>\n",
       "            <td>1996-02-17</td>\n",
       "            <td>13000.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>108</td>\n",
       "            <td>Nancy</td>\n",
       "            <td>Greenberg</td>\n",
       "            <td>1994-08-17</td>\n",
       "            <td>12000.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>101</td>\n",
       "            <td>Neena</td>\n",
       "            <td>Kochhar</td>\n",
       "            <td>1989-09-21</td>\n",
       "            <td>17000.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>202</td>\n",
       "            <td>Pat</td>\n",
       "            <td>Fay</td>\n",
       "            <td>1997-08-17</td>\n",
       "            <td>6000.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>122</td>\n",
       "            <td>Payam</td>\n",
       "            <td>Kaufling</td>\n",
       "            <td>1995-05-01</td>\n",
       "            <td>7900.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>192</td>\n",
       "            <td>Sarah</td>\n",
       "            <td>Bell</td>\n",
       "            <td>1996-02-04</td>\n",
       "            <td>4000.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>123</td>\n",
       "            <td>Shanta</td>\n",
       "            <td>Vollman</td>\n",
       "            <td>1997-10-10</td>\n",
       "            <td>6500.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>205</td>\n",
       "            <td>Shelley</td>\n",
       "            <td>Higgins</td>\n",
       "            <td>1994-06-07</td>\n",
       "            <td>12000.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>116</td>\n",
       "            <td>Shelli</td>\n",
       "            <td>Baida</td>\n",
       "            <td>1997-12-24</td>\n",
       "            <td>2900.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>117</td>\n",
       "            <td>Sigal</td>\n",
       "            <td>Tobias</td>\n",
       "            <td>1997-07-24</td>\n",
       "            <td>2800.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>100</td>\n",
       "            <td>Steven</td>\n",
       "            <td>King</td>\n",
       "            <td>1987-06-17</td>\n",
       "            <td>24000.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>203</td>\n",
       "            <td>Susan</td>\n",
       "            <td>Mavris</td>\n",
       "            <td>1994-06-07</td>\n",
       "            <td>6500.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>106</td>\n",
       "            <td>Valli</td>\n",
       "            <td>Pataballa</td>\n",
       "            <td>1998-02-05</td>\n",
       "            <td>4800.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>206</td>\n",
       "            <td>William</td>\n",
       "            <td>Gietz</td>\n",
       "            <td>1994-06-07</td>\n",
       "            <td>8300.0</td>\n",
       "        </tr>\n",
       "    </tbody>\n",
       "</table>"
      ],
      "text/plain": [
       "[(121, 'Adam', 'Fripp', '1997-04-10', 8200.0),\n",
       " (103, 'Alexander', 'Hunold', '1990-01-03', 9000.0),\n",
       " (115, 'Alexander', 'Khoo', '1995-05-18', 3100.0),\n",
       " (193, 'Britney', 'Everett', '1997-03-03', 3900.0),\n",
       " (104, 'Bruce', 'Ernst', '1991-05-21', 6000.0),\n",
       " (179, 'Charles', 'Johnson', '2000-01-04', 6200.0),\n",
       " (109, 'Daniel', 'Faviet', '1994-08-16', 9000.0),\n",
       " (105, 'David', 'Austin', '1997-06-25', 4800.0),\n",
       " (114, 'Den', 'Raphaely', '1994-12-07', 11000.0),\n",
       " (107, 'Diana', 'Lorentz', '1999-02-07', 4200.0),\n",
       " (118, 'Guy', 'Himuro', '1998-11-15', 2600.0),\n",
       " (204, 'Hermann', 'Baer', '1994-06-07', 10000.0),\n",
       " (126, 'Irene', 'Mikkilineni', '1998-09-28', 2700.0),\n",
       " (111, 'Ismael', 'Sciarra', '1997-09-30', 7700.0),\n",
       " (177, 'Jack', 'Livingston', '1998-04-23', 8400.0),\n",
       " (200, 'Jennifer', 'Whalen', '1987-09-17', 4400.0),\n",
       " (110, 'John', 'Chen', '1997-09-28', 8200.0),\n",
       " (145, 'John', 'Russell', '1996-10-01', 14000.0),\n",
       " (176, 'Jonathon', 'Taylor', '1998-03-24', 8600.0),\n",
       " (112, 'Jose Manuel', 'Urman', '1998-03-07', 7800.0),\n",
       " (119, 'Karen', 'Colmenares', '1999-08-10', 2500.0),\n",
       " (146, 'Karen', 'Partners', '1997-01-05', 13500.0),\n",
       " (178, 'Kimberely', 'Grant', '1999-05-24', 7000.0),\n",
       " (102, 'Lex', 'De Haan', '1993-01-13', 17000.0),\n",
       " (113, 'Luis', 'Popp', '1999-12-07', 6900.0),\n",
       " (120, 'Matthew', 'Weiss', '1996-07-18', 8000.0),\n",
       " (201, 'Michael', 'Hartstein', '1996-02-17', 13000.0),\n",
       " (108, 'Nancy', 'Greenberg', '1994-08-17', 12000.0),\n",
       " (101, 'Neena', 'Kochhar', '1989-09-21', 17000.0),\n",
       " (202, 'Pat', 'Fay', '1997-08-17', 6000.0),\n",
       " (122, 'Payam', 'Kaufling', '1995-05-01', 7900.0),\n",
       " (192, 'Sarah', 'Bell', '1996-02-04', 4000.0),\n",
       " (123, 'Shanta', 'Vollman', '1997-10-10', 6500.0),\n",
       " (205, 'Shelley', 'Higgins', '1994-06-07', 12000.0),\n",
       " (116, 'Shelli', 'Baida', '1997-12-24', 2900.0),\n",
       " (117, 'Sigal', 'Tobias', '1997-07-24', 2800.0),\n",
       " (100, 'Steven', 'King', '1987-06-17', 24000.0),\n",
       " (203, 'Susan', 'Mavris', '1994-06-07', 6500.0),\n",
       " (106, 'Valli', 'Pataballa', '1998-02-05', 4800.0),\n",
       " (206, 'William', 'Gietz', '1994-06-07', 8300.0)]"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "%%sql \n",
    "SELECT \n",
    "    employee_id, first_name, last_name, hire_date, salary \n",
    "FROM \n",
    "    employees \n",
    "ORDER BY first_name;"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "qfpTwQ-QDgiI"
   },
   "source": [
    "The `ORDER BY` clause also allows using multiple expressions for sorting, separated by commas. In the  following example `ORDER BY` is used to sort the employees by their first name in ascending order, and the employees who have the same first name are further sorted by their last name in descending order. E.g., check the sorting for the two employees with the name Alexander. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 912
    },
    "executionInfo": {
     "elapsed": 315,
     "status": "ok",
     "timestamp": 1668546498511,
     "user": {
      "displayName": "Aleksandar Vakanski",
      "userId": "07675307153279708378"
     },
     "user_tz": 420
    },
    "id": "5sYoF7im86i5",
    "outputId": "0fa50803-1c34-4562-f215-e4538520f06b"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " * sqlite://\n",
      "Done.\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<table>\n",
       "    <thead>\n",
       "        <tr>\n",
       "            <th>employee_id</th>\n",
       "            <th>first_name</th>\n",
       "            <th>last_name</th>\n",
       "            <th>hire_date</th>\n",
       "            <th>salary</th>\n",
       "        </tr>\n",
       "    </thead>\n",
       "    <tbody>\n",
       "        <tr>\n",
       "            <td>121</td>\n",
       "            <td>Adam</td>\n",
       "            <td>Fripp</td>\n",
       "            <td>1997-04-10</td>\n",
       "            <td>8200.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>115</td>\n",
       "            <td>Alexander</td>\n",
       "            <td>Khoo</td>\n",
       "            <td>1995-05-18</td>\n",
       "            <td>3100.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>103</td>\n",
       "            <td>Alexander</td>\n",
       "            <td>Hunold</td>\n",
       "            <td>1990-01-03</td>\n",
       "            <td>9000.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>193</td>\n",
       "            <td>Britney</td>\n",
       "            <td>Everett</td>\n",
       "            <td>1997-03-03</td>\n",
       "            <td>3900.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>104</td>\n",
       "            <td>Bruce</td>\n",
       "            <td>Ernst</td>\n",
       "            <td>1991-05-21</td>\n",
       "            <td>6000.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>179</td>\n",
       "            <td>Charles</td>\n",
       "            <td>Johnson</td>\n",
       "            <td>2000-01-04</td>\n",
       "            <td>6200.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>109</td>\n",
       "            <td>Daniel</td>\n",
       "            <td>Faviet</td>\n",
       "            <td>1994-08-16</td>\n",
       "            <td>9000.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>105</td>\n",
       "            <td>David</td>\n",
       "            <td>Austin</td>\n",
       "            <td>1997-06-25</td>\n",
       "            <td>4800.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>114</td>\n",
       "            <td>Den</td>\n",
       "            <td>Raphaely</td>\n",
       "            <td>1994-12-07</td>\n",
       "            <td>11000.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>107</td>\n",
       "            <td>Diana</td>\n",
       "            <td>Lorentz</td>\n",
       "            <td>1999-02-07</td>\n",
       "            <td>4200.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>118</td>\n",
       "            <td>Guy</td>\n",
       "            <td>Himuro</td>\n",
       "            <td>1998-11-15</td>\n",
       "            <td>2600.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>204</td>\n",
       "            <td>Hermann</td>\n",
       "            <td>Baer</td>\n",
       "            <td>1994-06-07</td>\n",
       "            <td>10000.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>126</td>\n",
       "            <td>Irene</td>\n",
       "            <td>Mikkilineni</td>\n",
       "            <td>1998-09-28</td>\n",
       "            <td>2700.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>111</td>\n",
       "            <td>Ismael</td>\n",
       "            <td>Sciarra</td>\n",
       "            <td>1997-09-30</td>\n",
       "            <td>7700.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>177</td>\n",
       "            <td>Jack</td>\n",
       "            <td>Livingston</td>\n",
       "            <td>1998-04-23</td>\n",
       "            <td>8400.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>200</td>\n",
       "            <td>Jennifer</td>\n",
       "            <td>Whalen</td>\n",
       "            <td>1987-09-17</td>\n",
       "            <td>4400.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>145</td>\n",
       "            <td>John</td>\n",
       "            <td>Russell</td>\n",
       "            <td>1996-10-01</td>\n",
       "            <td>14000.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>110</td>\n",
       "            <td>John</td>\n",
       "            <td>Chen</td>\n",
       "            <td>1997-09-28</td>\n",
       "            <td>8200.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>176</td>\n",
       "            <td>Jonathon</td>\n",
       "            <td>Taylor</td>\n",
       "            <td>1998-03-24</td>\n",
       "            <td>8600.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>112</td>\n",
       "            <td>Jose Manuel</td>\n",
       "            <td>Urman</td>\n",
       "            <td>1998-03-07</td>\n",
       "            <td>7800.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>146</td>\n",
       "            <td>Karen</td>\n",
       "            <td>Partners</td>\n",
       "            <td>1997-01-05</td>\n",
       "            <td>13500.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>119</td>\n",
       "            <td>Karen</td>\n",
       "            <td>Colmenares</td>\n",
       "            <td>1999-08-10</td>\n",
       "            <td>2500.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>178</td>\n",
       "            <td>Kimberely</td>\n",
       "            <td>Grant</td>\n",
       "            <td>1999-05-24</td>\n",
       "            <td>7000.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>102</td>\n",
       "            <td>Lex</td>\n",
       "            <td>De Haan</td>\n",
       "            <td>1993-01-13</td>\n",
       "            <td>17000.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>113</td>\n",
       "            <td>Luis</td>\n",
       "            <td>Popp</td>\n",
       "            <td>1999-12-07</td>\n",
       "            <td>6900.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>120</td>\n",
       "            <td>Matthew</td>\n",
       "            <td>Weiss</td>\n",
       "            <td>1996-07-18</td>\n",
       "            <td>8000.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>201</td>\n",
       "            <td>Michael</td>\n",
       "            <td>Hartstein</td>\n",
       "            <td>1996-02-17</td>\n",
       "            <td>13000.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>108</td>\n",
       "            <td>Nancy</td>\n",
       "            <td>Greenberg</td>\n",
       "            <td>1994-08-17</td>\n",
       "            <td>12000.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>101</td>\n",
       "            <td>Neena</td>\n",
       "            <td>Kochhar</td>\n",
       "            <td>1989-09-21</td>\n",
       "            <td>17000.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>202</td>\n",
       "            <td>Pat</td>\n",
       "            <td>Fay</td>\n",
       "            <td>1997-08-17</td>\n",
       "            <td>6000.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>122</td>\n",
       "            <td>Payam</td>\n",
       "            <td>Kaufling</td>\n",
       "            <td>1995-05-01</td>\n",
       "            <td>7900.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>192</td>\n",
       "            <td>Sarah</td>\n",
       "            <td>Bell</td>\n",
       "            <td>1996-02-04</td>\n",
       "            <td>4000.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>123</td>\n",
       "            <td>Shanta</td>\n",
       "            <td>Vollman</td>\n",
       "            <td>1997-10-10</td>\n",
       "            <td>6500.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>205</td>\n",
       "            <td>Shelley</td>\n",
       "            <td>Higgins</td>\n",
       "            <td>1994-06-07</td>\n",
       "            <td>12000.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>116</td>\n",
       "            <td>Shelli</td>\n",
       "            <td>Baida</td>\n",
       "            <td>1997-12-24</td>\n",
       "            <td>2900.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>117</td>\n",
       "            <td>Sigal</td>\n",
       "            <td>Tobias</td>\n",
       "            <td>1997-07-24</td>\n",
       "            <td>2800.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>100</td>\n",
       "            <td>Steven</td>\n",
       "            <td>King</td>\n",
       "            <td>1987-06-17</td>\n",
       "            <td>24000.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>203</td>\n",
       "            <td>Susan</td>\n",
       "            <td>Mavris</td>\n",
       "            <td>1994-06-07</td>\n",
       "            <td>6500.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>106</td>\n",
       "            <td>Valli</td>\n",
       "            <td>Pataballa</td>\n",
       "            <td>1998-02-05</td>\n",
       "            <td>4800.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>206</td>\n",
       "            <td>William</td>\n",
       "            <td>Gietz</td>\n",
       "            <td>1994-06-07</td>\n",
       "            <td>8300.0</td>\n",
       "        </tr>\n",
       "    </tbody>\n",
       "</table>"
      ],
      "text/plain": [
       "[(121, 'Adam', 'Fripp', '1997-04-10', 8200.0),\n",
       " (115, 'Alexander', 'Khoo', '1995-05-18', 3100.0),\n",
       " (103, 'Alexander', 'Hunold', '1990-01-03', 9000.0),\n",
       " (193, 'Britney', 'Everett', '1997-03-03', 3900.0),\n",
       " (104, 'Bruce', 'Ernst', '1991-05-21', 6000.0),\n",
       " (179, 'Charles', 'Johnson', '2000-01-04', 6200.0),\n",
       " (109, 'Daniel', 'Faviet', '1994-08-16', 9000.0),\n",
       " (105, 'David', 'Austin', '1997-06-25', 4800.0),\n",
       " (114, 'Den', 'Raphaely', '1994-12-07', 11000.0),\n",
       " (107, 'Diana', 'Lorentz', '1999-02-07', 4200.0),\n",
       " (118, 'Guy', 'Himuro', '1998-11-15', 2600.0),\n",
       " (204, 'Hermann', 'Baer', '1994-06-07', 10000.0),\n",
       " (126, 'Irene', 'Mikkilineni', '1998-09-28', 2700.0),\n",
       " (111, 'Ismael', 'Sciarra', '1997-09-30', 7700.0),\n",
       " (177, 'Jack', 'Livingston', '1998-04-23', 8400.0),\n",
       " (200, 'Jennifer', 'Whalen', '1987-09-17', 4400.0),\n",
       " (145, 'John', 'Russell', '1996-10-01', 14000.0),\n",
       " (110, 'John', 'Chen', '1997-09-28', 8200.0),\n",
       " (176, 'Jonathon', 'Taylor', '1998-03-24', 8600.0),\n",
       " (112, 'Jose Manuel', 'Urman', '1998-03-07', 7800.0),\n",
       " (146, 'Karen', 'Partners', '1997-01-05', 13500.0),\n",
       " (119, 'Karen', 'Colmenares', '1999-08-10', 2500.0),\n",
       " (178, 'Kimberely', 'Grant', '1999-05-24', 7000.0),\n",
       " (102, 'Lex', 'De Haan', '1993-01-13', 17000.0),\n",
       " (113, 'Luis', 'Popp', '1999-12-07', 6900.0),\n",
       " (120, 'Matthew', 'Weiss', '1996-07-18', 8000.0),\n",
       " (201, 'Michael', 'Hartstein', '1996-02-17', 13000.0),\n",
       " (108, 'Nancy', 'Greenberg', '1994-08-17', 12000.0),\n",
       " (101, 'Neena', 'Kochhar', '1989-09-21', 17000.0),\n",
       " (202, 'Pat', 'Fay', '1997-08-17', 6000.0),\n",
       " (122, 'Payam', 'Kaufling', '1995-05-01', 7900.0),\n",
       " (192, 'Sarah', 'Bell', '1996-02-04', 4000.0),\n",
       " (123, 'Shanta', 'Vollman', '1997-10-10', 6500.0),\n",
       " (205, 'Shelley', 'Higgins', '1994-06-07', 12000.0),\n",
       " (116, 'Shelli', 'Baida', '1997-12-24', 2900.0),\n",
       " (117, 'Sigal', 'Tobias', '1997-07-24', 2800.0),\n",
       " (100, 'Steven', 'King', '1987-06-17', 24000.0),\n",
       " (203, 'Susan', 'Mavris', '1994-06-07', 6500.0),\n",
       " (106, 'Valli', 'Pataballa', '1998-02-05', 4800.0),\n",
       " (206, 'William', 'Gietz', '1994-06-07', 8300.0)]"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "%%sql \n",
    "SELECT \n",
    "    employee_id, first_name, last_name, hire_date, salary \n",
    "FROM \n",
    "    employees \n",
    "ORDER BY first_name, last_name DESC;"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "i0tX2jFdEumx"
   },
   "source": [
    "Similarly, we can use `ORDER BY` to sort columns with numerical data, or to sort by date as in the following cell. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 912
    },
    "executionInfo": {
     "elapsed": 42,
     "status": "ok",
     "timestamp": 1668546498512,
     "user": {
      "displayName": "Aleksandar Vakanski",
      "userId": "07675307153279708378"
     },
     "user_tz": 420
    },
    "id": "0geN3ekW2wAZ",
    "outputId": "08323f24-a25b-491a-952d-b604a756a99f"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " * sqlite://\n",
      "Done.\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<table>\n",
       "    <thead>\n",
       "        <tr>\n",
       "            <th>employee_id</th>\n",
       "            <th>first_name</th>\n",
       "            <th>last_name</th>\n",
       "            <th>hire_date</th>\n",
       "            <th>salary</th>\n",
       "        </tr>\n",
       "    </thead>\n",
       "    <tbody>\n",
       "        <tr>\n",
       "            <td>100</td>\n",
       "            <td>Steven</td>\n",
       "            <td>King</td>\n",
       "            <td>1987-06-17</td>\n",
       "            <td>24000.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>200</td>\n",
       "            <td>Jennifer</td>\n",
       "            <td>Whalen</td>\n",
       "            <td>1987-09-17</td>\n",
       "            <td>4400.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>101</td>\n",
       "            <td>Neena</td>\n",
       "            <td>Kochhar</td>\n",
       "            <td>1989-09-21</td>\n",
       "            <td>17000.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>103</td>\n",
       "            <td>Alexander</td>\n",
       "            <td>Hunold</td>\n",
       "            <td>1990-01-03</td>\n",
       "            <td>9000.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>104</td>\n",
       "            <td>Bruce</td>\n",
       "            <td>Ernst</td>\n",
       "            <td>1991-05-21</td>\n",
       "            <td>6000.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>102</td>\n",
       "            <td>Lex</td>\n",
       "            <td>De Haan</td>\n",
       "            <td>1993-01-13</td>\n",
       "            <td>17000.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>203</td>\n",
       "            <td>Susan</td>\n",
       "            <td>Mavris</td>\n",
       "            <td>1994-06-07</td>\n",
       "            <td>6500.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>204</td>\n",
       "            <td>Hermann</td>\n",
       "            <td>Baer</td>\n",
       "            <td>1994-06-07</td>\n",
       "            <td>10000.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>205</td>\n",
       "            <td>Shelley</td>\n",
       "            <td>Higgins</td>\n",
       "            <td>1994-06-07</td>\n",
       "            <td>12000.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>206</td>\n",
       "            <td>William</td>\n",
       "            <td>Gietz</td>\n",
       "            <td>1994-06-07</td>\n",
       "            <td>8300.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>109</td>\n",
       "            <td>Daniel</td>\n",
       "            <td>Faviet</td>\n",
       "            <td>1994-08-16</td>\n",
       "            <td>9000.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>108</td>\n",
       "            <td>Nancy</td>\n",
       "            <td>Greenberg</td>\n",
       "            <td>1994-08-17</td>\n",
       "            <td>12000.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>114</td>\n",
       "            <td>Den</td>\n",
       "            <td>Raphaely</td>\n",
       "            <td>1994-12-07</td>\n",
       "            <td>11000.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>122</td>\n",
       "            <td>Payam</td>\n",
       "            <td>Kaufling</td>\n",
       "            <td>1995-05-01</td>\n",
       "            <td>7900.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>115</td>\n",
       "            <td>Alexander</td>\n",
       "            <td>Khoo</td>\n",
       "            <td>1995-05-18</td>\n",
       "            <td>3100.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>192</td>\n",
       "            <td>Sarah</td>\n",
       "            <td>Bell</td>\n",
       "            <td>1996-02-04</td>\n",
       "            <td>4000.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>201</td>\n",
       "            <td>Michael</td>\n",
       "            <td>Hartstein</td>\n",
       "            <td>1996-02-17</td>\n",
       "            <td>13000.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>120</td>\n",
       "            <td>Matthew</td>\n",
       "            <td>Weiss</td>\n",
       "            <td>1996-07-18</td>\n",
       "            <td>8000.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>145</td>\n",
       "            <td>John</td>\n",
       "            <td>Russell</td>\n",
       "            <td>1996-10-01</td>\n",
       "            <td>14000.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>146</td>\n",
       "            <td>Karen</td>\n",
       "            <td>Partners</td>\n",
       "            <td>1997-01-05</td>\n",
       "            <td>13500.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>193</td>\n",
       "            <td>Britney</td>\n",
       "            <td>Everett</td>\n",
       "            <td>1997-03-03</td>\n",
       "            <td>3900.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>121</td>\n",
       "            <td>Adam</td>\n",
       "            <td>Fripp</td>\n",
       "            <td>1997-04-10</td>\n",
       "            <td>8200.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>105</td>\n",
       "            <td>David</td>\n",
       "            <td>Austin</td>\n",
       "            <td>1997-06-25</td>\n",
       "            <td>4800.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>117</td>\n",
       "            <td>Sigal</td>\n",
       "            <td>Tobias</td>\n",
       "            <td>1997-07-24</td>\n",
       "            <td>2800.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>202</td>\n",
       "            <td>Pat</td>\n",
       "            <td>Fay</td>\n",
       "            <td>1997-08-17</td>\n",
       "            <td>6000.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>110</td>\n",
       "            <td>John</td>\n",
       "            <td>Chen</td>\n",
       "            <td>1997-09-28</td>\n",
       "            <td>8200.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>111</td>\n",
       "            <td>Ismael</td>\n",
       "            <td>Sciarra</td>\n",
       "            <td>1997-09-30</td>\n",
       "            <td>7700.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>123</td>\n",
       "            <td>Shanta</td>\n",
       "            <td>Vollman</td>\n",
       "            <td>1997-10-10</td>\n",
       "            <td>6500.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>116</td>\n",
       "            <td>Shelli</td>\n",
       "            <td>Baida</td>\n",
       "            <td>1997-12-24</td>\n",
       "            <td>2900.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>106</td>\n",
       "            <td>Valli</td>\n",
       "            <td>Pataballa</td>\n",
       "            <td>1998-02-05</td>\n",
       "            <td>4800.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>112</td>\n",
       "            <td>Jose Manuel</td>\n",
       "            <td>Urman</td>\n",
       "            <td>1998-03-07</td>\n",
       "            <td>7800.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>176</td>\n",
       "            <td>Jonathon</td>\n",
       "            <td>Taylor</td>\n",
       "            <td>1998-03-24</td>\n",
       "            <td>8600.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>177</td>\n",
       "            <td>Jack</td>\n",
       "            <td>Livingston</td>\n",
       "            <td>1998-04-23</td>\n",
       "            <td>8400.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>126</td>\n",
       "            <td>Irene</td>\n",
       "            <td>Mikkilineni</td>\n",
       "            <td>1998-09-28</td>\n",
       "            <td>2700.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>118</td>\n",
       "            <td>Guy</td>\n",
       "            <td>Himuro</td>\n",
       "            <td>1998-11-15</td>\n",
       "            <td>2600.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>107</td>\n",
       "            <td>Diana</td>\n",
       "            <td>Lorentz</td>\n",
       "            <td>1999-02-07</td>\n",
       "            <td>4200.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>178</td>\n",
       "            <td>Kimberely</td>\n",
       "            <td>Grant</td>\n",
       "            <td>1999-05-24</td>\n",
       "            <td>7000.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>119</td>\n",
       "            <td>Karen</td>\n",
       "            <td>Colmenares</td>\n",
       "            <td>1999-08-10</td>\n",
       "            <td>2500.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>113</td>\n",
       "            <td>Luis</td>\n",
       "            <td>Popp</td>\n",
       "            <td>1999-12-07</td>\n",
       "            <td>6900.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>179</td>\n",
       "            <td>Charles</td>\n",
       "            <td>Johnson</td>\n",
       "            <td>2000-01-04</td>\n",
       "            <td>6200.0</td>\n",
       "        </tr>\n",
       "    </tbody>\n",
       "</table>"
      ],
      "text/plain": [
       "[(100, 'Steven', 'King', '1987-06-17', 24000.0),\n",
       " (200, 'Jennifer', 'Whalen', '1987-09-17', 4400.0),\n",
       " (101, 'Neena', 'Kochhar', '1989-09-21', 17000.0),\n",
       " (103, 'Alexander', 'Hunold', '1990-01-03', 9000.0),\n",
       " (104, 'Bruce', 'Ernst', '1991-05-21', 6000.0),\n",
       " (102, 'Lex', 'De Haan', '1993-01-13', 17000.0),\n",
       " (203, 'Susan', 'Mavris', '1994-06-07', 6500.0),\n",
       " (204, 'Hermann', 'Baer', '1994-06-07', 10000.0),\n",
       " (205, 'Shelley', 'Higgins', '1994-06-07', 12000.0),\n",
       " (206, 'William', 'Gietz', '1994-06-07', 8300.0),\n",
       " (109, 'Daniel', 'Faviet', '1994-08-16', 9000.0),\n",
       " (108, 'Nancy', 'Greenberg', '1994-08-17', 12000.0),\n",
       " (114, 'Den', 'Raphaely', '1994-12-07', 11000.0),\n",
       " (122, 'Payam', 'Kaufling', '1995-05-01', 7900.0),\n",
       " (115, 'Alexander', 'Khoo', '1995-05-18', 3100.0),\n",
       " (192, 'Sarah', 'Bell', '1996-02-04', 4000.0),\n",
       " (201, 'Michael', 'Hartstein', '1996-02-17', 13000.0),\n",
       " (120, 'Matthew', 'Weiss', '1996-07-18', 8000.0),\n",
       " (145, 'John', 'Russell', '1996-10-01', 14000.0),\n",
       " (146, 'Karen', 'Partners', '1997-01-05', 13500.0),\n",
       " (193, 'Britney', 'Everett', '1997-03-03', 3900.0),\n",
       " (121, 'Adam', 'Fripp', '1997-04-10', 8200.0),\n",
       " (105, 'David', 'Austin', '1997-06-25', 4800.0),\n",
       " (117, 'Sigal', 'Tobias', '1997-07-24', 2800.0),\n",
       " (202, 'Pat', 'Fay', '1997-08-17', 6000.0),\n",
       " (110, 'John', 'Chen', '1997-09-28', 8200.0),\n",
       " (111, 'Ismael', 'Sciarra', '1997-09-30', 7700.0),\n",
       " (123, 'Shanta', 'Vollman', '1997-10-10', 6500.0),\n",
       " (116, 'Shelli', 'Baida', '1997-12-24', 2900.0),\n",
       " (106, 'Valli', 'Pataballa', '1998-02-05', 4800.0),\n",
       " (112, 'Jose Manuel', 'Urman', '1998-03-07', 7800.0),\n",
       " (176, 'Jonathon', 'Taylor', '1998-03-24', 8600.0),\n",
       " (177, 'Jack', 'Livingston', '1998-04-23', 8400.0),\n",
       " (126, 'Irene', 'Mikkilineni', '1998-09-28', 2700.0),\n",
       " (118, 'Guy', 'Himuro', '1998-11-15', 2600.0),\n",
       " (107, 'Diana', 'Lorentz', '1999-02-07', 4200.0),\n",
       " (178, 'Kimberely', 'Grant', '1999-05-24', 7000.0),\n",
       " (119, 'Karen', 'Colmenares', '1999-08-10', 2500.0),\n",
       " (113, 'Luis', 'Popp', '1999-12-07', 6900.0),\n",
       " (179, 'Charles', 'Johnson', '2000-01-04', 6200.0)]"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "%%sql\n",
    "SELECT \n",
    "    employee_id, first_name, last_name, hire_date, salary \n",
    "FROM \n",
    "    employees \n",
    "ORDER BY hire_date;"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "1tftp-AjGK9Q"
   },
   "source": [
    "## 10.7 Filtering Data <a name='10.7-filtering-data'></a>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "3-vca0nPGqVB"
   },
   "source": [
    "### LIMIT\n",
    "\n",
    "`LIMIT` is used to constrain the number of rows returned by a query, similar to the functions `head()` and `tail()` in Pandas.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 179
    },
    "executionInfo": {
     "elapsed": 41,
     "status": "ok",
     "timestamp": 1668546498513,
     "user": {
      "displayName": "Aleksandar Vakanski",
      "userId": "07675307153279708378"
     },
     "user_tz": 420
    },
    "id": "dsNuYSusK_jX",
    "outputId": "788a2b42-38cf-4b4f-a7a0-bb18a627a5fc"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " * sqlite://\n",
      "Done.\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<table>\n",
       "    <thead>\n",
       "        <tr>\n",
       "            <th>employee_id</th>\n",
       "            <th>first_name</th>\n",
       "            <th>last_name</th>\n",
       "            <th>hire_date</th>\n",
       "            <th>salary</th>\n",
       "        </tr>\n",
       "    </thead>\n",
       "    <tbody>\n",
       "        <tr>\n",
       "            <td>121</td>\n",
       "            <td>Adam</td>\n",
       "            <td>Fripp</td>\n",
       "            <td>1997-04-10</td>\n",
       "            <td>8200.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>103</td>\n",
       "            <td>Alexander</td>\n",
       "            <td>Hunold</td>\n",
       "            <td>1990-01-03</td>\n",
       "            <td>9000.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>115</td>\n",
       "            <td>Alexander</td>\n",
       "            <td>Khoo</td>\n",
       "            <td>1995-05-18</td>\n",
       "            <td>3100.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>193</td>\n",
       "            <td>Britney</td>\n",
       "            <td>Everett</td>\n",
       "            <td>1997-03-03</td>\n",
       "            <td>3900.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>104</td>\n",
       "            <td>Bruce</td>\n",
       "            <td>Ernst</td>\n",
       "            <td>1991-05-21</td>\n",
       "            <td>6000.0</td>\n",
       "        </tr>\n",
       "    </tbody>\n",
       "</table>"
      ],
      "text/plain": [
       "[(121, 'Adam', 'Fripp', '1997-04-10', 8200.0),\n",
       " (103, 'Alexander', 'Hunold', '1990-01-03', 9000.0),\n",
       " (115, 'Alexander', 'Khoo', '1995-05-18', 3100.0),\n",
       " (193, 'Britney', 'Everett', '1997-03-03', 3900.0),\n",
       " (104, 'Bruce', 'Ernst', '1991-05-21', 6000.0)]"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "%%sql\n",
    "SELECT \n",
    "    employee_id, first_name, last_name, hire_date, salary \n",
    "FROM \n",
    "    employees \n",
    "ORDER BY first_name \n",
    "LIMIT 5;"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "9Y97Q-sPIrQm"
   },
   "source": [
    "It is also possible to include an `OFFSET` clause, which will skip rows before retrieving the data. E.g., in the next cell, the first 3 rows are skipped, and rows 4-8 are returned. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 179
    },
    "executionInfo": {
     "elapsed": 37,
     "status": "ok",
     "timestamp": 1668546498513,
     "user": {
      "displayName": "Aleksandar Vakanski",
      "userId": "07675307153279708378"
     },
     "user_tz": 420
    },
    "id": "4Gp6pN85GLEt",
    "outputId": "83ca8090-2c02-4f12-fe64-f17ed36021b8"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " * sqlite://\n",
      "Done.\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<table>\n",
       "    <thead>\n",
       "        <tr>\n",
       "            <th>employee_id</th>\n",
       "            <th>first_name</th>\n",
       "            <th>last_name</th>\n",
       "            <th>hire_date</th>\n",
       "            <th>salary</th>\n",
       "        </tr>\n",
       "    </thead>\n",
       "    <tbody>\n",
       "        <tr>\n",
       "            <td>193</td>\n",
       "            <td>Britney</td>\n",
       "            <td>Everett</td>\n",
       "            <td>1997-03-03</td>\n",
       "            <td>3900.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>104</td>\n",
       "            <td>Bruce</td>\n",
       "            <td>Ernst</td>\n",
       "            <td>1991-05-21</td>\n",
       "            <td>6000.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>179</td>\n",
       "            <td>Charles</td>\n",
       "            <td>Johnson</td>\n",
       "            <td>2000-01-04</td>\n",
       "            <td>6200.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>109</td>\n",
       "            <td>Daniel</td>\n",
       "            <td>Faviet</td>\n",
       "            <td>1994-08-16</td>\n",
       "            <td>9000.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>105</td>\n",
       "            <td>David</td>\n",
       "            <td>Austin</td>\n",
       "            <td>1997-06-25</td>\n",
       "            <td>4800.0</td>\n",
       "        </tr>\n",
       "    </tbody>\n",
       "</table>"
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      "text/plain": [
       "[(193, 'Britney', 'Everett', '1997-03-03', 3900.0),\n",
       " (104, 'Bruce', 'Ernst', '1991-05-21', 6000.0),\n",
       " (179, 'Charles', 'Johnson', '2000-01-04', 6200.0),\n",
       " (109, 'Daniel', 'Faviet', '1994-08-16', 9000.0),\n",
       " (105, 'David', 'Austin', '1997-06-25', 4800.0)]"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "%%sql \n",
    "SELECT\n",
    "    employee_id, first_name, last_name, hire_date, salary \n",
    "FROM \n",
    "    employees \n",
    "ORDER BY first_name \n",
    "LIMIT 5 \n",
    "OFFSET 3;"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "scbrAeEPJZLx"
   },
   "source": [
    "### DISTINCT \n",
    "\n",
    "The `DISTINCT` clause allows to remove duplicate rows from the result set.\n",
    "\n",
    "E.g., the next cell shows the first 15 rows of the salary columns, where some rows have the same value. In the cell afterward, `DISTINCT` is used to remove the rows with the same values for salary."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 389
    },
    "executionInfo": {
     "elapsed": 33,
     "status": "ok",
     "timestamp": 1668546498513,
     "user": {
      "displayName": "Aleksandar Vakanski",
      "userId": "07675307153279708378"
     },
     "user_tz": 420
    },
    "id": "smgAPe0SGLGi",
    "outputId": "8610af08-bdfe-4861-a2c1-709bd47fd794"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " * sqlite://\n",
      "Done.\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<table>\n",
       "    <thead>\n",
       "        <tr>\n",
       "            <th>salary</th>\n",
       "        </tr>\n",
       "    </thead>\n",
       "    <tbody>\n",
       "        <tr>\n",
       "            <td>24000.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>17000.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>17000.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>14000.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>13500.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>13000.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>12000.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>12000.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>11000.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>10000.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>9000.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>9000.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>8600.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>8400.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>8300.0</td>\n",
       "        </tr>\n",
       "    </tbody>\n",
       "</table>"
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      "text/plain": [
       "[(24000.0,),\n",
       " (17000.0,),\n",
       " (17000.0,),\n",
       " (14000.0,),\n",
       " (13500.0,),\n",
       " (13000.0,),\n",
       " (12000.0,),\n",
       " (12000.0,),\n",
       " (11000.0,),\n",
       " (10000.0,),\n",
       " (9000.0,),\n",
       " (9000.0,),\n",
       " (8600.0,),\n",
       " (8400.0,),\n",
       " (8300.0,)]"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "%%sql\n",
    "SELECT \n",
    "    salary \n",
    "FROM \n",
    "    employees \n",
    "ORDER BY salary DESC \n",
    "LIMIT 15;"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 389
    },
    "executionInfo": {
     "elapsed": 31,
     "status": "ok",
     "timestamp": 1668546498514,
     "user": {
      "displayName": "Aleksandar Vakanski",
      "userId": "07675307153279708378"
     },
     "user_tz": 420
    },
    "id": "Jk867nh7GLIf",
    "outputId": "9f901a8b-1c6d-4353-c7f0-c5a066344b86"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " * sqlite://\n",
      "Done.\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<table>\n",
       "    <thead>\n",
       "        <tr>\n",
       "            <th>salary</th>\n",
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       "            <td>8000.0</td>\n",
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       "            <td>7900.0</td>\n",
       "        </tr>\n",
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       "[(24000.0,),\n",
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       " (13000.0,),\n",
       " (12000.0,),\n",
       " (11000.0,),\n",
       " (10000.0,),\n",
       " (9000.0,),\n",
       " (8600.0,),\n",
       " (8400.0,),\n",
       " (8300.0,),\n",
       " (8200.0,),\n",
       " (8000.0,),\n",
       " (7900.0,)]"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "%%sql \n",
    "SELECT DISTINCT \n",
    "    salary \n",
    "FROM \n",
    "    employees \n",
    "ORDER BY salary DESC\n",
    "LIMIT 15;"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "T9JRPTQ9MGJI"
   },
   "source": [
    "### WHERE\n",
    "\n",
    "The `WHERE` clause filters data based on specified conditions. For instance, return only the employees that have a salary greater than a certain value."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 284
    },
    "executionInfo": {
     "elapsed": 28,
     "status": "ok",
     "timestamp": 1668546498514,
     "user": {
      "displayName": "Aleksandar Vakanski",
      "userId": "07675307153279708378"
     },
     "user_tz": 420
    },
    "id": "F3nnMfBxGLLY",
    "outputId": "00a3e730-cc2c-4fae-d3db-bd6e0e2a5730"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " * sqlite://\n",
      "Done.\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<table>\n",
       "    <thead>\n",
       "        <tr>\n",
       "            <th>employee_id</th>\n",
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       "            <th>last_name</th>\n",
       "            <th>salary</th>\n",
       "        </tr>\n",
       "    </thead>\n",
       "    <tbody>\n",
       "        <tr>\n",
       "            <td>100</td>\n",
       "            <td>Steven</td>\n",
       "            <td>King</td>\n",
       "            <td>24000.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>101</td>\n",
       "            <td>Neena</td>\n",
       "            <td>Kochhar</td>\n",
       "            <td>17000.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>102</td>\n",
       "            <td>Lex</td>\n",
       "            <td>De Haan</td>\n",
       "            <td>17000.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>145</td>\n",
       "            <td>John</td>\n",
       "            <td>Russell</td>\n",
       "            <td>14000.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>146</td>\n",
       "            <td>Karen</td>\n",
       "            <td>Partners</td>\n",
       "            <td>13500.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>201</td>\n",
       "            <td>Michael</td>\n",
       "            <td>Hartstein</td>\n",
       "            <td>13000.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>108</td>\n",
       "            <td>Nancy</td>\n",
       "            <td>Greenberg</td>\n",
       "            <td>12000.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>205</td>\n",
       "            <td>Shelley</td>\n",
       "            <td>Higgins</td>\n",
       "            <td>12000.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>114</td>\n",
       "            <td>Den</td>\n",
       "            <td>Raphaely</td>\n",
       "            <td>11000.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>204</td>\n",
       "            <td>Hermann</td>\n",
       "            <td>Baer</td>\n",
       "            <td>10000.0</td>\n",
       "        </tr>\n",
       "    </tbody>\n",
       "</table>"
      ],
      "text/plain": [
       "[(100, 'Steven', 'King', 24000.0),\n",
       " (101, 'Neena', 'Kochhar', 17000.0),\n",
       " (102, 'Lex', 'De Haan', 17000.0),\n",
       " (145, 'John', 'Russell', 14000.0),\n",
       " (146, 'Karen', 'Partners', 13500.0),\n",
       " (201, 'Michael', 'Hartstein', 13000.0),\n",
       " (108, 'Nancy', 'Greenberg', 12000.0),\n",
       " (205, 'Shelley', 'Higgins', 12000.0),\n",
       " (114, 'Den', 'Raphaely', 11000.0),\n",
       " (204, 'Hermann', 'Baer', 10000.0)]"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "%%sql \n",
    "SELECT DISTINCT \n",
    "    employee_id, first_name, last_name,salary \n",
    "FROM \n",
    "    employees \n",
    "WHERE salary > 9000 \n",
    "ORDER BY salary DESC;"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "ybtWARO0M9AA"
   },
   "source": [
    "Or, return the employees who work in the department 5. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 221
    },
    "executionInfo": {
     "elapsed": 26,
     "status": "ok",
     "timestamp": 1668546498515,
     "user": {
      "displayName": "Aleksandar Vakanski",
      "userId": "07675307153279708378"
     },
     "user_tz": 420
    },
    "id": "neKdj-UhM6gr",
    "outputId": "1184d94d-5aa7-4b6c-f0e9-3a16a44a5310"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " * sqlite://\n",
      "Done.\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<table>\n",
       "    <thead>\n",
       "        <tr>\n",
       "            <th>employee_id</th>\n",
       "            <th>first_name</th>\n",
       "            <th>last_name</th>\n",
       "            <th>salary</th>\n",
       "            <th>department_id</th>\n",
       "        </tr>\n",
       "    </thead>\n",
       "    <tbody>\n",
       "        <tr>\n",
       "            <td>121</td>\n",
       "            <td>Adam</td>\n",
       "            <td>Fripp</td>\n",
       "            <td>8200.0</td>\n",
       "            <td>5</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>193</td>\n",
       "            <td>Britney</td>\n",
       "            <td>Everett</td>\n",
       "            <td>3900.0</td>\n",
       "            <td>5</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>126</td>\n",
       "            <td>Irene</td>\n",
       "            <td>Mikkilineni</td>\n",
       "            <td>2700.0</td>\n",
       "            <td>5</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>120</td>\n",
       "            <td>Matthew</td>\n",
       "            <td>Weiss</td>\n",
       "            <td>8000.0</td>\n",
       "            <td>5</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>122</td>\n",
       "            <td>Payam</td>\n",
       "            <td>Kaufling</td>\n",
       "            <td>7900.0</td>\n",
       "            <td>5</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>192</td>\n",
       "            <td>Sarah</td>\n",
       "            <td>Bell</td>\n",
       "            <td>4000.0</td>\n",
       "            <td>5</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>123</td>\n",
       "            <td>Shanta</td>\n",
       "            <td>Vollman</td>\n",
       "            <td>6500.0</td>\n",
       "            <td>5</td>\n",
       "        </tr>\n",
       "    </tbody>\n",
       "</table>"
      ],
      "text/plain": [
       "[(121, 'Adam', 'Fripp', 8200.0, 5),\n",
       " (193, 'Britney', 'Everett', 3900.0, 5),\n",
       " (126, 'Irene', 'Mikkilineni', 2700.0, 5),\n",
       " (120, 'Matthew', 'Weiss', 8000.0, 5),\n",
       " (122, 'Payam', 'Kaufling', 7900.0, 5),\n",
       " (192, 'Sarah', 'Bell', 4000.0, 5),\n",
       " (123, 'Shanta', 'Vollman', 6500.0, 5)]"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "%%sql \n",
    "SELECT DISTINCT \n",
    "    employee_id, first_name, last_name, salary, department_id \n",
    "FROM \n",
    "    employees \n",
    "WHERE department_id = 5 \n",
    "ORDER BY first_name;"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "wNGiqy3_Ob3x"
   },
   "source": [
    "### Comparison Operators"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "LbcqYkoUNufB"
   },
   "source": [
    "To specify a condition, we can use the standard comparison operators, such as `>`, `<`, `>=`, `<=`, `=`, and note that `<>` can be used for 'not equal to'."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 766
    },
    "executionInfo": {
     "elapsed": 22,
     "status": "ok",
     "timestamp": 1668546498515,
     "user": {
      "displayName": "Aleksandar Vakanski",
      "userId": "07675307153279708378"
     },
     "user_tz": 420
    },
    "id": "VJ4J1gf8M6kp",
    "outputId": "12e9a251-9406-4b49-feda-c36af7680673"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " * sqlite://\n",
      "Done.\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<table>\n",
       "    <thead>\n",
       "        <tr>\n",
       "            <th>employee_id</th>\n",
       "            <th>first_name</th>\n",
       "            <th>last_name</th>\n",
       "            <th>salary</th>\n",
       "            <th>department_id</th>\n",
       "        </tr>\n",
       "    </thead>\n",
       "    <tbody>\n",
       "        <tr>\n",
       "            <td>103</td>\n",
       "            <td>Alexander</td>\n",
       "            <td>Hunold</td>\n",
       "            <td>9000.0</td>\n",
       "            <td>6</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>115</td>\n",
       "            <td>Alexander</td>\n",
       "            <td>Khoo</td>\n",
       "            <td>3100.0</td>\n",
       "            <td>3</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>104</td>\n",
       "            <td>Bruce</td>\n",
       "            <td>Ernst</td>\n",
       "            <td>6000.0</td>\n",
       "            <td>6</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>179</td>\n",
       "            <td>Charles</td>\n",
       "            <td>Johnson</td>\n",
       "            <td>6200.0</td>\n",
       "            <td>8</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>109</td>\n",
       "            <td>Daniel</td>\n",
       "            <td>Faviet</td>\n",
       "            <td>9000.0</td>\n",
       "            <td>10</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>105</td>\n",
       "            <td>David</td>\n",
       "            <td>Austin</td>\n",
       "            <td>4800.0</td>\n",
       "            <td>6</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>114</td>\n",
       "            <td>Den</td>\n",
       "            <td>Raphaely</td>\n",
       "            <td>11000.0</td>\n",
       "            <td>3</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>107</td>\n",
       "            <td>Diana</td>\n",
       "            <td>Lorentz</td>\n",
       "            <td>4200.0</td>\n",
       "            <td>6</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>118</td>\n",
       "            <td>Guy</td>\n",
       "            <td>Himuro</td>\n",
       "            <td>2600.0</td>\n",
       "            <td>3</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>204</td>\n",
       "            <td>Hermann</td>\n",
       "            <td>Baer</td>\n",
       "            <td>10000.0</td>\n",
       "            <td>7</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>111</td>\n",
       "            <td>Ismael</td>\n",
       "            <td>Sciarra</td>\n",
       "            <td>7700.0</td>\n",
       "            <td>10</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>177</td>\n",
       "            <td>Jack</td>\n",
       "            <td>Livingston</td>\n",
       "            <td>8400.0</td>\n",
       "            <td>8</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>200</td>\n",
       "            <td>Jennifer</td>\n",
       "            <td>Whalen</td>\n",
       "            <td>4400.0</td>\n",
       "            <td>1</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>110</td>\n",
       "            <td>John</td>\n",
       "            <td>Chen</td>\n",
       "            <td>8200.0</td>\n",
       "            <td>10</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>145</td>\n",
       "            <td>John</td>\n",
       "            <td>Russell</td>\n",
       "            <td>14000.0</td>\n",
       "            <td>8</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>176</td>\n",
       "            <td>Jonathon</td>\n",
       "            <td>Taylor</td>\n",
       "            <td>8600.0</td>\n",
       "            <td>8</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>112</td>\n",
       "            <td>Jose Manuel</td>\n",
       "            <td>Urman</td>\n",
       "            <td>7800.0</td>\n",
       "            <td>10</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>119</td>\n",
       "            <td>Karen</td>\n",
       "            <td>Colmenares</td>\n",
       "            <td>2500.0</td>\n",
       "            <td>3</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>146</td>\n",
       "            <td>Karen</td>\n",
       "            <td>Partners</td>\n",
       "            <td>13500.0</td>\n",
       "            <td>8</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>178</td>\n",
       "            <td>Kimberely</td>\n",
       "            <td>Grant</td>\n",
       "            <td>7000.0</td>\n",
       "            <td>8</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>102</td>\n",
       "            <td>Lex</td>\n",
       "            <td>De Haan</td>\n",
       "            <td>17000.0</td>\n",
       "            <td>9</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>113</td>\n",
       "            <td>Luis</td>\n",
       "            <td>Popp</td>\n",
       "            <td>6900.0</td>\n",
       "            <td>10</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>201</td>\n",
       "            <td>Michael</td>\n",
       "            <td>Hartstein</td>\n",
       "            <td>13000.0</td>\n",
       "            <td>2</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>108</td>\n",
       "            <td>Nancy</td>\n",
       "            <td>Greenberg</td>\n",
       "            <td>12000.0</td>\n",
       "            <td>10</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>101</td>\n",
       "            <td>Neena</td>\n",
       "            <td>Kochhar</td>\n",
       "            <td>17000.0</td>\n",
       "            <td>9</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>202</td>\n",
       "            <td>Pat</td>\n",
       "            <td>Fay</td>\n",
       "            <td>6000.0</td>\n",
       "            <td>2</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>205</td>\n",
       "            <td>Shelley</td>\n",
       "            <td>Higgins</td>\n",
       "            <td>12000.0</td>\n",
       "            <td>11</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>116</td>\n",
       "            <td>Shelli</td>\n",
       "            <td>Baida</td>\n",
       "            <td>2900.0</td>\n",
       "            <td>3</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>117</td>\n",
       "            <td>Sigal</td>\n",
       "            <td>Tobias</td>\n",
       "            <td>2800.0</td>\n",
       "            <td>3</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>100</td>\n",
       "            <td>Steven</td>\n",
       "            <td>King</td>\n",
       "            <td>24000.0</td>\n",
       "            <td>9</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>203</td>\n",
       "            <td>Susan</td>\n",
       "            <td>Mavris</td>\n",
       "            <td>6500.0</td>\n",
       "            <td>4</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>106</td>\n",
       "            <td>Valli</td>\n",
       "            <td>Pataballa</td>\n",
       "            <td>4800.0</td>\n",
       "            <td>6</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>206</td>\n",
       "            <td>William</td>\n",
       "            <td>Gietz</td>\n",
       "            <td>8300.0</td>\n",
       "            <td>11</td>\n",
       "        </tr>\n",
       "    </tbody>\n",
       "</table>"
      ],
      "text/plain": [
       "[(103, 'Alexander', 'Hunold', 9000.0, 6),\n",
       " (115, 'Alexander', 'Khoo', 3100.0, 3),\n",
       " (104, 'Bruce', 'Ernst', 6000.0, 6),\n",
       " (179, 'Charles', 'Johnson', 6200.0, 8),\n",
       " (109, 'Daniel', 'Faviet', 9000.0, 10),\n",
       " (105, 'David', 'Austin', 4800.0, 6),\n",
       " (114, 'Den', 'Raphaely', 11000.0, 3),\n",
       " (107, 'Diana', 'Lorentz', 4200.0, 6),\n",
       " (118, 'Guy', 'Himuro', 2600.0, 3),\n",
       " (204, 'Hermann', 'Baer', 10000.0, 7),\n",
       " (111, 'Ismael', 'Sciarra', 7700.0, 10),\n",
       " (177, 'Jack', 'Livingston', 8400.0, 8),\n",
       " (200, 'Jennifer', 'Whalen', 4400.0, 1),\n",
       " (110, 'John', 'Chen', 8200.0, 10),\n",
       " (145, 'John', 'Russell', 14000.0, 8),\n",
       " (176, 'Jonathon', 'Taylor', 8600.0, 8),\n",
       " (112, 'Jose Manuel', 'Urman', 7800.0, 10),\n",
       " (119, 'Karen', 'Colmenares', 2500.0, 3),\n",
       " (146, 'Karen', 'Partners', 13500.0, 8),\n",
       " (178, 'Kimberely', 'Grant', 7000.0, 8),\n",
       " (102, 'Lex', 'De Haan', 17000.0, 9),\n",
       " (113, 'Luis', 'Popp', 6900.0, 10),\n",
       " (201, 'Michael', 'Hartstein', 13000.0, 2),\n",
       " (108, 'Nancy', 'Greenberg', 12000.0, 10),\n",
       " (101, 'Neena', 'Kochhar', 17000.0, 9),\n",
       " (202, 'Pat', 'Fay', 6000.0, 2),\n",
       " (205, 'Shelley', 'Higgins', 12000.0, 11),\n",
       " (116, 'Shelli', 'Baida', 2900.0, 3),\n",
       " (117, 'Sigal', 'Tobias', 2800.0, 3),\n",
       " (100, 'Steven', 'King', 24000.0, 9),\n",
       " (203, 'Susan', 'Mavris', 6500.0, 4),\n",
       " (106, 'Valli', 'Pataballa', 4800.0, 6),\n",
       " (206, 'William', 'Gietz', 8300.0, 11)]"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "%%sql \n",
    "SELECT DISTINCT \n",
    "    employee_id, first_name, last_name, salary, department_id\n",
    "FROM \n",
    "    employees \n",
    "WHERE department_id <> 5 \n",
    "ORDER BY first_name;"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "VlSVddSKOe84"
   },
   "source": [
    "### Logical Operators\n",
    "\n",
    "We can also use logical operators to combine multiple conditions in the `WHERE` clause of an SQL statement. The following table contains the SQL logical operators.\n",
    "\n",
    "<img src=\"images/logical_operators.png\" width=\"600\">\n",
    "<em>Figure source: Reference [1].</em>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 200
    },
    "executionInfo": {
     "elapsed": 369,
     "status": "ok",
     "timestamp": 1668546498866,
     "user": {
      "displayName": "Aleksandar Vakanski",
      "userId": "07675307153279708378"
     },
     "user_tz": 420
    },
    "id": "nUBYaYsiM6ma",
    "outputId": "373af86f-4cde-4b5e-946d-148e34dbf8e1"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " * sqlite://\n",
      "Done.\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<table>\n",
       "    <thead>\n",
       "        <tr>\n",
       "            <th>first_name</th>\n",
       "            <th>last_name</th>\n",
       "            <th>salary</th>\n",
       "        </tr>\n",
       "    </thead>\n",
       "    <tbody>\n",
       "        <tr>\n",
       "            <td>Bruce</td>\n",
       "            <td>Ernst</td>\n",
       "            <td>6000.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>Pat</td>\n",
       "            <td>Fay</td>\n",
       "            <td>6000.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>Charles</td>\n",
       "            <td>Johnson</td>\n",
       "            <td>6200.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>Shanta</td>\n",
       "            <td>Vollman</td>\n",
       "            <td>6500.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>Susan</td>\n",
       "            <td>Mavris</td>\n",
       "            <td>6500.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>Luis</td>\n",
       "            <td>Popp</td>\n",
       "            <td>6900.0</td>\n",
       "        </tr>\n",
       "    </tbody>\n",
       "</table>"
      ],
      "text/plain": [
       "[('Bruce', 'Ernst', 6000.0),\n",
       " ('Pat', 'Fay', 6000.0),\n",
       " ('Charles', 'Johnson', 6200.0),\n",
       " ('Shanta', 'Vollman', 6500.0),\n",
       " ('Susan', 'Mavris', 6500.0),\n",
       " ('Luis', 'Popp', 6900.0)]"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "%%sql \n",
    "SELECT \n",
    "    first_name, last_name, salary \n",
    "FROM \n",
    "    employees \n",
    "WHERE salary > 5000 AND salary < 7000 \n",
    "ORDER BY salary;"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 221
    },
    "executionInfo": {
     "elapsed": 59,
     "status": "ok",
     "timestamp": 1668546498866,
     "user": {
      "displayName": "Aleksandar Vakanski",
      "userId": "07675307153279708378"
     },
     "user_tz": 420
    },
    "id": "rWRZdEJNRpZo",
    "outputId": "d3a8007a-2394-4536-9890-623b785c7e42"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " * sqlite://\n",
      "Done.\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<table>\n",
       "    <thead>\n",
       "        <tr>\n",
       "            <th>first_name</th>\n",
       "            <th>last_name</th>\n",
       "            <th>salary</th>\n",
       "        </tr>\n",
       "    </thead>\n",
       "    <tbody>\n",
       "        <tr>\n",
       "            <td>Bruce</td>\n",
       "            <td>Ernst</td>\n",
       "            <td>6000.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>Pat</td>\n",
       "            <td>Fay</td>\n",
       "            <td>6000.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>Charles</td>\n",
       "            <td>Johnson</td>\n",
       "            <td>6200.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>Shanta</td>\n",
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       "            <td>6500.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>Susan</td>\n",
       "            <td>Mavris</td>\n",
       "            <td>6500.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>Luis</td>\n",
       "            <td>Popp</td>\n",
       "            <td>6900.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>Kimberely</td>\n",
       "            <td>Grant</td>\n",
       "            <td>7000.0</td>\n",
       "        </tr>\n",
       "    </tbody>\n",
       "</table>"
      ],
      "text/plain": [
       "[('Bruce', 'Ernst', 6000.0),\n",
       " ('Pat', 'Fay', 6000.0),\n",
       " ('Charles', 'Johnson', 6200.0),\n",
       " ('Shanta', 'Vollman', 6500.0),\n",
       " ('Susan', 'Mavris', 6500.0),\n",
       " ('Luis', 'Popp', 6900.0),\n",
       " ('Kimberely', 'Grant', 7000.0)]"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "%%sql\n",
    "SELECT \n",
    "    first_name, last_name, salary \n",
    "FROM \n",
    "    employees \n",
    "WHERE salary BETWEEN 5000 AND 7000 \n",
    "ORDER BY salary;"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 137
    },
    "executionInfo": {
     "elapsed": 57,
     "status": "ok",
     "timestamp": 1668546498867,
     "user": {
      "displayName": "Aleksandar Vakanski",
      "userId": "07675307153279708378"
     },
     "user_tz": 420
    },
    "id": "2WHcM351M6ox",
    "outputId": "73e68f06-edb1-4e35-f739-41a15659cdf8"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " * sqlite://\n",
      "Done.\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<table>\n",
       "    <thead>\n",
       "        <tr>\n",
       "            <th>first_name</th>\n",
       "            <th>last_name</th>\n",
       "            <th>salary</th>\n",
       "        </tr>\n",
       "    </thead>\n",
       "    <tbody>\n",
       "        <tr>\n",
       "            <td>Bruce</td>\n",
       "            <td>Ernst</td>\n",
       "            <td>6000.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>Pat</td>\n",
       "            <td>Fay</td>\n",
       "            <td>6000.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>Kimberely</td>\n",
       "            <td>Grant</td>\n",
       "            <td>7000.0</td>\n",
       "        </tr>\n",
       "    </tbody>\n",
       "</table>"
      ],
      "text/plain": [
       "[('Bruce', 'Ernst', 6000.0),\n",
       " ('Pat', 'Fay', 6000.0),\n",
       " ('Kimberely', 'Grant', 7000.0)]"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "%%sql \n",
    "SELECT \n",
    "    first_name, last_name, salary \n",
    "FROM \n",
    "    employees \n",
    "WHERE salary = 6000 OR salary = 7000 \n",
    "ORDER BY salary;"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Select employees with first names that start with `jo`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 158
    },
    "executionInfo": {
     "elapsed": 54,
     "status": "ok",
     "timestamp": 1668546498867,
     "user": {
      "displayName": "Aleksandar Vakanski",
      "userId": "07675307153279708378"
     },
     "user_tz": 420
    },
    "id": "jkR-H_s2GLM_",
    "outputId": "9bbb7833-2ac6-43ca-ae65-5e7c0dee6feb"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " * sqlite://\n",
      "Done.\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<table>\n",
       "    <thead>\n",
       "        <tr>\n",
       "            <th>employee_id</th>\n",
       "            <th>first_name</th>\n",
       "            <th>last_name</th>\n",
       "        </tr>\n",
       "    </thead>\n",
       "    <tbody>\n",
       "        <tr>\n",
       "            <td>110</td>\n",
       "            <td>John</td>\n",
       "            <td>Chen</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>145</td>\n",
       "            <td>John</td>\n",
       "            <td>Russell</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>176</td>\n",
       "            <td>Jonathon</td>\n",
       "            <td>Taylor</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>112</td>\n",
       "            <td>Jose Manuel</td>\n",
       "            <td>Urman</td>\n",
       "        </tr>\n",
       "    </tbody>\n",
       "</table>"
      ],
      "text/plain": [
       "[(110, 'John', 'Chen'),\n",
       " (145, 'John', 'Russell'),\n",
       " (176, 'Jonathon', 'Taylor'),\n",
       " (112, 'Jose Manuel', 'Urman')]"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "%%sql \n",
    "SELECT \n",
    "    employee_id, first_name, last_name \n",
    "FROM \n",
    "    employees \n",
    "WHERE first_name LIKE 'jo%' \n",
    "ORDER BY first_name;"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Select employees with first names whose second character is `h`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " * sqlite://\n",
      "Done.\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<table>\n",
       "    <thead>\n",
       "        <tr>\n",
       "            <th>employee_id</th>\n",
       "            <th>first_name</th>\n",
       "            <th>last_name</th>\n",
       "        </tr>\n",
       "    </thead>\n",
       "    <tbody>\n",
       "        <tr>\n",
       "            <td>179</td>\n",
       "            <td>Charles</td>\n",
       "            <td>Johnson</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>123</td>\n",
       "            <td>Shanta</td>\n",
       "            <td>Vollman</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>205</td>\n",
       "            <td>Shelley</td>\n",
       "            <td>Higgins</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>116</td>\n",
       "            <td>Shelli</td>\n",
       "            <td>Baida</td>\n",
       "        </tr>\n",
       "    </tbody>\n",
       "</table>"
      ],
      "text/plain": [
       "[(179, 'Charles', 'Johnson'),\n",
       " (123, 'Shanta', 'Vollman'),\n",
       " (205, 'Shelley', 'Higgins'),\n",
       " (116, 'Shelli', 'Baida')]"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "%%sql \n",
    "SELECT \n",
    "    employee_id, first_name, last_name\n",
    "FROM\n",
    "    employees\n",
    "WHERE\n",
    "    first_name LIKE '_h%'\n",
    "ORDER BY first_name;"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " * sqlite://\n",
      "Done.\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<table>\n",
       "    <thead>\n",
       "        <tr>\n",
       "            <th>first_name</th>\n",
       "            <th>last_name</th>\n",
       "            <th>department_id</th>\n",
       "        </tr>\n",
       "    </thead>\n",
       "    <tbody>\n",
       "        <tr>\n",
       "            <td>John</td>\n",
       "            <td>Russell</td>\n",
       "            <td>8</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>Karen</td>\n",
       "            <td>Partners</td>\n",
       "            <td>8</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>Jonathon</td>\n",
       "            <td>Taylor</td>\n",
       "            <td>8</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>Jack</td>\n",
       "            <td>Livingston</td>\n",
       "            <td>8</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>Kimberely</td>\n",
       "            <td>Grant</td>\n",
       "            <td>8</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>Charles</td>\n",
       "            <td>Johnson</td>\n",
       "            <td>8</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>Steven</td>\n",
       "            <td>King</td>\n",
       "            <td>9</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>Neena</td>\n",
       "            <td>Kochhar</td>\n",
       "            <td>9</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>Lex</td>\n",
       "            <td>De Haan</td>\n",
       "            <td>9</td>\n",
       "        </tr>\n",
       "    </tbody>\n",
       "</table>"
      ],
      "text/plain": [
       "[('John', 'Russell', 8),\n",
       " ('Karen', 'Partners', 8),\n",
       " ('Jonathon', 'Taylor', 8),\n",
       " ('Jack', 'Livingston', 8),\n",
       " ('Kimberely', 'Grant', 8),\n",
       " ('Charles', 'Johnson', 8),\n",
       " ('Steven', 'King', 9),\n",
       " ('Neena', 'Kochhar', 9),\n",
       " ('Lex', 'De Haan', 9)]"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "%%sql \n",
    "SELECT \n",
    "    first_name, last_name, department_id\n",
    "FROM\n",
    "    employees\n",
    "WHERE department_id IN (8, 9)\n",
    "ORDER BY department_id;"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "tags": []
   },
   "source": [
    "### IS NULL Operator\n",
    "\n",
    "To determine whether a row or column has missing or non-defined values, we can use the `IS NULL` operator. \n",
    "\n",
    "For instance, to find all employees who do not have phone numbers, we use the `IS NUL` operator as follows."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " * sqlite://\n",
      "Done.\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<table>\n",
       "    <thead>\n",
       "        <tr>\n",
       "            <th>first_name</th>\n",
       "            <th>last_name</th>\n",
       "            <th>phone_number</th>\n",
       "        </tr>\n",
       "    </thead>\n",
       "    <tbody>\n",
       "        <tr>\n",
       "            <td>Charles</td>\n",
       "            <td>Johnson</td>\n",
       "            <td>None</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>Jack</td>\n",
       "            <td>Livingston</td>\n",
       "            <td>None</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>John</td>\n",
       "            <td>Russell</td>\n",
       "            <td>None</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>Jonathon</td>\n",
       "            <td>Taylor</td>\n",
       "            <td>None</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>Karen</td>\n",
       "            <td>Partners</td>\n",
       "            <td>None</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>Kimberely</td>\n",
       "            <td>Grant</td>\n",
       "            <td>None</td>\n",
       "        </tr>\n",
       "    </tbody>\n",
       "</table>"
      ],
      "text/plain": [
       "[('Charles', 'Johnson', None),\n",
       " ('Jack', 'Livingston', None),\n",
       " ('John', 'Russell', None),\n",
       " ('Jonathon', 'Taylor', None),\n",
       " ('Karen', 'Partners', None),\n",
       " ('Kimberely', 'Grant', None)]"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "%%sql \n",
    "SELECT \n",
    "    first_name, last_name, phone_number\n",
    "FROM\n",
    "    employees\n",
    "WHERE phone_number IS NULL\n",
    "ORDER BY first_name , last_name;"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "GaIG3J4cbJda"
   },
   "source": [
    "## 10.8 Conditional Expressions <a name='10.8-conditional-expressions'></a>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "FLrXfGRublAp"
   },
   "source": [
    "The `CASE` expression is used to add if-then-else logic to SQL statements, which allows to evaluate a list of conditions and returns one of the possible results.\n",
    "\n",
    "In the next cell, the `CASE` expression returns the results `Low`, `Average`, or `High` based on the conditions regarding the salary. The results are collected in the `evaluation` column. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 389
    },
    "executionInfo": {
     "elapsed": 52,
     "status": "ok",
     "timestamp": 1668546498867,
     "user": {
      "displayName": "Aleksandar Vakanski",
      "userId": "07675307153279708378"
     },
     "user_tz": 420
    },
    "id": "nUsDyB9qGLRR",
    "outputId": "3139b973-92c1-486a-b96d-80ccad5b83a5"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " * sqlite://\n",
      "Done.\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<table>\n",
       "    <thead>\n",
       "        <tr>\n",
       "            <th>first_name</th>\n",
       "            <th>last_name</th>\n",
       "            <th>evaluation</th>\n",
       "        </tr>\n",
       "    </thead>\n",
       "    <tbody>\n",
       "        <tr>\n",
       "            <td>Steven</td>\n",
       "            <td>King</td>\n",
       "            <td>High</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>Neena</td>\n",
       "            <td>Kochhar</td>\n",
       "            <td>High</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>Lex</td>\n",
       "            <td>De Haan</td>\n",
       "            <td>High</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>Alexander</td>\n",
       "            <td>Hunold</td>\n",
       "            <td>High</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>Bruce</td>\n",
       "            <td>Ernst</td>\n",
       "            <td>High</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>David</td>\n",
       "            <td>Austin</td>\n",
       "            <td>Average</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>Valli</td>\n",
       "            <td>Pataballa</td>\n",
       "            <td>Average</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>Diana</td>\n",
       "            <td>Lorentz</td>\n",
       "            <td>Average</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>Nancy</td>\n",
       "            <td>Greenberg</td>\n",
       "            <td>High</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>Daniel</td>\n",
       "            <td>Faviet</td>\n",
       "            <td>High</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>John</td>\n",
       "            <td>Chen</td>\n",
       "            <td>High</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>Ismael</td>\n",
       "            <td>Sciarra</td>\n",
       "            <td>High</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>Jose Manuel</td>\n",
       "            <td>Urman</td>\n",
       "            <td>High</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>Luis</td>\n",
       "            <td>Popp</td>\n",
       "            <td>High</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>Den</td>\n",
       "            <td>Raphaely</td>\n",
       "            <td>High</td>\n",
       "        </tr>\n",
       "    </tbody>\n",
       "</table>"
      ],
      "text/plain": [
       "[('Steven', 'King', 'High'),\n",
       " ('Neena', 'Kochhar', 'High'),\n",
       " ('Lex', 'De Haan', 'High'),\n",
       " ('Alexander', 'Hunold', 'High'),\n",
       " ('Bruce', 'Ernst', 'High'),\n",
       " ('David', 'Austin', 'Average'),\n",
       " ('Valli', 'Pataballa', 'Average'),\n",
       " ('Diana', 'Lorentz', 'Average'),\n",
       " ('Nancy', 'Greenberg', 'High'),\n",
       " ('Daniel', 'Faviet', 'High'),\n",
       " ('John', 'Chen', 'High'),\n",
       " ('Ismael', 'Sciarra', 'High'),\n",
       " ('Jose Manuel', 'Urman', 'High'),\n",
       " ('Luis', 'Popp', 'High'),\n",
       " ('Den', 'Raphaely', 'High')]"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "%%sql \n",
    "SELECT \n",
    "    first_name, last_name,\n",
    "CASE WHEN salary < 3000 THEN 'Low' \n",
    "     WHEN salary >= 3000 AND salary <= 5000 THEN 'Average' \n",
    "     WHEN salary > 5000 THEN 'High' \n",
    "END evaluation  \n",
    "FROM \n",
    "    employees\n",
    "LIMIT 15;"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "7eB9fXgqc9gy"
   },
   "source": [
    "## 10.9 Joining Multiple Tables <a name='10.9-joining-multiple-tables'></a>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "YPlF-mKndx3B"
   },
   "source": [
    "SQL provides several ways to join tables, such as `INNER JOIN`, `LEFT JOIN`, `RIGHT JOIN`, `FULL JOIN`, `CROSS JOIN`, and others. \n",
    "\n",
    "### INNER JOIN\n",
    "\n",
    "`INNER JOIN` combines rows from two or more tables based on a related column between them. It retrieves only the rows that have matching values in both tables.\n",
    "\n",
    "The syntax is:\n",
    "\n",
    "    SELECT \n",
    "        column1, column2, ...\n",
    "    FROM \n",
    "        table1\n",
    "    INNER JOIN table2 ON table1.columnX = table2.columnX;\n",
    "\n",
    "It specifies to join `table1` and `table2` by matching values in `columnX` from `table1` and `columnX` from `table2`, adn returns `column1, column2, ...` from the joined tables.\n",
    "\n",
    "Let's show how we can use `INNER JOIN`, where for instance, we want to retrieve the list of employees who work in departments 1, 2, and 3, and we would like to list the names of the departments. \n",
    "\n",
    "To do that, first we can notice that both the `employees` table and the `departments` table have a column `department_id`. Therefore, we can use the `department_id` column in the `employees` table as the foreign key column to link the `employees` to the `departments` table. \n",
    "\n",
    "Let's first display the employees who work in departments 1, 2, and 3."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 263
    },
    "executionInfo": {
     "elapsed": 50,
     "status": "ok",
     "timestamp": 1668546498868,
     "user": {
      "displayName": "Aleksandar Vakanski",
      "userId": "07675307153279708378"
     },
     "user_tz": 420
    },
    "id": "83UlDh2-yUlQ",
    "outputId": "df1bb096-835c-4ca1-fd57-6ebca6c25ab6"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " * sqlite://\n",
      "Done.\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<table>\n",
       "    <thead>\n",
       "        <tr>\n",
       "            <th>first_name</th>\n",
       "            <th>last_name</th>\n",
       "            <th>department_id</th>\n",
       "        </tr>\n",
       "    </thead>\n",
       "    <tbody>\n",
       "        <tr>\n",
       "            <td>Jennifer</td>\n",
       "            <td>Whalen</td>\n",
       "            <td>1</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>Michael</td>\n",
       "            <td>Hartstein</td>\n",
       "            <td>2</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>Pat</td>\n",
       "            <td>Fay</td>\n",
       "            <td>2</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>Den</td>\n",
       "            <td>Raphaely</td>\n",
       "            <td>3</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>Alexander</td>\n",
       "            <td>Khoo</td>\n",
       "            <td>3</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>Shelli</td>\n",
       "            <td>Baida</td>\n",
       "            <td>3</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>Sigal</td>\n",
       "            <td>Tobias</td>\n",
       "            <td>3</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>Guy</td>\n",
       "            <td>Himuro</td>\n",
       "            <td>3</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>Karen</td>\n",
       "            <td>Colmenares</td>\n",
       "            <td>3</td>\n",
       "        </tr>\n",
       "    </tbody>\n",
       "</table>"
      ],
      "text/plain": [
       "[('Jennifer', 'Whalen', 1),\n",
       " ('Michael', 'Hartstein', 2),\n",
       " ('Pat', 'Fay', 2),\n",
       " ('Den', 'Raphaely', 3),\n",
       " ('Alexander', 'Khoo', 3),\n",
       " ('Shelli', 'Baida', 3),\n",
       " ('Sigal', 'Tobias', 3),\n",
       " ('Guy', 'Himuro', 3),\n",
       " ('Karen', 'Colmenares', 3)]"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "%%sql \n",
    "SELECT \n",
    "    first_name, last_name, department_id \n",
    "FROM \n",
    "    employees \n",
    "WHERE department_id IN (1, 2, 3) \n",
    "ORDER BY department_id;"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "DOHaywdZzKVI"
   },
   "source": [
    "We can also find the names of the departments that have a `department_id` of 1, 2, and 3. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 137
    },
    "executionInfo": {
     "elapsed": 47,
     "status": "ok",
     "timestamp": 1668546498868,
     "user": {
      "displayName": "Aleksandar Vakanski",
      "userId": "07675307153279708378"
     },
     "user_tz": 420
    },
    "id": "EVESoBuzzLOQ",
    "outputId": "9eeb7184-33eb-42d1-d6ba-57d5407c15f2"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " * sqlite://\n",
      "Done.\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<table>\n",
       "    <thead>\n",
       "        <tr>\n",
       "            <th>department_id</th>\n",
       "            <th>department_name</th>\n",
       "        </tr>\n",
       "    </thead>\n",
       "    <tbody>\n",
       "        <tr>\n",
       "            <td>1</td>\n",
       "            <td>Administration</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>2</td>\n",
       "            <td>Marketing</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>3</td>\n",
       "            <td>Purchasing</td>\n",
       "        </tr>\n",
       "    </tbody>\n",
       "</table>"
      ],
      "text/plain": [
       "[(1, 'Administration'), (2, 'Marketing'), (3, 'Purchasing')]"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "%%sql \n",
    "SELECT \n",
    "    department_id, department_name \n",
    "FROM \n",
    "    departments\n",
    "WHERE department_id IN (1, 2, 3);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "DXtqPD2sznss"
   },
   "source": [
    "Next, we join the `employees` and `departments` tables, and use `INNER JOIN` to match the `department_id` column in the two tables. For each row, if the condition `departments.department_id = employees.department_id` is satisfied, the combined row will include data from rows in both `employees` and `departments` tables in the result set."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 263
    },
    "executionInfo": {
     "elapsed": 46,
     "status": "ok",
     "timestamp": 1668546498869,
     "user": {
      "displayName": "Aleksandar Vakanski",
      "userId": "07675307153279708378"
     },
     "user_tz": 420
    },
    "id": "VsodnK_kbIKt",
    "outputId": "39470e2f-0551-48a1-f8de-a56c7c63eae1"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " * sqlite://\n",
      "Done.\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<table>\n",
       "    <thead>\n",
       "        <tr>\n",
       "            <th>first_name</th>\n",
       "            <th>last_name</th>\n",
       "            <th>department_id</th>\n",
       "            <th>department_id_1</th>\n",
       "            <th>department_name</th>\n",
       "        </tr>\n",
       "    </thead>\n",
       "    <tbody>\n",
       "        <tr>\n",
       "            <td>Jennifer</td>\n",
       "            <td>Whalen</td>\n",
       "            <td>1</td>\n",
       "            <td>1</td>\n",
       "            <td>Administration</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>Michael</td>\n",
       "            <td>Hartstein</td>\n",
       "            <td>2</td>\n",
       "            <td>2</td>\n",
       "            <td>Marketing</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>Pat</td>\n",
       "            <td>Fay</td>\n",
       "            <td>2</td>\n",
       "            <td>2</td>\n",
       "            <td>Marketing</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>Den</td>\n",
       "            <td>Raphaely</td>\n",
       "            <td>3</td>\n",
       "            <td>3</td>\n",
       "            <td>Purchasing</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>Alexander</td>\n",
       "            <td>Khoo</td>\n",
       "            <td>3</td>\n",
       "            <td>3</td>\n",
       "            <td>Purchasing</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>Shelli</td>\n",
       "            <td>Baida</td>\n",
       "            <td>3</td>\n",
       "            <td>3</td>\n",
       "            <td>Purchasing</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>Sigal</td>\n",
       "            <td>Tobias</td>\n",
       "            <td>3</td>\n",
       "            <td>3</td>\n",
       "            <td>Purchasing</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>Guy</td>\n",
       "            <td>Himuro</td>\n",
       "            <td>3</td>\n",
       "            <td>3</td>\n",
       "            <td>Purchasing</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>Karen</td>\n",
       "            <td>Colmenares</td>\n",
       "            <td>3</td>\n",
       "            <td>3</td>\n",
       "            <td>Purchasing</td>\n",
       "        </tr>\n",
       "    </tbody>\n",
       "</table>"
      ],
      "text/plain": [
       "[('Jennifer', 'Whalen', 1, 1, 'Administration'),\n",
       " ('Michael', 'Hartstein', 2, 2, 'Marketing'),\n",
       " ('Pat', 'Fay', 2, 2, 'Marketing'),\n",
       " ('Den', 'Raphaely', 3, 3, 'Purchasing'),\n",
       " ('Alexander', 'Khoo', 3, 3, 'Purchasing'),\n",
       " ('Shelli', 'Baida', 3, 3, 'Purchasing'),\n",
       " ('Sigal', 'Tobias', 3, 3, 'Purchasing'),\n",
       " ('Guy', 'Himuro', 3, 3, 'Purchasing'),\n",
       " ('Karen', 'Colmenares', 3, 3, 'Purchasing')]"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "%%sql\n",
    "SELECT \n",
    "    first_name, last_name, employees.department_id, departments.department_id, department_name \n",
    "FROM \n",
    "    employees \n",
    "INNER JOIN departments ON departments.department_id = employees.department_id \n",
    "WHERE employees.department_id IN (1, 2, 3);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let's look at one more example, where we used `INNER JOIN` to join three tables. Specifically, in the next cell we use one more `INNER JOIN` clause to join the tables `employees` and `jobs` using the `jobs_id` column, in order to retrieve the information about the `job_title` column from the `jobs` table."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " * sqlite://\n",
      "Done.\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<table>\n",
       "    <thead>\n",
       "        <tr>\n",
       "            <th>first_name</th>\n",
       "            <th>last_name</th>\n",
       "            <th>job_title</th>\n",
       "            <th>department_name</th>\n",
       "        </tr>\n",
       "    </thead>\n",
       "    <tbody>\n",
       "        <tr>\n",
       "            <td>Den</td>\n",
       "            <td>Raphaely</td>\n",
       "            <td>Purchasing Manager</td>\n",
       "            <td>Purchasing</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>Alexander</td>\n",
       "            <td>Khoo</td>\n",
       "            <td>Purchasing Clerk</td>\n",
       "            <td>Purchasing</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>Shelli</td>\n",
       "            <td>Baida</td>\n",
       "            <td>Purchasing Clerk</td>\n",
       "            <td>Purchasing</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>Sigal</td>\n",
       "            <td>Tobias</td>\n",
       "            <td>Purchasing Clerk</td>\n",
       "            <td>Purchasing</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>Guy</td>\n",
       "            <td>Himuro</td>\n",
       "            <td>Purchasing Clerk</td>\n",
       "            <td>Purchasing</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>Karen</td>\n",
       "            <td>Colmenares</td>\n",
       "            <td>Purchasing Clerk</td>\n",
       "            <td>Purchasing</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>Jennifer</td>\n",
       "            <td>Whalen</td>\n",
       "            <td>Administration Assistant</td>\n",
       "            <td>Administration</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>Michael</td>\n",
       "            <td>Hartstein</td>\n",
       "            <td>Marketing Manager</td>\n",
       "            <td>Marketing</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>Pat</td>\n",
       "            <td>Fay</td>\n",
       "            <td>Marketing Representative</td>\n",
       "            <td>Marketing</td>\n",
       "        </tr>\n",
       "    </tbody>\n",
       "</table>"
      ],
      "text/plain": [
       "[('Den', 'Raphaely', 'Purchasing Manager', 'Purchasing'),\n",
       " ('Alexander', 'Khoo', 'Purchasing Clerk', 'Purchasing'),\n",
       " ('Shelli', 'Baida', 'Purchasing Clerk', 'Purchasing'),\n",
       " ('Sigal', 'Tobias', 'Purchasing Clerk', 'Purchasing'),\n",
       " ('Guy', 'Himuro', 'Purchasing Clerk', 'Purchasing'),\n",
       " ('Karen', 'Colmenares', 'Purchasing Clerk', 'Purchasing'),\n",
       " ('Jennifer', 'Whalen', 'Administration Assistant', 'Administration'),\n",
       " ('Michael', 'Hartstein', 'Marketing Manager', 'Marketing'),\n",
       " ('Pat', 'Fay', 'Marketing Representative', 'Marketing')]"
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "%%sql\n",
    "SELECT\n",
    "    first_name, last_name, job_title, department_name\n",
    "FROM\n",
    "    employees\n",
    "INNER JOIN departments ON departments.department_id = employees.department_id\n",
    "INNER JOIN jobs ON jobs.job_id = employees.job_id\n",
    "WHERE employees.department_id IN (1, 2, 3);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### LEFT JOIN\n",
    "\n",
    "`LEFT JOIN` (also referred to as `LEFT OUTER JOIN`) is similar to `INNER JOIN`, only it retrieves all rows from the left table in the `JOIN` clause and the matched rows from the right table. \n",
    "\n",
    "The \"left table\" is the table that appears on the left side of the `JOIN` clause. It is considered the primary table, and its rows are the ones that we want to retrieve or work with primarily.\n",
    "\n",
    "The \"right table\" is the table that appears on the right side of the `JOIN` clause. It is the secondary table, and we are typically interested in its data to complement or match with the data from the left table.\n",
    "\n",
    "For instance, the `countries` table is shown below, with `country_id` column being the primary key. The following query returns columns for the countries US, UK, and China."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " * sqlite://\n",
      "Done.\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<table>\n",
       "    <thead>\n",
       "        <tr>\n",
       "            <th>country_id</th>\n",
       "            <th>country_name</th>\n",
       "        </tr>\n",
       "    </thead>\n",
       "    <tbody>\n",
       "        <tr>\n",
       "            <td>CN</td>\n",
       "            <td>China</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>UK</td>\n",
       "            <td>United Kingdom</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>US</td>\n",
       "            <td>United States of America</td>\n",
       "        </tr>\n",
       "    </tbody>\n",
       "</table>"
      ],
      "text/plain": [
       "[('CN', 'China'), ('UK', 'United Kingdom'), ('US', 'United States of America')]"
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "%%sql\n",
    "SELECT\n",
    "    country_id,\n",
    "    country_name\n",
    "FROM\n",
    "    countries\n",
    "WHERE country_id IN ('US', 'UK', 'CN');"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Similarly, the `locations` table shown below has a `country_id` column as the foreign key. The query returns the locations located in the US, UK, and China."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " * sqlite://\n",
      "Done.\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<table>\n",
       "    <thead>\n",
       "        <tr>\n",
       "            <th>country_id</th>\n",
       "            <th>street_address</th>\n",
       "            <th>city</th>\n",
       "        </tr>\n",
       "    </thead>\n",
       "    <tbody>\n",
       "        <tr>\n",
       "            <td>US</td>\n",
       "            <td>2014 Jabberwocky Rd</td>\n",
       "            <td>Southlake</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>US</td>\n",
       "            <td>2011 Interiors Blvd</td>\n",
       "            <td>South San Francisco</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>US</td>\n",
       "            <td>2004 Charade Rd</td>\n",
       "            <td>Seattle</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>UK</td>\n",
       "            <td>8204 Arthur St</td>\n",
       "            <td>London</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>UK</td>\n",
       "            <td>Magdalen Centre, The Oxford Science Park</td>\n",
       "            <td>Oxford</td>\n",
       "        </tr>\n",
       "    </tbody>\n",
       "</table>"
      ],
      "text/plain": [
       "[('US', '2014 Jabberwocky Rd', 'Southlake'),\n",
       " ('US', '2011 Interiors Blvd', 'South San Francisco'),\n",
       " ('US', '2004 Charade Rd', 'Seattle'),\n",
       " ('UK', '8204 Arthur St', 'London'),\n",
       " ('UK', 'Magdalen Centre, The Oxford Science Park', 'Oxford')]"
      ]
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "%%sql\n",
    "SELECT\n",
    "    country_id,\n",
    "    street_address,\n",
    "    city\n",
    "FROM\n",
    "    locations\n",
    "WHERE country_id IN ('US', 'UK', 'CN');"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "In the next cell, because we use the `LEFT JOIN` clause, all rows that satisfy the condition in the `WHERE` clause of the `countries` table are included in the result set. \n",
    "\n",
    "For each row in the `countries` table, the `LEFT JOIN` clause finds the matching rows in the `locations` table. If at least one matching row is found, the database engine combines the data from columns of the matching rows in both tables.\n",
    "\n",
    "In this case, there is no matching row found for the country with the `country_id` of CN, and therefore, the row in the `countries` table is included in the result set and the row in the `locations` table is filled with `None` values. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " * sqlite://\n",
      "Done.\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<table>\n",
       "    <thead>\n",
       "        <tr>\n",
       "            <th>country_name</th>\n",
       "            <th>country_id</th>\n",
       "            <th>country_id_1</th>\n",
       "            <th>street_address</th>\n",
       "            <th>city</th>\n",
       "        </tr>\n",
       "    </thead>\n",
       "    <tbody>\n",
       "        <tr>\n",
       "            <td>China</td>\n",
       "            <td>CN</td>\n",
       "            <td>None</td>\n",
       "            <td>None</td>\n",
       "            <td>None</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>United Kingdom</td>\n",
       "            <td>UK</td>\n",
       "            <td>UK</td>\n",
       "            <td>8204 Arthur St</td>\n",
       "            <td>London</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>United Kingdom</td>\n",
       "            <td>UK</td>\n",
       "            <td>UK</td>\n",
       "            <td>Magdalen Centre, The Oxford Science Park</td>\n",
       "            <td>Oxford</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>United States of America</td>\n",
       "            <td>US</td>\n",
       "            <td>US</td>\n",
       "            <td>2014 Jabberwocky Rd</td>\n",
       "            <td>Southlake</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>United States of America</td>\n",
       "            <td>US</td>\n",
       "            <td>US</td>\n",
       "            <td>2011 Interiors Blvd</td>\n",
       "            <td>South San Francisco</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>United States of America</td>\n",
       "            <td>US</td>\n",
       "            <td>US</td>\n",
       "            <td>2004 Charade Rd</td>\n",
       "            <td>Seattle</td>\n",
       "        </tr>\n",
       "    </tbody>\n",
       "</table>"
      ],
      "text/plain": [
       "[('China', 'CN', None, None, None),\n",
       " ('United Kingdom', 'UK', 'UK', '8204 Arthur St', 'London'),\n",
       " ('United Kingdom', 'UK', 'UK', 'Magdalen Centre, The Oxford Science Park', 'Oxford'),\n",
       " ('United States of America', 'US', 'US', '2014 Jabberwocky Rd', 'Southlake'),\n",
       " ('United States of America', 'US', 'US', '2011 Interiors Blvd', 'South San Francisco'),\n",
       " ('United States of America', 'US', 'US', '2004 Charade Rd', 'Seattle')]"
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "%%sql\n",
    "SELECT\n",
    "    countries.country_name,\n",
    "    countries.country_id,\n",
    "    locations.country_id,\n",
    "    locations.street_address,\n",
    "    locations.city\n",
    "FROM\n",
    "    countries\n",
    "LEFT JOIN locations ON locations.country_id = countries.country_id\n",
    "WHERE countries.country_id IN ('US', 'UK', 'CN')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "`LEFT JOIN` is useful when we want to retrieve data from a primary table and include related information from a secondary table, but we don't want to exclude records from the primary table if there are no matching rows in the secondary table."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "And, because non-matching rows in the `locations` table are filled with the `None` values, we can apply the `LEFT JOIN` clause to find mismatched rows between the tables.\n",
    "\n",
    "For example, to find the country that does not have any locations in the `locations` table, we use the following query."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " * sqlite://\n",
      "Done.\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<table>\n",
       "    <thead>\n",
       "        <tr>\n",
       "            <th>country_name</th>\n",
       "        </tr>\n",
       "    </thead>\n",
       "    <tbody>\n",
       "        <tr>\n",
       "            <td>Argentina</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>Australia</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>Belgium</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>Brazil</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>China</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>Denmark</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>Egypt</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>France</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>HongKong</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>India</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>Israel</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>Italy</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>Japan</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>Kuwait</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>Mexico</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>Netherlands</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>Nigeria</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>Singapore</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>Switzerland</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>Zambia</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>Zimbabwe</td>\n",
       "        </tr>\n",
       "    </tbody>\n",
       "</table>"
      ],
      "text/plain": [
       "[('Argentina',),\n",
       " ('Australia',),\n",
       " ('Belgium',),\n",
       " ('Brazil',),\n",
       " ('China',),\n",
       " ('Denmark',),\n",
       " ('Egypt',),\n",
       " ('France',),\n",
       " ('HongKong',),\n",
       " ('India',),\n",
       " ('Israel',),\n",
       " ('Italy',),\n",
       " ('Japan',),\n",
       " ('Kuwait',),\n",
       " ('Mexico',),\n",
       " ('Netherlands',),\n",
       " ('Nigeria',),\n",
       " ('Singapore',),\n",
       " ('Switzerland',),\n",
       " ('Zambia',),\n",
       " ('Zimbabwe',)]"
      ]
     },
     "execution_count": 42,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "%%sql\n",
    "SELECT\n",
    "    country_name\n",
    "FROM\n",
    "    countries\n",
    "LEFT JOIN locations ON locations.country_id = countries.country_id\n",
    "WHERE locations.location_id IS NULL\n",
    "ORDER BY country_name;"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Compare the previous cell to the next cell."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " * sqlite://\n",
      "Done.\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<table>\n",
       "    <thead>\n",
       "        <tr>\n",
       "            <th>country_name</th>\n",
       "            <th>country_id</th>\n",
       "            <th>country_id_1</th>\n",
       "            <th>street_address</th>\n",
       "            <th>city</th>\n",
       "        </tr>\n",
       "    </thead>\n",
       "    <tbody>\n",
       "        <tr>\n",
       "            <td>Argentina</td>\n",
       "            <td>AR</td>\n",
       "            <td>None</td>\n",
       "            <td>None</td>\n",
       "            <td>None</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>Australia</td>\n",
       "            <td>AU</td>\n",
       "            <td>None</td>\n",
       "            <td>None</td>\n",
       "            <td>None</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>Belgium</td>\n",
       "            <td>BE</td>\n",
       "            <td>None</td>\n",
       "            <td>None</td>\n",
       "            <td>None</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>Brazil</td>\n",
       "            <td>BR</td>\n",
       "            <td>None</td>\n",
       "            <td>None</td>\n",
       "            <td>None</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>Canada</td>\n",
       "            <td>CA</td>\n",
       "            <td>CA</td>\n",
       "            <td>147 Spadina Ave</td>\n",
       "            <td>Toronto</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>Switzerland</td>\n",
       "            <td>CH</td>\n",
       "            <td>None</td>\n",
       "            <td>None</td>\n",
       "            <td>None</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>China</td>\n",
       "            <td>CN</td>\n",
       "            <td>None</td>\n",
       "            <td>None</td>\n",
       "            <td>None</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>Germany</td>\n",
       "            <td>DE</td>\n",
       "            <td>DE</td>\n",
       "            <td>Schwanthalerstr. 7031</td>\n",
       "            <td>Munich</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>Denmark</td>\n",
       "            <td>DK</td>\n",
       "            <td>None</td>\n",
       "            <td>None</td>\n",
       "            <td>None</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>Egypt</td>\n",
       "            <td>EG</td>\n",
       "            <td>None</td>\n",
       "            <td>None</td>\n",
       "            <td>None</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>France</td>\n",
       "            <td>FR</td>\n",
       "            <td>None</td>\n",
       "            <td>None</td>\n",
       "            <td>None</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>HongKong</td>\n",
       "            <td>HK</td>\n",
       "            <td>None</td>\n",
       "            <td>None</td>\n",
       "            <td>None</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>Israel</td>\n",
       "            <td>IL</td>\n",
       "            <td>None</td>\n",
       "            <td>None</td>\n",
       "            <td>None</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>India</td>\n",
       "            <td>IN</td>\n",
       "            <td>None</td>\n",
       "            <td>None</td>\n",
       "            <td>None</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>Italy</td>\n",
       "            <td>IT</td>\n",
       "            <td>None</td>\n",
       "            <td>None</td>\n",
       "            <td>None</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>Japan</td>\n",
       "            <td>JP</td>\n",
       "            <td>None</td>\n",
       "            <td>None</td>\n",
       "            <td>None</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>Kuwait</td>\n",
       "            <td>KW</td>\n",
       "            <td>None</td>\n",
       "            <td>None</td>\n",
       "            <td>None</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>Mexico</td>\n",
       "            <td>MX</td>\n",
       "            <td>None</td>\n",
       "            <td>None</td>\n",
       "            <td>None</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>Nigeria</td>\n",
       "            <td>NG</td>\n",
       "            <td>None</td>\n",
       "            <td>None</td>\n",
       "            <td>None</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>Netherlands</td>\n",
       "            <td>NL</td>\n",
       "            <td>None</td>\n",
       "            <td>None</td>\n",
       "            <td>None</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>Singapore</td>\n",
       "            <td>SG</td>\n",
       "            <td>None</td>\n",
       "            <td>None</td>\n",
       "            <td>None</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>United Kingdom</td>\n",
       "            <td>UK</td>\n",
       "            <td>UK</td>\n",
       "            <td>8204 Arthur St</td>\n",
       "            <td>London</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>United Kingdom</td>\n",
       "            <td>UK</td>\n",
       "            <td>UK</td>\n",
       "            <td>Magdalen Centre, The Oxford Science Park</td>\n",
       "            <td>Oxford</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>United States of America</td>\n",
       "            <td>US</td>\n",
       "            <td>US</td>\n",
       "            <td>2004 Charade Rd</td>\n",
       "            <td>Seattle</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>United States of America</td>\n",
       "            <td>US</td>\n",
       "            <td>US</td>\n",
       "            <td>2011 Interiors Blvd</td>\n",
       "            <td>South San Francisco</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>United States of America</td>\n",
       "            <td>US</td>\n",
       "            <td>US</td>\n",
       "            <td>2014 Jabberwocky Rd</td>\n",
       "            <td>Southlake</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>Zambia</td>\n",
       "            <td>ZM</td>\n",
       "            <td>None</td>\n",
       "            <td>None</td>\n",
       "            <td>None</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>Zimbabwe</td>\n",
       "            <td>ZW</td>\n",
       "            <td>None</td>\n",
       "            <td>None</td>\n",
       "            <td>None</td>\n",
       "        </tr>\n",
       "    </tbody>\n",
       "</table>"
      ],
      "text/plain": [
       "[('Argentina', 'AR', None, None, None),\n",
       " ('Australia', 'AU', None, None, None),\n",
       " ('Belgium', 'BE', None, None, None),\n",
       " ('Brazil', 'BR', None, None, None),\n",
       " ('Canada', 'CA', 'CA', '147 Spadina Ave', 'Toronto'),\n",
       " ('Switzerland', 'CH', None, None, None),\n",
       " ('China', 'CN', None, None, None),\n",
       " ('Germany', 'DE', 'DE', 'Schwanthalerstr. 7031', 'Munich'),\n",
       " ('Denmark', 'DK', None, None, None),\n",
       " ('Egypt', 'EG', None, None, None),\n",
       " ('France', 'FR', None, None, None),\n",
       " ('HongKong', 'HK', None, None, None),\n",
       " ('Israel', 'IL', None, None, None),\n",
       " ('India', 'IN', None, None, None),\n",
       " ('Italy', 'IT', None, None, None),\n",
       " ('Japan', 'JP', None, None, None),\n",
       " ('Kuwait', 'KW', None, None, None),\n",
       " ('Mexico', 'MX', None, None, None),\n",
       " ('Nigeria', 'NG', None, None, None),\n",
       " ('Netherlands', 'NL', None, None, None),\n",
       " ('Singapore', 'SG', None, None, None),\n",
       " ('United Kingdom', 'UK', 'UK', '8204 Arthur St', 'London'),\n",
       " ('United Kingdom', 'UK', 'UK', 'Magdalen Centre, The Oxford Science Park', 'Oxford'),\n",
       " ('United States of America', 'US', 'US', '2004 Charade Rd', 'Seattle'),\n",
       " ('United States of America', 'US', 'US', '2011 Interiors Blvd', 'South San Francisco'),\n",
       " ('United States of America', 'US', 'US', '2014 Jabberwocky Rd', 'Southlake'),\n",
       " ('Zambia', 'ZM', None, None, None),\n",
       " ('Zimbabwe', 'ZW', None, None, None)]"
      ]
     },
     "execution_count": 43,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "%%sql\n",
    "SELECT\n",
    "    countries.country_name,\n",
    "    countries.country_id,\n",
    "    locations.country_id,\n",
    "    locations.street_address,\n",
    "    locations.city\n",
    "FROM\n",
    "    countries\n",
    "LEFT JOIN locations ON locations.country_id = countries.country_id"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### RIGHT JOIN\n",
    "\n",
    "By analogy, `RIGHT JOIN` (or `RIGHT OUTER JOIN`) returns all rows from the right table and the matched rows from the left table. If there are no matches in the left table, the result will contain None values for those columns from the left table."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " * sqlite://\n",
      "Done.\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<table>\n",
       "    <thead>\n",
       "        <tr>\n",
       "            <th>country_name</th>\n",
       "            <th>country_id</th>\n",
       "            <th>country_id_1</th>\n",
       "            <th>street_address</th>\n",
       "            <th>city</th>\n",
       "        </tr>\n",
       "    </thead>\n",
       "    <tbody>\n",
       "        <tr>\n",
       "            <td>Canada</td>\n",
       "            <td>CA</td>\n",
       "            <td>CA</td>\n",
       "            <td>147 Spadina Ave</td>\n",
       "            <td>Toronto</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>Germany</td>\n",
       "            <td>DE</td>\n",
       "            <td>DE</td>\n",
       "            <td>Schwanthalerstr. 7031</td>\n",
       "            <td>Munich</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>United Kingdom</td>\n",
       "            <td>UK</td>\n",
       "            <td>UK</td>\n",
       "            <td>8204 Arthur St</td>\n",
       "            <td>London</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>United Kingdom</td>\n",
       "            <td>UK</td>\n",
       "            <td>UK</td>\n",
       "            <td>Magdalen Centre, The Oxford Science Park</td>\n",
       "            <td>Oxford</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>United States of America</td>\n",
       "            <td>US</td>\n",
       "            <td>US</td>\n",
       "            <td>2014 Jabberwocky Rd</td>\n",
       "            <td>Southlake</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>United States of America</td>\n",
       "            <td>US</td>\n",
       "            <td>US</td>\n",
       "            <td>2011 Interiors Blvd</td>\n",
       "            <td>South San Francisco</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>United States of America</td>\n",
       "            <td>US</td>\n",
       "            <td>US</td>\n",
       "            <td>2004 Charade Rd</td>\n",
       "            <td>Seattle</td>\n",
       "        </tr>\n",
       "    </tbody>\n",
       "</table>"
      ],
      "text/plain": [
       "[('Canada', 'CA', 'CA', '147 Spadina Ave', 'Toronto'),\n",
       " ('Germany', 'DE', 'DE', 'Schwanthalerstr. 7031', 'Munich'),\n",
       " ('United Kingdom', 'UK', 'UK', '8204 Arthur St', 'London'),\n",
       " ('United Kingdom', 'UK', 'UK', 'Magdalen Centre, The Oxford Science Park', 'Oxford'),\n",
       " ('United States of America', 'US', 'US', '2014 Jabberwocky Rd', 'Southlake'),\n",
       " ('United States of America', 'US', 'US', '2011 Interiors Blvd', 'South San Francisco'),\n",
       " ('United States of America', 'US', 'US', '2004 Charade Rd', 'Seattle')]"
      ]
     },
     "execution_count": 44,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "%%sql\n",
    "SELECT\n",
    "    countries.country_name,\n",
    "    countries.country_id,\n",
    "    locations.country_id,\n",
    "    locations.street_address,\n",
    "    locations.city\n",
    "FROM\n",
    "    countries\n",
    "RIGHT JOIN locations ON locations.country_id = countries.country_id\n",
    "WHERE countries.country_id IN ('US', 'UK', 'CN', 'CA', 'DE', 'IT')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "`FULL JOIN` (also known as a `FULL OUTER JOIN`) combines the result sets of both a `LEFT JOIN` and a `RIGHT JOIN`, it returns all rows from both tables and includes rows from the left table that have no match in the right table (with None values for right table columns) and rows from the right table that have no match in the left table (with None values for left table columns).\n",
    "\n",
    "`CROSS JOIN` (also known as a `CARTESIAN JOIN`), combines all rows from the first table with all rows from the second table, and generates all possible combinations of data."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "O5hYRZFW0wLx"
   },
   "source": [
    "## 10.10 Return Data Statistics <a name='10.10-return-data-statistics'></a>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "kZFwPAMy02ry"
   },
   "source": [
    "*Aggregate functions* in SQL take a list of values and return a single value, such as the average `AVG()`, `MIN()`, `MAX()`, `SUM()`, or `COUNT()`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 95
    },
    "executionInfo": {
     "elapsed": 42,
     "status": "ok",
     "timestamp": 1668546498869,
     "user": {
      "displayName": "Aleksandar Vakanski",
      "userId": "07675307153279708378"
     },
     "user_tz": 420
    },
    "id": "rddarNqh2_7f",
    "outputId": "78c221a1-abdf-438b-8318-50633df0f154"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " * sqlite://\n",
      "Done.\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<table>\n",
       "    <thead>\n",
       "        <tr>\n",
       "            <th>AVG(salary)</th>\n",
       "        </tr>\n",
       "    </thead>\n",
       "    <tbody>\n",
       "        <tr>\n",
       "            <td>8060.0</td>\n",
       "        </tr>\n",
       "    </tbody>\n",
       "</table>"
      ],
      "text/plain": [
       "[(8060.0,)]"
      ]
     },
     "execution_count": 45,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "%%sql \n",
    "SELECT \n",
    "    AVG(salary) \n",
    "FROM \n",
    "    employees;"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 95
    },
    "executionInfo": {
     "elapsed": 39,
     "status": "ok",
     "timestamp": 1668546498869,
     "user": {
      "displayName": "Aleksandar Vakanski",
      "userId": "07675307153279708378"
     },
     "user_tz": 420
    },
    "id": "CQc0D-KvlSqH",
    "outputId": "aff04c02-b4c5-4727-d474-40013f61786f"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " * sqlite://\n",
      "Done.\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<table>\n",
       "    <thead>\n",
       "        <tr>\n",
       "            <th>MAX(salary)</th>\n",
       "        </tr>\n",
       "    </thead>\n",
       "    <tbody>\n",
       "        <tr>\n",
       "            <td>24000.0</td>\n",
       "        </tr>\n",
       "    </tbody>\n",
       "</table>"
      ],
      "text/plain": [
       "[(24000.0,)]"
      ]
     },
     "execution_count": 46,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "%%sql \n",
    "SELECT \n",
    "    MAX(salary) \n",
    "FROM \n",
    "    employees;"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 95
    },
    "executionInfo": {
     "elapsed": 38,
     "status": "ok",
     "timestamp": 1668546498870,
     "user": {
      "displayName": "Aleksandar Vakanski",
      "userId": "07675307153279708378"
     },
     "user_tz": 420
    },
    "id": "X25mN5iXlngk",
    "outputId": "67ba6402-7c71-42d2-8fc5-c947c494d461"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " * sqlite://\n",
      "Done.\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<table>\n",
       "    <thead>\n",
       "        <tr>\n",
       "            <th>SUM(salary)</th>\n",
       "        </tr>\n",
       "    </thead>\n",
       "    <tbody>\n",
       "        <tr>\n",
       "            <td>41200.0</td>\n",
       "        </tr>\n",
       "    </tbody>\n",
       "</table>"
      ],
      "text/plain": [
       "[(41200.0,)]"
      ]
     },
     "execution_count": 47,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "%%sql \n",
    "SELECT \n",
    "    SUM(salary) \n",
    "FROM \n",
    "    employees \n",
    "WHERE department_id = 5;"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "BdaOzPbimOv4"
   },
   "source": [
    "`COUNT` returns the number of rows in a table. It can be used by providing the name of a column, or it can also be used with an asterisk `*` as in the following cell."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 95
    },
    "executionInfo": {
     "elapsed": 36,
     "status": "ok",
     "timestamp": 1668546498870,
     "user": {
      "displayName": "Aleksandar Vakanski",
      "userId": "07675307153279708378"
     },
     "user_tz": 420
    },
    "id": "toQh7LgKl9dv",
    "outputId": "77943f0a-0f96-4017-83ee-594de81c78f1"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " * sqlite://\n",
      "Done.\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<table>\n",
       "    <thead>\n",
       "        <tr>\n",
       "            <th>COUNT(employee_id)</th>\n",
       "        </tr>\n",
       "    </thead>\n",
       "    <tbody>\n",
       "        <tr>\n",
       "            <td>40</td>\n",
       "        </tr>\n",
       "    </tbody>\n",
       "</table>"
      ],
      "text/plain": [
       "[(40,)]"
      ]
     },
     "execution_count": 48,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "%%sql \n",
    "SELECT \n",
    "    COUNT(employee_id) \n",
    "FROM \n",
    "    employees;"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 95
    },
    "executionInfo": {
     "elapsed": 34,
     "status": "ok",
     "timestamp": 1668546498871,
     "user": {
      "displayName": "Aleksandar Vakanski",
      "userId": "07675307153279708378"
     },
     "user_tz": 420
    },
    "id": "C2CEZSXmmf5p",
    "outputId": "20eb0696-cf9a-42ae-810f-48a72d61a9f1"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " * sqlite://\n",
      "Done.\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<table>\n",
       "    <thead>\n",
       "        <tr>\n",
       "            <th>COUNT(*)</th>\n",
       "        </tr>\n",
       "    </thead>\n",
       "    <tbody>\n",
       "        <tr>\n",
       "            <td>40</td>\n",
       "        </tr>\n",
       "    </tbody>\n",
       "</table>"
      ],
      "text/plain": [
       "[(40,)]"
      ]
     },
     "execution_count": 49,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "%%sql \n",
    "SELECT \n",
    "    COUNT(*) \n",
    "FROM \n",
    "    employees;"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "o3983LmT1mrQ"
   },
   "source": [
    "## 10.11 Grouping Data <a name='10.11-grouping-data'></a>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "yGzk2k0R1wYl"
   },
   "source": [
    "`GROUP BY` allows to group rows based on values from more than one column. It is typically combined with aggregate functions, like `COUNT`, `SUM`, `AVG`, `MIN`, and `MAX`.\n",
    "\n",
    "For instance, let's assume that we would like to retrieve information about the average salary in each department. In the next cell we will first display the salaries of all employees per department, and in the following cell we can see how `GROUP BY` is used to calculate the average salary for each department. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " * sqlite://\n",
      "Done.\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<table>\n",
       "    <thead>\n",
       "        <tr>\n",
       "            <th>department_id</th>\n",
       "            <th>salary</th>\n",
       "        </tr>\n",
       "    </thead>\n",
       "    <tbody>\n",
       "        <tr>\n",
       "            <td>9</td>\n",
       "            <td>24000.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>9</td>\n",
       "            <td>17000.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>9</td>\n",
       "            <td>17000.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>6</td>\n",
       "            <td>9000.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>6</td>\n",
       "            <td>6000.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>6</td>\n",
       "            <td>4800.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>6</td>\n",
       "            <td>4800.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>6</td>\n",
       "            <td>4200.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>10</td>\n",
       "            <td>12000.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>10</td>\n",
       "            <td>9000.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>10</td>\n",
       "            <td>8200.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>10</td>\n",
       "            <td>7700.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>10</td>\n",
       "            <td>7800.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>10</td>\n",
       "            <td>6900.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>3</td>\n",
       "            <td>11000.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>3</td>\n",
       "            <td>3100.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>3</td>\n",
       "            <td>2900.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>3</td>\n",
       "            <td>2800.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>3</td>\n",
       "            <td>2600.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>3</td>\n",
       "            <td>2500.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>5</td>\n",
       "            <td>8000.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>5</td>\n",
       "            <td>8200.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>5</td>\n",
       "            <td>7900.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>5</td>\n",
       "            <td>6500.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>5</td>\n",
       "            <td>2700.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>8</td>\n",
       "            <td>14000.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>8</td>\n",
       "            <td>13500.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>8</td>\n",
       "            <td>8600.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>8</td>\n",
       "            <td>8400.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>8</td>\n",
       "            <td>7000.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>8</td>\n",
       "            <td>6200.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>5</td>\n",
       "            <td>4000.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>5</td>\n",
       "            <td>3900.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>1</td>\n",
       "            <td>4400.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>2</td>\n",
       "            <td>13000.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>2</td>\n",
       "            <td>6000.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>4</td>\n",
       "            <td>6500.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>7</td>\n",
       "            <td>10000.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>11</td>\n",
       "            <td>12000.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>11</td>\n",
       "            <td>8300.0</td>\n",
       "        </tr>\n",
       "    </tbody>\n",
       "</table>"
      ],
      "text/plain": [
       "[(9, 24000.0),\n",
       " (9, 17000.0),\n",
       " (9, 17000.0),\n",
       " (6, 9000.0),\n",
       " (6, 6000.0),\n",
       " (6, 4800.0),\n",
       " (6, 4800.0),\n",
       " (6, 4200.0),\n",
       " (10, 12000.0),\n",
       " (10, 9000.0),\n",
       " (10, 8200.0),\n",
       " (10, 7700.0),\n",
       " (10, 7800.0),\n",
       " (10, 6900.0),\n",
       " (3, 11000.0),\n",
       " (3, 3100.0),\n",
       " (3, 2900.0),\n",
       " (3, 2800.0),\n",
       " (3, 2600.0),\n",
       " (3, 2500.0),\n",
       " (5, 8000.0),\n",
       " (5, 8200.0),\n",
       " (5, 7900.0),\n",
       " (5, 6500.0),\n",
       " (5, 2700.0),\n",
       " (8, 14000.0),\n",
       " (8, 13500.0),\n",
       " (8, 8600.0),\n",
       " (8, 8400.0),\n",
       " (8, 7000.0),\n",
       " (8, 6200.0),\n",
       " (5, 4000.0),\n",
       " (5, 3900.0),\n",
       " (1, 4400.0),\n",
       " (2, 13000.0),\n",
       " (2, 6000.0),\n",
       " (4, 6500.0),\n",
       " (7, 10000.0),\n",
       " (11, 12000.0),\n",
       " (11, 8300.0)]"
      ]
     },
     "execution_count": 50,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "%%sql \n",
    "SELECT \n",
    "    department_id, salary\n",
    "FROM \n",
    "    employees "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 305
    },
    "executionInfo": {
     "elapsed": 307,
     "status": "ok",
     "timestamp": 1668546499147,
     "user": {
      "displayName": "Aleksandar Vakanski",
      "userId": "07675307153279708378"
     },
     "user_tz": 420
    },
    "id": "VoHmAANV3X2s",
    "outputId": "2b2f52a3-bf57-4c24-a8c0-5401f1c3569a"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " * sqlite://\n",
      "Done.\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<table>\n",
       "    <thead>\n",
       "        <tr>\n",
       "            <th>department_id</th>\n",
       "            <th>AVG(salary)</th>\n",
       "        </tr>\n",
       "    </thead>\n",
       "    <tbody>\n",
       "        <tr>\n",
       "            <td>1</td>\n",
       "            <td>4400.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>2</td>\n",
       "            <td>9500.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>3</td>\n",
       "            <td>4150.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>4</td>\n",
       "            <td>6500.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>5</td>\n",
       "            <td>5885.714285714285</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>6</td>\n",
       "            <td>5760.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>7</td>\n",
       "            <td>10000.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>8</td>\n",
       "            <td>9616.666666666666</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>9</td>\n",
       "            <td>19333.333333333332</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>10</td>\n",
       "            <td>8600.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>11</td>\n",
       "            <td>10150.0</td>\n",
       "        </tr>\n",
       "    </tbody>\n",
       "</table>"
      ],
      "text/plain": [
       "[(1, 4400.0),\n",
       " (2, 9500.0),\n",
       " (3, 4150.0),\n",
       " (4, 6500.0),\n",
       " (5, 5885.714285714285),\n",
       " (6, 5760.0),\n",
       " (7, 10000.0),\n",
       " (8, 9616.666666666666),\n",
       " (9, 19333.333333333332),\n",
       " (10, 8600.0),\n",
       " (11, 10150.0)]"
      ]
     },
     "execution_count": 51,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "%%sql \n",
    "SELECT \n",
    "    department_id, AVG(salary) \n",
    "FROM \n",
    "    employees \n",
    "GROUP BY department_id;"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "06iZQVKIpqp3"
   },
   "source": [
    "Similarly, the following cell displays the minimum, maximum, and average salary for each department. And, instead of using the `department_id` column, it will be more convenient to display the department names. Since the `employees` table does not have a column with the department names, we will use `INNER JOIN` to retrieve the `department_name` column from the `departments` table."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 305
    },
    "executionInfo": {
     "elapsed": 59,
     "status": "ok",
     "timestamp": 1668546499148,
     "user": {
      "displayName": "Aleksandar Vakanski",
      "userId": "07675307153279708378"
     },
     "user_tz": 420
    },
    "id": "Z3dtqQf73icA",
    "outputId": "fb903209-ad01-4b5f-ea62-5a55b7692d1c"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " * sqlite://\n",
      "Done.\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<table>\n",
       "    <thead>\n",
       "        <tr>\n",
       "            <th>department_name</th>\n",
       "            <th>min_salary</th>\n",
       "            <th>max_salary</th>\n",
       "            <th>average_salary</th>\n",
       "        </tr>\n",
       "    </thead>\n",
       "    <tbody>\n",
       "        <tr>\n",
       "            <td>Accounting</td>\n",
       "            <td>8300.0</td>\n",
       "            <td>12000.0</td>\n",
       "            <td>10150.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>Administration</td>\n",
       "            <td>4400.0</td>\n",
       "            <td>4400.0</td>\n",
       "            <td>4400.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>Executive</td>\n",
       "            <td>17000.0</td>\n",
       "            <td>24000.0</td>\n",
       "            <td>19333.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>Finance</td>\n",
       "            <td>6900.0</td>\n",
       "            <td>12000.0</td>\n",
       "            <td>8600.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>Human Resources</td>\n",
       "            <td>6500.0</td>\n",
       "            <td>6500.0</td>\n",
       "            <td>6500.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>IT</td>\n",
       "            <td>4200.0</td>\n",
       "            <td>9000.0</td>\n",
       "            <td>5760.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>Marketing</td>\n",
       "            <td>6000.0</td>\n",
       "            <td>13000.0</td>\n",
       "            <td>9500.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>Public Relations</td>\n",
       "            <td>10000.0</td>\n",
       "            <td>10000.0</td>\n",
       "            <td>10000.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>Purchasing</td>\n",
       "            <td>2500.0</td>\n",
       "            <td>11000.0</td>\n",
       "            <td>4150.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>Sales</td>\n",
       "            <td>6200.0</td>\n",
       "            <td>14000.0</td>\n",
       "            <td>9617.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>Shipping</td>\n",
       "            <td>2700.0</td>\n",
       "            <td>8200.0</td>\n",
       "            <td>5886.0</td>\n",
       "        </tr>\n",
       "    </tbody>\n",
       "</table>"
      ],
      "text/plain": [
       "[('Accounting', 8300.0, 12000.0, 10150.0),\n",
       " ('Administration', 4400.0, 4400.0, 4400.0),\n",
       " ('Executive', 17000.0, 24000.0, 19333.0),\n",
       " ('Finance', 6900.0, 12000.0, 8600.0),\n",
       " ('Human Resources', 6500.0, 6500.0, 6500.0),\n",
       " ('IT', 4200.0, 9000.0, 5760.0),\n",
       " ('Marketing', 6000.0, 13000.0, 9500.0),\n",
       " ('Public Relations', 10000.0, 10000.0, 10000.0),\n",
       " ('Purchasing', 2500.0, 11000.0, 4150.0),\n",
       " ('Sales', 6200.0, 14000.0, 9617.0),\n",
       " ('Shipping', 2700.0, 8200.0, 5886.0)]"
      ]
     },
     "execution_count": 52,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "%%sql \n",
    "SELECT \n",
    "    department_name, MIN(salary) AS min_salary, MAX(salary) AS max_salary, \n",
    "    ROUND(AVG(salary)) AS average_salary \n",
    "FROM \n",
    "    employees \n",
    "INNER JOIN departments ON departments.department_id = employees.department_id \n",
    "GROUP BY department_name;"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "qj3ipXnJ4YXD"
   },
   "source": [
    "## 10.12 Modifying Data <a name='10.12-modifying-data'></a>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "g8cb7h4H4kMA"
   },
   "source": [
    "### INSERT\n",
    "\n",
    "`INSERT` is used to insert one or more rows into a table, and we already used it in subsection 10.3 when we created new tables. The general syntax is:\n",
    "\n",
    "```\n",
    "INSERT INTO table (column1, column2,...)\n",
    "VALUES (value1, value2, ...);\n",
    "```\n",
    "\n",
    "It is important to ensure that the number of values matches the number of columns, and that the value type corresponds to the data type for that column.\n",
    "\n",
    "It is also possible to insert value without specifying the columns, as in:\n",
    "\n",
    "```\n",
    "INSERT INTO table \n",
    "VALUES (value1, value2, ...);\n",
    "```\n",
    "\n",
    "For instance, to insert a new row into the `dependents` table, we can use the following code. The new row will be added to the bottom of the table `dependents`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "executionInfo": {
     "elapsed": 56,
     "status": "ok",
     "timestamp": 1668546499148,
     "user": {
      "displayName": "Aleksandar Vakanski",
      "userId": "07675307153279708378"
     },
     "user_tz": 420
    },
    "id": "x9Psimq42__0",
    "outputId": "ef9ceee6-74eb-4571-f2a7-2f0c65765ae8"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " * sqlite://\n",
      "1 rows affected.\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "[]"
      ]
     },
     "execution_count": 53,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "%%sql \n",
    "INSERT INTO \n",
    "    dependents (first_name, last_name, relationship, employee_id) \n",
    "VALUES ('Dustin', 'Johnson', 'Child', 178);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 724
    },
    "executionInfo": {
     "elapsed": 51,
     "status": "ok",
     "timestamp": 1668546499148,
     "user": {
      "displayName": "Aleksandar Vakanski",
      "userId": "07675307153279708378"
     },
     "user_tz": 420
    },
    "id": "Xf3a3Fyi3AEE",
    "outputId": "f7b03e0b-7ab4-44a3-d356-2fea09943d68"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " * sqlite://\n",
      "Done.\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<table>\n",
       "    <thead>\n",
       "        <tr>\n",
       "            <th>dependent_id</th>\n",
       "            <th>first_name</th>\n",
       "            <th>last_name</th>\n",
       "            <th>relationship</th>\n",
       "            <th>employee_id</th>\n",
       "        </tr>\n",
       "    </thead>\n",
       "    <tbody>\n",
       "        <tr>\n",
       "            <td>1</td>\n",
       "            <td>Penelope</td>\n",
       "            <td>Gietz</td>\n",
       "            <td>Child</td>\n",
       "            <td>206</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>2</td>\n",
       "            <td>Nick</td>\n",
       "            <td>Higgins</td>\n",
       "            <td>Child</td>\n",
       "            <td>205</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>3</td>\n",
       "            <td>Ed</td>\n",
       "            <td>Whalen</td>\n",
       "            <td>Child</td>\n",
       "            <td>200</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>4</td>\n",
       "            <td>Jennifer</td>\n",
       "            <td>King</td>\n",
       "            <td>Child</td>\n",
       "            <td>100</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>5</td>\n",
       "            <td>Johnny</td>\n",
       "            <td>Kochhar</td>\n",
       "            <td>Child</td>\n",
       "            <td>101</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>6</td>\n",
       "            <td>Bette</td>\n",
       "            <td>De Haan</td>\n",
       "            <td>Child</td>\n",
       "            <td>102</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>7</td>\n",
       "            <td>Grace</td>\n",
       "            <td>Faviet</td>\n",
       "            <td>Child</td>\n",
       "            <td>109</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>8</td>\n",
       "            <td>Matthew</td>\n",
       "            <td>Chen</td>\n",
       "            <td>Child</td>\n",
       "            <td>110</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>9</td>\n",
       "            <td>Joe</td>\n",
       "            <td>Sciarra</td>\n",
       "            <td>Child</td>\n",
       "            <td>111</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>10</td>\n",
       "            <td>Christian</td>\n",
       "            <td>Urman</td>\n",
       "            <td>Child</td>\n",
       "            <td>112</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>11</td>\n",
       "            <td>Zero</td>\n",
       "            <td>Popp</td>\n",
       "            <td>Child</td>\n",
       "            <td>113</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>12</td>\n",
       "            <td>Karl</td>\n",
       "            <td>Greenberg</td>\n",
       "            <td>Child</td>\n",
       "            <td>108</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>13</td>\n",
       "            <td>Uma</td>\n",
       "            <td>Mavris</td>\n",
       "            <td>Child</td>\n",
       "            <td>203</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>14</td>\n",
       "            <td>Vivien</td>\n",
       "            <td>Hunold</td>\n",
       "            <td>Child</td>\n",
       "            <td>103</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>15</td>\n",
       "            <td>Cuba</td>\n",
       "            <td>Ernst</td>\n",
       "            <td>Child</td>\n",
       "            <td>104</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>16</td>\n",
       "            <td>Fred</td>\n",
       "            <td>Austin</td>\n",
       "            <td>Child</td>\n",
       "            <td>105</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>17</td>\n",
       "            <td>Helen</td>\n",
       "            <td>Pataballa</td>\n",
       "            <td>Child</td>\n",
       "            <td>106</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>18</td>\n",
       "            <td>Dan</td>\n",
       "            <td>Lorentz</td>\n",
       "            <td>Child</td>\n",
       "            <td>107</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>19</td>\n",
       "            <td>Bob</td>\n",
       "            <td>Hartstein</td>\n",
       "            <td>Child</td>\n",
       "            <td>201</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>20</td>\n",
       "            <td>Lucille</td>\n",
       "            <td>Fay</td>\n",
       "            <td>Child</td>\n",
       "            <td>202</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>21</td>\n",
       "            <td>Kirsten</td>\n",
       "            <td>Baer</td>\n",
       "            <td>Child</td>\n",
       "            <td>204</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>22</td>\n",
       "            <td>Elvis</td>\n",
       "            <td>Khoo</td>\n",
       "            <td>Child</td>\n",
       "            <td>115</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>23</td>\n",
       "            <td>Sandra</td>\n",
       "            <td>Baida</td>\n",
       "            <td>Child</td>\n",
       "            <td>116</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>24</td>\n",
       "            <td>Cameron</td>\n",
       "            <td>Tobias</td>\n",
       "            <td>Child</td>\n",
       "            <td>117</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>25</td>\n",
       "            <td>Kevin</td>\n",
       "            <td>Himuro</td>\n",
       "            <td>Child</td>\n",
       "            <td>118</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>26</td>\n",
       "            <td>Rip</td>\n",
       "            <td>Colmenares</td>\n",
       "            <td>Child</td>\n",
       "            <td>119</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>27</td>\n",
       "            <td>Julia</td>\n",
       "            <td>Raphaely</td>\n",
       "            <td>Child</td>\n",
       "            <td>114</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>28</td>\n",
       "            <td>Woody</td>\n",
       "            <td>Russell</td>\n",
       "            <td>Child</td>\n",
       "            <td>145</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>29</td>\n",
       "            <td>Alec</td>\n",
       "            <td>Partners</td>\n",
       "            <td>Child</td>\n",
       "            <td>146</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>30</td>\n",
       "            <td>Sandra</td>\n",
       "            <td>Taylor</td>\n",
       "            <td>Child</td>\n",
       "            <td>176</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>31</td>\n",
       "            <td>Dustin</td>\n",
       "            <td>Johnson</td>\n",
       "            <td>Child</td>\n",
       "            <td>178</td>\n",
       "        </tr>\n",
       "    </tbody>\n",
       "</table>"
      ],
      "text/plain": [
       "[(1, 'Penelope', 'Gietz', 'Child', 206),\n",
       " (2, 'Nick', 'Higgins', 'Child', 205),\n",
       " (3, 'Ed', 'Whalen', 'Child', 200),\n",
       " (4, 'Jennifer', 'King', 'Child', 100),\n",
       " (5, 'Johnny', 'Kochhar', 'Child', 101),\n",
       " (6, 'Bette', 'De Haan', 'Child', 102),\n",
       " (7, 'Grace', 'Faviet', 'Child', 109),\n",
       " (8, 'Matthew', 'Chen', 'Child', 110),\n",
       " (9, 'Joe', 'Sciarra', 'Child', 111),\n",
       " (10, 'Christian', 'Urman', 'Child', 112),\n",
       " (11, 'Zero', 'Popp', 'Child', 113),\n",
       " (12, 'Karl', 'Greenberg', 'Child', 108),\n",
       " (13, 'Uma', 'Mavris', 'Child', 203),\n",
       " (14, 'Vivien', 'Hunold', 'Child', 103),\n",
       " (15, 'Cuba', 'Ernst', 'Child', 104),\n",
       " (16, 'Fred', 'Austin', 'Child', 105),\n",
       " (17, 'Helen', 'Pataballa', 'Child', 106),\n",
       " (18, 'Dan', 'Lorentz', 'Child', 107),\n",
       " (19, 'Bob', 'Hartstein', 'Child', 201),\n",
       " (20, 'Lucille', 'Fay', 'Child', 202),\n",
       " (21, 'Kirsten', 'Baer', 'Child', 204),\n",
       " (22, 'Elvis', 'Khoo', 'Child', 115),\n",
       " (23, 'Sandra', 'Baida', 'Child', 116),\n",
       " (24, 'Cameron', 'Tobias', 'Child', 117),\n",
       " (25, 'Kevin', 'Himuro', 'Child', 118),\n",
       " (26, 'Rip', 'Colmenares', 'Child', 119),\n",
       " (27, 'Julia', 'Raphaely', 'Child', 114),\n",
       " (28, 'Woody', 'Russell', 'Child', 145),\n",
       " (29, 'Alec', 'Partners', 'Child', 146),\n",
       " (30, 'Sandra', 'Taylor', 'Child', 176),\n",
       " (31, 'Dustin', 'Johnson', 'Child', 178)]"
      ]
     },
     "execution_count": 54,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# verify the changes\n",
    "%sql SELECT * from dependents"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "N9xUi0n6R9bD"
   },
   "source": [
    "### UPDATE\n",
    "\n",
    "`UPDATE` is used to update existing data in a table.\n",
    "\n",
    "For instance, to update the last name of the employee with `id=192`, we can write:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "executionInfo": {
     "elapsed": 47,
     "status": "ok",
     "timestamp": 1668546499149,
     "user": {
      "displayName": "Aleksandar Vakanski",
      "userId": "07675307153279708378"
     },
     "user_tz": 420
    },
    "id": "LhFKoRKT3AHq",
    "outputId": "1bf0116b-ebde-4350-c5b8-e541f45f5740"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " * sqlite://\n",
      "1 rows affected.\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "[]"
      ]
     },
     "execution_count": 55,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "%%sql \n",
    "UPDATE employees \n",
    "SET last_name = 'Lopez' \n",
    "WHERE employee_id = 192;"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "And we can verify the changes."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 95
    },
    "executionInfo": {
     "elapsed": 44,
     "status": "ok",
     "timestamp": 1668546499149,
     "user": {
      "displayName": "Aleksandar Vakanski",
      "userId": "07675307153279708378"
     },
     "user_tz": 420
    },
    "id": "XOsGIEm4R8fK",
    "outputId": "b869f4cb-5424-4867-c6ed-2eebeacbadc0"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " * sqlite://\n",
      "Done.\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<table>\n",
       "    <thead>\n",
       "        <tr>\n",
       "            <th>employee_id</th>\n",
       "            <th>first_name</th>\n",
       "            <th>last_name</th>\n",
       "        </tr>\n",
       "    </thead>\n",
       "    <tbody>\n",
       "        <tr>\n",
       "            <td>192</td>\n",
       "            <td>Sarah</td>\n",
       "            <td>Lopez</td>\n",
       "        </tr>\n",
       "    </tbody>\n",
       "</table>"
      ],
      "text/plain": [
       "[(192, 'Sarah', 'Lopez')]"
      ]
     },
     "execution_count": 56,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "%%sql \n",
    "SELECT\n",
    "    employee_id, first_name, last_name\n",
    "FROM \n",
    "    employees\n",
    "WHERE employee_id = 192;"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "jTGvcEMqVVvH"
   },
   "source": [
    "### DELETE\n",
    "\n",
    "`DELETE` is used to delete one or more rows from a table permanently."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "executionInfo": {
     "elapsed": 39,
     "status": "ok",
     "timestamp": 1668546499149,
     "user": {
      "displayName": "Aleksandar Vakanski",
      "userId": "07675307153279708378"
     },
     "user_tz": 420
    },
    "id": "qn4BtawLR8hW",
    "outputId": "d69632aa-83e5-4fa7-9a8b-1766b2a65e81"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " * sqlite://\n",
      "1 rows affected.\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "[]"
      ]
     },
     "execution_count": 57,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "%%sql \n",
    "DELETE FROM dependents \n",
    "WHERE dependent_id = 16;"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 703
    },
    "executionInfo": {
     "elapsed": 37,
     "status": "ok",
     "timestamp": 1668546499150,
     "user": {
      "displayName": "Aleksandar Vakanski",
      "userId": "07675307153279708378"
     },
     "user_tz": 420
    },
    "id": "Q9-VzVVnR8jF",
    "outputId": "f4d7e8b3-7717-4a28-96da-888c6100092b"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " * sqlite://\n",
      "Done.\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<table>\n",
       "    <thead>\n",
       "        <tr>\n",
       "            <th>dependent_id</th>\n",
       "            <th>first_name</th>\n",
       "            <th>last_name</th>\n",
       "            <th>relationship</th>\n",
       "            <th>employee_id</th>\n",
       "        </tr>\n",
       "    </thead>\n",
       "    <tbody>\n",
       "        <tr>\n",
       "            <td>1</td>\n",
       "            <td>Penelope</td>\n",
       "            <td>Gietz</td>\n",
       "            <td>Child</td>\n",
       "            <td>206</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>2</td>\n",
       "            <td>Nick</td>\n",
       "            <td>Higgins</td>\n",
       "            <td>Child</td>\n",
       "            <td>205</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>3</td>\n",
       "            <td>Ed</td>\n",
       "            <td>Whalen</td>\n",
       "            <td>Child</td>\n",
       "            <td>200</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>4</td>\n",
       "            <td>Jennifer</td>\n",
       "            <td>King</td>\n",
       "            <td>Child</td>\n",
       "            <td>100</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>5</td>\n",
       "            <td>Johnny</td>\n",
       "            <td>Kochhar</td>\n",
       "            <td>Child</td>\n",
       "            <td>101</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>6</td>\n",
       "            <td>Bette</td>\n",
       "            <td>De Haan</td>\n",
       "            <td>Child</td>\n",
       "            <td>102</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>7</td>\n",
       "            <td>Grace</td>\n",
       "            <td>Faviet</td>\n",
       "            <td>Child</td>\n",
       "            <td>109</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>8</td>\n",
       "            <td>Matthew</td>\n",
       "            <td>Chen</td>\n",
       "            <td>Child</td>\n",
       "            <td>110</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>9</td>\n",
       "            <td>Joe</td>\n",
       "            <td>Sciarra</td>\n",
       "            <td>Child</td>\n",
       "            <td>111</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>10</td>\n",
       "            <td>Christian</td>\n",
       "            <td>Urman</td>\n",
       "            <td>Child</td>\n",
       "            <td>112</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>11</td>\n",
       "            <td>Zero</td>\n",
       "            <td>Popp</td>\n",
       "            <td>Child</td>\n",
       "            <td>113</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>12</td>\n",
       "            <td>Karl</td>\n",
       "            <td>Greenberg</td>\n",
       "            <td>Child</td>\n",
       "            <td>108</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>13</td>\n",
       "            <td>Uma</td>\n",
       "            <td>Mavris</td>\n",
       "            <td>Child</td>\n",
       "            <td>203</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>14</td>\n",
       "            <td>Vivien</td>\n",
       "            <td>Hunold</td>\n",
       "            <td>Child</td>\n",
       "            <td>103</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>15</td>\n",
       "            <td>Cuba</td>\n",
       "            <td>Ernst</td>\n",
       "            <td>Child</td>\n",
       "            <td>104</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>17</td>\n",
       "            <td>Helen</td>\n",
       "            <td>Pataballa</td>\n",
       "            <td>Child</td>\n",
       "            <td>106</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>18</td>\n",
       "            <td>Dan</td>\n",
       "            <td>Lorentz</td>\n",
       "            <td>Child</td>\n",
       "            <td>107</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>19</td>\n",
       "            <td>Bob</td>\n",
       "            <td>Hartstein</td>\n",
       "            <td>Child</td>\n",
       "            <td>201</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>20</td>\n",
       "            <td>Lucille</td>\n",
       "            <td>Fay</td>\n",
       "            <td>Child</td>\n",
       "            <td>202</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>21</td>\n",
       "            <td>Kirsten</td>\n",
       "            <td>Baer</td>\n",
       "            <td>Child</td>\n",
       "            <td>204</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>22</td>\n",
       "            <td>Elvis</td>\n",
       "            <td>Khoo</td>\n",
       "            <td>Child</td>\n",
       "            <td>115</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>23</td>\n",
       "            <td>Sandra</td>\n",
       "            <td>Baida</td>\n",
       "            <td>Child</td>\n",
       "            <td>116</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>24</td>\n",
       "            <td>Cameron</td>\n",
       "            <td>Tobias</td>\n",
       "            <td>Child</td>\n",
       "            <td>117</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>25</td>\n",
       "            <td>Kevin</td>\n",
       "            <td>Himuro</td>\n",
       "            <td>Child</td>\n",
       "            <td>118</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>26</td>\n",
       "            <td>Rip</td>\n",
       "            <td>Colmenares</td>\n",
       "            <td>Child</td>\n",
       "            <td>119</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>27</td>\n",
       "            <td>Julia</td>\n",
       "            <td>Raphaely</td>\n",
       "            <td>Child</td>\n",
       "            <td>114</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>28</td>\n",
       "            <td>Woody</td>\n",
       "            <td>Russell</td>\n",
       "            <td>Child</td>\n",
       "            <td>145</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>29</td>\n",
       "            <td>Alec</td>\n",
       "            <td>Partners</td>\n",
       "            <td>Child</td>\n",
       "            <td>146</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>30</td>\n",
       "            <td>Sandra</td>\n",
       "            <td>Taylor</td>\n",
       "            <td>Child</td>\n",
       "            <td>176</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>31</td>\n",
       "            <td>Dustin</td>\n",
       "            <td>Johnson</td>\n",
       "            <td>Child</td>\n",
       "            <td>178</td>\n",
       "        </tr>\n",
       "    </tbody>\n",
       "</table>"
      ],
      "text/plain": [
       "[(1, 'Penelope', 'Gietz', 'Child', 206),\n",
       " (2, 'Nick', 'Higgins', 'Child', 205),\n",
       " (3, 'Ed', 'Whalen', 'Child', 200),\n",
       " (4, 'Jennifer', 'King', 'Child', 100),\n",
       " (5, 'Johnny', 'Kochhar', 'Child', 101),\n",
       " (6, 'Bette', 'De Haan', 'Child', 102),\n",
       " (7, 'Grace', 'Faviet', 'Child', 109),\n",
       " (8, 'Matthew', 'Chen', 'Child', 110),\n",
       " (9, 'Joe', 'Sciarra', 'Child', 111),\n",
       " (10, 'Christian', 'Urman', 'Child', 112),\n",
       " (11, 'Zero', 'Popp', 'Child', 113),\n",
       " (12, 'Karl', 'Greenberg', 'Child', 108),\n",
       " (13, 'Uma', 'Mavris', 'Child', 203),\n",
       " (14, 'Vivien', 'Hunold', 'Child', 103),\n",
       " (15, 'Cuba', 'Ernst', 'Child', 104),\n",
       " (17, 'Helen', 'Pataballa', 'Child', 106),\n",
       " (18, 'Dan', 'Lorentz', 'Child', 107),\n",
       " (19, 'Bob', 'Hartstein', 'Child', 201),\n",
       " (20, 'Lucille', 'Fay', 'Child', 202),\n",
       " (21, 'Kirsten', 'Baer', 'Child', 204),\n",
       " (22, 'Elvis', 'Khoo', 'Child', 115),\n",
       " (23, 'Sandra', 'Baida', 'Child', 116),\n",
       " (24, 'Cameron', 'Tobias', 'Child', 117),\n",
       " (25, 'Kevin', 'Himuro', 'Child', 118),\n",
       " (26, 'Rip', 'Colmenares', 'Child', 119),\n",
       " (27, 'Julia', 'Raphaely', 'Child', 114),\n",
       " (28, 'Woody', 'Russell', 'Child', 145),\n",
       " (29, 'Alec', 'Partners', 'Child', 146),\n",
       " (30, 'Sandra', 'Taylor', 'Child', 176),\n",
       " (31, 'Dustin', 'Johnson', 'Child', 178)]"
      ]
     },
     "execution_count": 58,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# verify the changes\n",
    "\n",
    "%sql SELECT * FROM dependents"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "OODNmYu4WuW5"
   },
   "source": [
    "## 10.13 Working with Tables <a name='10.13-working-with-tables'></a>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "pS0QOM6wWzZv"
   },
   "source": [
    "In subsection 10.3 we learned how to use the `CREATE TABLE` statement. Several other related SQL statements for working with tables are described next."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "6pfjgZjccVav"
   },
   "source": [
    "### ALTER TABLE\n",
    "\n",
    "`ALTER TABLE` allows to add new columns in an existing table using `ADD`, remove columns in a table with `DROP`, rename columns with `RENAME`, or modify attributes of a column such as primary key, default value, etc. with `ADD CONSTRAINT` or `DROP CONSTRAINT` and related commands."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Add a Column**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "executionInfo": {
     "elapsed": 33,
     "status": "ok",
     "timestamp": 1668546499150,
     "user": {
      "displayName": "Aleksandar Vakanski",
      "userId": "07675307153279708378"
     },
     "user_tz": 420
    },
    "id": "dffE_UQGR8ld",
    "outputId": "f172bab9-4605-45cb-8ee2-706dc3993eab"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " * sqlite://\n",
      "Done.\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "[]"
      ]
     },
     "execution_count": 59,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "%%sql \n",
    "ALTER TABLE cars \n",
    "ADD mileage INT;"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 242
    },
    "executionInfo": {
     "elapsed": 29,
     "status": "ok",
     "timestamp": 1668546499150,
     "user": {
      "displayName": "Aleksandar Vakanski",
      "userId": "07675307153279708378"
     },
     "user_tz": 420
    },
    "id": "2pnoaLoydBHu",
    "outputId": "f252596e-12d9-466c-b633-aaae79d04f92"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " * sqlite://\n",
      "Done.\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<table>\n",
       "    <thead>\n",
       "        <tr>\n",
       "            <th>id</th>\n",
       "            <th>name</th>\n",
       "            <th>price</th>\n",
       "            <th>mileage</th>\n",
       "        </tr>\n",
       "    </thead>\n",
       "    <tbody>\n",
       "        <tr>\n",
       "            <td>1</td>\n",
       "            <td>Audi</td>\n",
       "            <td>52642</td>\n",
       "            <td>None</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>2</td>\n",
       "            <td>Mercedes</td>\n",
       "            <td>57127</td>\n",
       "            <td>None</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>3</td>\n",
       "            <td>Skoda</td>\n",
       "            <td>9000</td>\n",
       "            <td>None</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>4</td>\n",
       "            <td>Volvo</td>\n",
       "            <td>29000</td>\n",
       "            <td>None</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>5</td>\n",
       "            <td>Bentley</td>\n",
       "            <td>350000</td>\n",
       "            <td>None</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>6</td>\n",
       "            <td>Citroen</td>\n",
       "            <td>21000</td>\n",
       "            <td>None</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>7</td>\n",
       "            <td>Hummer</td>\n",
       "            <td>41400</td>\n",
       "            <td>None</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>8</td>\n",
       "            <td>Volkswagen</td>\n",
       "            <td>21600</td>\n",
       "            <td>None</td>\n",
       "        </tr>\n",
       "    </tbody>\n",
       "</table>"
      ],
      "text/plain": [
       "[(1, 'Audi', 52642, None),\n",
       " (2, 'Mercedes', 57127, None),\n",
       " (3, 'Skoda', 9000, None),\n",
       " (4, 'Volvo', 29000, None),\n",
       " (5, 'Bentley', 350000, None),\n",
       " (6, 'Citroen', 21000, None),\n",
       " (7, 'Hummer', 41400, None),\n",
       " (8, 'Volkswagen', 21600, None)]"
      ]
     },
     "execution_count": 60,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "%sql SELECT * FROM cars"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Remove a Column**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " * sqlite://\n",
      "Done.\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "[]"
      ]
     },
     "execution_count": 61,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "%%sql \n",
    "ALTER TABLE cars \n",
    "DROP price;"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " * sqlite://\n",
      "Done.\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<table>\n",
       "    <thead>\n",
       "        <tr>\n",
       "            <th>id</th>\n",
       "            <th>name</th>\n",
       "            <th>mileage</th>\n",
       "        </tr>\n",
       "    </thead>\n",
       "    <tbody>\n",
       "        <tr>\n",
       "            <td>1</td>\n",
       "            <td>Audi</td>\n",
       "            <td>None</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>2</td>\n",
       "            <td>Mercedes</td>\n",
       "            <td>None</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>3</td>\n",
       "            <td>Skoda</td>\n",
       "            <td>None</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>4</td>\n",
       "            <td>Volvo</td>\n",
       "            <td>None</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>5</td>\n",
       "            <td>Bentley</td>\n",
       "            <td>None</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>6</td>\n",
       "            <td>Citroen</td>\n",
       "            <td>None</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>7</td>\n",
       "            <td>Hummer</td>\n",
       "            <td>None</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>8</td>\n",
       "            <td>Volkswagen</td>\n",
       "            <td>None</td>\n",
       "        </tr>\n",
       "    </tbody>\n",
       "</table>"
      ],
      "text/plain": [
       "[(1, 'Audi', None),\n",
       " (2, 'Mercedes', None),\n",
       " (3, 'Skoda', None),\n",
       " (4, 'Volvo', None),\n",
       " (5, 'Bentley', None),\n",
       " (6, 'Citroen', None),\n",
       " (7, 'Hummer', None),\n",
       " (8, 'Volkswagen', None)]"
      ]
     },
     "execution_count": 62,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# verfiy the change\n",
    "%sql SELECT * FROM cars"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "tags": []
   },
   "source": [
    "**Rename a Column**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " * sqlite://\n",
      "Done.\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "[]"
      ]
     },
     "execution_count": 63,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "%%sql \n",
    "ALTER TABLE cars \n",
    "RENAME mileage TO miles;"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " * sqlite://\n",
      "Done.\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<table>\n",
       "    <thead>\n",
       "        <tr>\n",
       "            <th>id</th>\n",
       "            <th>name</th>\n",
       "            <th>miles</th>\n",
       "        </tr>\n",
       "    </thead>\n",
       "    <tbody>\n",
       "        <tr>\n",
       "            <td>1</td>\n",
       "            <td>Audi</td>\n",
       "            <td>None</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>2</td>\n",
       "            <td>Mercedes</td>\n",
       "            <td>None</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>3</td>\n",
       "            <td>Skoda</td>\n",
       "            <td>None</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>4</td>\n",
       "            <td>Volvo</td>\n",
       "            <td>None</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>5</td>\n",
       "            <td>Bentley</td>\n",
       "            <td>None</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>6</td>\n",
       "            <td>Citroen</td>\n",
       "            <td>None</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>7</td>\n",
       "            <td>Hummer</td>\n",
       "            <td>None</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>8</td>\n",
       "            <td>Volkswagen</td>\n",
       "            <td>None</td>\n",
       "        </tr>\n",
       "    </tbody>\n",
       "</table>"
      ],
      "text/plain": [
       "[(1, 'Audi', None),\n",
       " (2, 'Mercedes', None),\n",
       " (3, 'Skoda', None),\n",
       " (4, 'Volvo', None),\n",
       " (5, 'Bentley', None),\n",
       " (6, 'Citroen', None),\n",
       " (7, 'Hummer', None),\n",
       " (8, 'Volkswagen', None)]"
      ]
     },
     "execution_count": 64,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# verfiy the change\n",
    "%sql SELECT * FROM cars"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Rename a Table**"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Similarly, `ALTER TABLE` can be used to rename a table, as in the following example. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " * sqlite://\n",
      "Done.\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "[]"
      ]
     },
     "execution_count": 65,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "%%sql \n",
    "ALTER TABLE writer\n",
    "RENAME TO authors;"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " * sqlite://\n",
      "Done.\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<table>\n",
       "    <thead>\n",
       "        <tr>\n",
       "            <th>name</th>\n",
       "        </tr>\n",
       "    </thead>\n",
       "    <tbody>\n",
       "        <tr>\n",
       "            <td>cars</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>authors</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>regions</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>sqlite_sequence</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>countries</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>locations</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>departments</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>jobs</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>employees</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>dependents</td>\n",
       "        </tr>\n",
       "    </tbody>\n",
       "</table>"
      ],
      "text/plain": [
       "[('cars',),\n",
       " ('authors',),\n",
       " ('regions',),\n",
       " ('sqlite_sequence',),\n",
       " ('countries',),\n",
       " ('locations',),\n",
       " ('departments',),\n",
       " ('jobs',),\n",
       " ('employees',),\n",
       " ('dependents',)]"
      ]
     },
     "execution_count": 66,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# verfiy the change\n",
    "%sql SELECT name FROM sqlite_master WHERE type='table'"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "VcUkklqeeVaO"
   },
   "source": [
    "### DROP TABLE\n",
    "\n",
    "`DROP TABLE` removes a table from a database.  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "executionInfo": {
     "elapsed": 25,
     "status": "ok",
     "timestamp": 1668546499151,
     "user": {
      "displayName": "Aleksandar Vakanski",
      "userId": "07675307153279708378"
     },
     "user_tz": 420
    },
    "id": "9LB_u2XyR8o2",
    "outputId": "d840cf0f-2965-410d-85b2-7dbb4ea6a5ac"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " * sqlite://\n",
      "Done.\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "[]"
      ]
     },
     "execution_count": 67,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "%sql DROP TABLE cars;"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 263
    },
    "executionInfo": {
     "elapsed": 256,
     "status": "ok",
     "timestamp": 1668546499386,
     "user": {
      "displayName": "Aleksandar Vakanski",
      "userId": "07675307153279708378"
     },
     "user_tz": 420
    },
    "id": "y3n8EHhwbIXI",
    "outputId": "1e7d29f0-01eb-4661-e7e9-a634be774cc9"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " * sqlite://\n",
      "Done.\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<table>\n",
       "    <thead>\n",
       "        <tr>\n",
       "            <th>name</th>\n",
       "        </tr>\n",
       "    </thead>\n",
       "    <tbody>\n",
       "        <tr>\n",
       "            <td>authors</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>regions</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>sqlite_sequence</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>countries</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>locations</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>departments</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>jobs</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>employees</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>dependents</td>\n",
       "        </tr>\n",
       "    </tbody>\n",
       "</table>"
      ],
      "text/plain": [
       "[('authors',),\n",
       " ('regions',),\n",
       " ('sqlite_sequence',),\n",
       " ('countries',),\n",
       " ('locations',),\n",
       " ('departments',),\n",
       " ('jobs',),\n",
       " ('employees',),\n",
       " ('dependents',)]"
      ]
     },
     "execution_count": 68,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# verfiy the change\n",
    "%sql SELECT name FROM sqlite_master WHERE type='table'"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "GiYZE-B7j3Ap"
   },
   "source": [
    "## 10.14 Constraints <a name='10.14-constraints'></a>\n",
    "\n",
    "Constraints enforce restrictions on the data that a column can contain or impose other related restrictions. So far, we described some of the constraints used in SQL databases, such as:\n",
    "\n",
    "- `PRIMARY KEY`, defines a primary key for a table.\n",
    "- `NOT NULL`, ensures that values are inserted in a column.\n",
    "- `UNIQUE`, ensures that each row in a column has unique values. \n",
    "\n",
    "### FOREIGN KEY\n",
    "\n",
    "Beside the primary key, some tables also define a **foreign key**. This is a column or a group of columns that enforces a link between the data in two tables. In a foreign key reference, the primary key column of the first table is referenced by the column of the second table, and the column of the second table becomes the foreign key. \n",
    "\n",
    "For instance, when we created the `countries` table (see the inserted code below), we specified that it has `country_id` column as a primary key, and `region_id` column as a foreign key. Therefore, the `region_id` column in `countries` will point to the `region_id` column in the `regions` table. This is indicated in the last line below: `FOREIGN KEY (region_id) REFERENCES regions (region_id)`.\n",
    "\n",
    "    CREATE TABLE countries (\n",
    "        country_id TEXT NOT NULL,\n",
    "        country_name TEXT NOT NULL,\n",
    "        region_id INTEGER NOT NULL,\n",
    "        PRIMARY KEY (country_id ASC),\n",
    "        FOREIGN KEY (region_id) REFERENCES regions (region_id) ON DELETE CASCADE ON UPDATE CASCADE);\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Note also that in the last line `ON DELETE CASCADE` specifies that if a row in the `regions` table is deleted, all rows in the `countries` table that have a matching `region_id` will also be deleted automatically. Analogously, `ON UPDATE CASCADE` specifies that if a `region_id` value in the `regions` table is updated, all corresponding rows in the `countries` table will be updated accordingly. This is useful for maintaining referential integrity between the rows in these two tables.\n",
    "\n",
    "Let's inspect the `countries` table."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 598
    },
    "executionInfo": {
     "elapsed": 19,
     "status": "ok",
     "timestamp": 1668546499386,
     "user": {
      "displayName": "Aleksandar Vakanski",
      "userId": "07675307153279708378"
     },
     "user_tz": 420
    },
    "id": "7CTqIambeqrU",
    "outputId": "ee6a2359-ed15-4107-b04a-ef7371fbba15"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " * sqlite://\n",
      "Done.\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<table>\n",
       "    <thead>\n",
       "        <tr>\n",
       "            <th>country_id</th>\n",
       "            <th>country_name</th>\n",
       "            <th>region_id</th>\n",
       "        </tr>\n",
       "    </thead>\n",
       "    <tbody>\n",
       "        <tr>\n",
       "            <td>AR</td>\n",
       "            <td>Argentina</td>\n",
       "            <td>2</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>AU</td>\n",
       "            <td>Australia</td>\n",
       "            <td>3</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>BE</td>\n",
       "            <td>Belgium</td>\n",
       "            <td>1</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>BR</td>\n",
       "            <td>Brazil</td>\n",
       "            <td>2</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>CA</td>\n",
       "            <td>Canada</td>\n",
       "            <td>2</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>CH</td>\n",
       "            <td>Switzerland</td>\n",
       "            <td>1</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>CN</td>\n",
       "            <td>China</td>\n",
       "            <td>3</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>DE</td>\n",
       "            <td>Germany</td>\n",
       "            <td>1</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>DK</td>\n",
       "            <td>Denmark</td>\n",
       "            <td>1</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>EG</td>\n",
       "            <td>Egypt</td>\n",
       "            <td>4</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>FR</td>\n",
       "            <td>France</td>\n",
       "            <td>1</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>HK</td>\n",
       "            <td>HongKong</td>\n",
       "            <td>3</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>IL</td>\n",
       "            <td>Israel</td>\n",
       "            <td>4</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>IN</td>\n",
       "            <td>India</td>\n",
       "            <td>3</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>IT</td>\n",
       "            <td>Italy</td>\n",
       "            <td>1</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>JP</td>\n",
       "            <td>Japan</td>\n",
       "            <td>3</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>KW</td>\n",
       "            <td>Kuwait</td>\n",
       "            <td>4</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>MX</td>\n",
       "            <td>Mexico</td>\n",
       "            <td>2</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>NG</td>\n",
       "            <td>Nigeria</td>\n",
       "            <td>4</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>NL</td>\n",
       "            <td>Netherlands</td>\n",
       "            <td>1</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>SG</td>\n",
       "            <td>Singapore</td>\n",
       "            <td>3</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>UK</td>\n",
       "            <td>United Kingdom</td>\n",
       "            <td>1</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>US</td>\n",
       "            <td>United States of America</td>\n",
       "            <td>2</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>ZM</td>\n",
       "            <td>Zambia</td>\n",
       "            <td>4</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>ZW</td>\n",
       "            <td>Zimbabwe</td>\n",
       "            <td>4</td>\n",
       "        </tr>\n",
       "    </tbody>\n",
       "</table>"
      ],
      "text/plain": [
       "[('AR', 'Argentina', 2),\n",
       " ('AU', 'Australia', 3),\n",
       " ('BE', 'Belgium', 1),\n",
       " ('BR', 'Brazil', 2),\n",
       " ('CA', 'Canada', 2),\n",
       " ('CH', 'Switzerland', 1),\n",
       " ('CN', 'China', 3),\n",
       " ('DE', 'Germany', 1),\n",
       " ('DK', 'Denmark', 1),\n",
       " ('EG', 'Egypt', 4),\n",
       " ('FR', 'France', 1),\n",
       " ('HK', 'HongKong', 3),\n",
       " ('IL', 'Israel', 4),\n",
       " ('IN', 'India', 3),\n",
       " ('IT', 'Italy', 1),\n",
       " ('JP', 'Japan', 3),\n",
       " ('KW', 'Kuwait', 4),\n",
       " ('MX', 'Mexico', 2),\n",
       " ('NG', 'Nigeria', 4),\n",
       " ('NL', 'Netherlands', 1),\n",
       " ('SG', 'Singapore', 3),\n",
       " ('UK', 'United Kingdom', 1),\n",
       " ('US', 'United States of America', 2),\n",
       " ('ZM', 'Zambia', 4),\n",
       " ('ZW', 'Zimbabwe', 4)]"
      ]
     },
     "execution_count": 69,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "%sql SELECT * FROM countries"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 158
    },
    "executionInfo": {
     "elapsed": 18,
     "status": "ok",
     "timestamp": 1668546499387,
     "user": {
      "displayName": "Aleksandar Vakanski",
      "userId": "07675307153279708378"
     },
     "user_tz": 420
    },
    "id": "-2HzN3dGeqvp",
    "outputId": "3de03f86-3b30-474b-b426-104504091b87"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " * sqlite://\n",
      "Done.\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<table>\n",
       "    <thead>\n",
       "        <tr>\n",
       "            <th>region_id</th>\n",
       "            <th>region_name</th>\n",
       "        </tr>\n",
       "    </thead>\n",
       "    <tbody>\n",
       "        <tr>\n",
       "            <td>1</td>\n",
       "            <td>Europe</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>2</td>\n",
       "            <td>Americas</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>3</td>\n",
       "            <td>Asia</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>4</td>\n",
       "            <td>Middle East and Africa</td>\n",
       "        </tr>\n",
       "    </tbody>\n",
       "</table>"
      ],
      "text/plain": [
       "[(1, 'Europe'), (2, 'Americas'), (3, 'Asia'), (4, 'Middle East and Africa')]"
      ]
     },
     "execution_count": 70,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "%sql SELECT * FROM regions"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "As we mentioned in the section on joining tables, we can use the foreign key column in a table to link to other tables. In the above example, the `region_id` column establishes a relationship between the `countries` table and the `regions` table, where` countries.region_id` must match an existing value in `regions.region_id`."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "1fMWL_AqqZeV"
   },
   "source": [
    "## 10.15 Subqueries <a name='10.15-subqueries'></a>\n",
    "\n",
    "A *subquery* is a query that is nested inside another query, such as `SELECT`. \n",
    "\n",
    "For instance, the following cell retrieves employees in the departments that have a `location_id=1700`. \n",
    "\n",
    "The query placed inside the parentheses is a subquery. It is also known as an *inner query* or *inner select*. The query that contains the subquery is called an *outer query* or an *outer select*.\n",
    "\n",
    "To execute the query, the database system first has to execute the subquery and retrieve the departments with a `location_id` of 1700, and afterward it has to execute the outer query."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 451
    },
    "executionInfo": {
     "elapsed": 16,
     "status": "ok",
     "timestamp": 1668546499388,
     "user": {
      "displayName": "Aleksandar Vakanski",
      "userId": "07675307153279708378"
     },
     "user_tz": 420
    },
    "id": "e3I_hOSPeqxU",
    "outputId": "8f810ab5-fbdf-465d-bf5d-118b80ef6034"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " * sqlite://\n",
      "Done.\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<table>\n",
       "    <thead>\n",
       "        <tr>\n",
       "            <th>employee_id</th>\n",
       "            <th>first_name</th>\n",
       "            <th>last_name</th>\n",
       "        </tr>\n",
       "    </thead>\n",
       "    <tbody>\n",
       "        <tr>\n",
       "            <td>115</td>\n",
       "            <td>Alexander</td>\n",
       "            <td>Khoo</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>109</td>\n",
       "            <td>Daniel</td>\n",
       "            <td>Faviet</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>114</td>\n",
       "            <td>Den</td>\n",
       "            <td>Raphaely</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>118</td>\n",
       "            <td>Guy</td>\n",
       "            <td>Himuro</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>111</td>\n",
       "            <td>Ismael</td>\n",
       "            <td>Sciarra</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>200</td>\n",
       "            <td>Jennifer</td>\n",
       "            <td>Whalen</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>110</td>\n",
       "            <td>John</td>\n",
       "            <td>Chen</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>112</td>\n",
       "            <td>Jose Manuel</td>\n",
       "            <td>Urman</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>119</td>\n",
       "            <td>Karen</td>\n",
       "            <td>Colmenares</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>102</td>\n",
       "            <td>Lex</td>\n",
       "            <td>De Haan</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>113</td>\n",
       "            <td>Luis</td>\n",
       "            <td>Popp</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>108</td>\n",
       "            <td>Nancy</td>\n",
       "            <td>Greenberg</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>101</td>\n",
       "            <td>Neena</td>\n",
       "            <td>Kochhar</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>205</td>\n",
       "            <td>Shelley</td>\n",
       "            <td>Higgins</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>116</td>\n",
       "            <td>Shelli</td>\n",
       "            <td>Baida</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>117</td>\n",
       "            <td>Sigal</td>\n",
       "            <td>Tobias</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>100</td>\n",
       "            <td>Steven</td>\n",
       "            <td>King</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>206</td>\n",
       "            <td>William</td>\n",
       "            <td>Gietz</td>\n",
       "        </tr>\n",
       "    </tbody>\n",
       "</table>"
      ],
      "text/plain": [
       "[(115, 'Alexander', 'Khoo'),\n",
       " (109, 'Daniel', 'Faviet'),\n",
       " (114, 'Den', 'Raphaely'),\n",
       " (118, 'Guy', 'Himuro'),\n",
       " (111, 'Ismael', 'Sciarra'),\n",
       " (200, 'Jennifer', 'Whalen'),\n",
       " (110, 'John', 'Chen'),\n",
       " (112, 'Jose Manuel', 'Urman'),\n",
       " (119, 'Karen', 'Colmenares'),\n",
       " (102, 'Lex', 'De Haan'),\n",
       " (113, 'Luis', 'Popp'),\n",
       " (108, 'Nancy', 'Greenberg'),\n",
       " (101, 'Neena', 'Kochhar'),\n",
       " (205, 'Shelley', 'Higgins'),\n",
       " (116, 'Shelli', 'Baida'),\n",
       " (117, 'Sigal', 'Tobias'),\n",
       " (100, 'Steven', 'King'),\n",
       " (206, 'William', 'Gietz')]"
      ]
     },
     "execution_count": 71,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "%%sql\n",
    "SELECT \n",
    "    employee_id, first_name, last_name \n",
    "FROM \n",
    "    employees \n",
    "WHERE department_id IN \n",
    "    (SELECT department_id FROM departments \n",
    "        WHERE location_id = 1700) \n",
    "ORDER BY first_name , last_name;"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The next code finds the employee who has the highest salary."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 72,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " * sqlite://\n",
      "Done.\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<table>\n",
       "    <thead>\n",
       "        <tr>\n",
       "            <th>employee_id</th>\n",
       "            <th>first_name</th>\n",
       "            <th>last_name</th>\n",
       "            <th>salary</th>\n",
       "        </tr>\n",
       "    </thead>\n",
       "    <tbody>\n",
       "        <tr>\n",
       "            <td>100</td>\n",
       "            <td>Steven</td>\n",
       "            <td>King</td>\n",
       "            <td>24000.0</td>\n",
       "        </tr>\n",
       "    </tbody>\n",
       "</table>"
      ],
      "text/plain": [
       "[(100, 'Steven', 'King', 24000.0)]"
      ]
     },
     "execution_count": 72,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "%%sql\n",
    "SELECT \n",
    "    employee_id, first_name, last_name, salary\n",
    "FROM\n",
    "    employees\n",
    "WHERE salary = \n",
    "    (SELECT MAX(salary) FROM employees)\n",
    "ORDER BY first_name , last_name;"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "E.g., find all employees who salaries are greater than the average salary of all employees."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 73,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " * sqlite://\n",
      "Done.\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<table>\n",
       "    <thead>\n",
       "        <tr>\n",
       "            <th>employee_id</th>\n",
       "            <th>first_name</th>\n",
       "            <th>last_name</th>\n",
       "            <th>salary</th>\n",
       "        </tr>\n",
       "    </thead>\n",
       "    <tbody>\n",
       "        <tr>\n",
       "            <td>100</td>\n",
       "            <td>Steven</td>\n",
       "            <td>King</td>\n",
       "            <td>24000.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>101</td>\n",
       "            <td>Neena</td>\n",
       "            <td>Kochhar</td>\n",
       "            <td>17000.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>102</td>\n",
       "            <td>Lex</td>\n",
       "            <td>De Haan</td>\n",
       "            <td>17000.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>103</td>\n",
       "            <td>Alexander</td>\n",
       "            <td>Hunold</td>\n",
       "            <td>9000.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>108</td>\n",
       "            <td>Nancy</td>\n",
       "            <td>Greenberg</td>\n",
       "            <td>12000.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>109</td>\n",
       "            <td>Daniel</td>\n",
       "            <td>Faviet</td>\n",
       "            <td>9000.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>110</td>\n",
       "            <td>John</td>\n",
       "            <td>Chen</td>\n",
       "            <td>8200.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>114</td>\n",
       "            <td>Den</td>\n",
       "            <td>Raphaely</td>\n",
       "            <td>11000.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>121</td>\n",
       "            <td>Adam</td>\n",
       "            <td>Fripp</td>\n",
       "            <td>8200.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>145</td>\n",
       "            <td>John</td>\n",
       "            <td>Russell</td>\n",
       "            <td>14000.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>146</td>\n",
       "            <td>Karen</td>\n",
       "            <td>Partners</td>\n",
       "            <td>13500.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>176</td>\n",
       "            <td>Jonathon</td>\n",
       "            <td>Taylor</td>\n",
       "            <td>8600.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>177</td>\n",
       "            <td>Jack</td>\n",
       "            <td>Livingston</td>\n",
       "            <td>8400.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>201</td>\n",
       "            <td>Michael</td>\n",
       "            <td>Hartstein</td>\n",
       "            <td>13000.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>204</td>\n",
       "            <td>Hermann</td>\n",
       "            <td>Baer</td>\n",
       "            <td>10000.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>205</td>\n",
       "            <td>Shelley</td>\n",
       "            <td>Higgins</td>\n",
       "            <td>12000.0</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>206</td>\n",
       "            <td>William</td>\n",
       "            <td>Gietz</td>\n",
       "            <td>8300.0</td>\n",
       "        </tr>\n",
       "    </tbody>\n",
       "</table>"
      ],
      "text/plain": [
       "[(100, 'Steven', 'King', 24000.0),\n",
       " (101, 'Neena', 'Kochhar', 17000.0),\n",
       " (102, 'Lex', 'De Haan', 17000.0),\n",
       " (103, 'Alexander', 'Hunold', 9000.0),\n",
       " (108, 'Nancy', 'Greenberg', 12000.0),\n",
       " (109, 'Daniel', 'Faviet', 9000.0),\n",
       " (110, 'John', 'Chen', 8200.0),\n",
       " (114, 'Den', 'Raphaely', 11000.0),\n",
       " (121, 'Adam', 'Fripp', 8200.0),\n",
       " (145, 'John', 'Russell', 14000.0),\n",
       " (146, 'Karen', 'Partners', 13500.0),\n",
       " (176, 'Jonathon', 'Taylor', 8600.0),\n",
       " (177, 'Jack', 'Livingston', 8400.0),\n",
       " (201, 'Michael', 'Hartstein', 13000.0),\n",
       " (204, 'Hermann', 'Baer', 10000.0),\n",
       " (205, 'Shelley', 'Higgins', 12000.0),\n",
       " (206, 'William', 'Gietz', 8300.0)]"
      ]
     },
     "execution_count": 73,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "%%sql\n",
    "SELECT \n",
    "    employee_id, first_name, last_name, salary\n",
    "FROM\n",
    "    employees\n",
    "WHERE\n",
    "    salary > \n",
    "    (SELECT AVG(salary) FROM employees);       "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "74DCdk9oeZWU"
   },
   "source": [
    "## 10.16 Connect to an Existing Database <a name='10.16-connect-to-an-existing-database'></a>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "90R-3ze3ecuY"
   },
   "source": [
    "Recall again that when we created new tables in section 10.3 or a new database in section 10.4, we used `sqlite://` to connect to the tables or to the database. This syntax is used to specify an **in-memory** table or database, that is, it indicates that we want to work with tables or databases that exist only in the memory of our local machine. This syntax uses two forward slashes `//` after `sqlite:`.\n",
    "\n",
    "To connect to an existing database that is stored in a local directory of our computer, we will use the syntax `sqlite:///relative_database_path`, where `relative_database_path` specifies the **relative path** to the local directory where the SQL database is stored. This syntax uses three forward slashes `///` after `sqlite:`.\n",
    "\n",
    "Similarly, we can connect to an existing database that is stored in a directory of our computer by using the **absolute path** to the database with the syntax `sqlite:////absolute_database_path`. This syntax uses four forward slashes `////` after `sqlite:`.\n",
    "\n",
    "In the following cell, we used `sqlite:///data/EssentialSQL.db` to initialize the connection to the database `EssentialSQL.db` which is located in the `data` subdirectory in the current working directory.  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 74,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 36
    },
    "executionInfo": {
     "elapsed": 459,
     "status": "ok",
     "timestamp": 1668546516311,
     "user": {
      "displayName": "Aleksandar Vakanski",
      "userId": "07675307153279708378"
     },
     "user_tz": 420
    },
    "id": "PjvC53LzKAA7",
    "outputId": "99fd3213-304a-4abf-db31-a2ac31ed130c"
   },
   "outputs": [],
   "source": [
    "%sql sqlite:///data/EssentialSQL.db"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "By0Hflsnig19"
   },
   "source": [
    "Note again that there are three forward slashes after `sqlite:`, since we provided a relative path to the database.\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "zeCNSm3L5tWs"
   },
   "source": [
    "We can inspect the tables in the database `EssentialSQL.db` in the following cell."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 75,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 657
    },
    "executionInfo": {
     "elapsed": 639,
     "status": "ok",
     "timestamp": 1668546516947,
     "user": {
      "displayName": "Aleksandar Vakanski",
      "userId": "07675307153279708378"
     },
     "user_tz": 420
    },
    "id": "i13EiAJ95mhL",
    "outputId": "e0981d5f-79cd-4e7a-e02e-07e49c9c4be2"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "   sqlite://\n",
      " * sqlite:///data/EssentialSQL.db\n",
      "Done.\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<table>\n",
       "    <thead>\n",
       "        <tr>\n",
       "            <th>name</th>\n",
       "        </tr>\n",
       "    </thead>\n",
       "    <tbody>\n",
       "        <tr>\n",
       "            <td>Customers</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>Shippers</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>Employees</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>Orders</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>OrderDetails</td>\n",
       "        </tr>\n",
       "    </tbody>\n",
       "</table>"
      ],
      "text/plain": [
       "[('Customers',), ('Shippers',), ('Employees',), ('Orders',), ('OrderDetails',)]"
      ]
     },
     "execution_count": 75,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "%sql SELECT name FROM sqlite_master WHERE type='table'"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "And we can inspect the data in the table `Customers`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 76,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "   sqlite://\n",
      " * sqlite:///data/EssentialSQL.db\n",
      "Done.\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<table>\n",
       "    <thead>\n",
       "        <tr>\n",
       "            <th>CustomerID</th>\n",
       "            <th>CompanyName</th>\n",
       "            <th>ContactName</th>\n",
       "            <th>ContactTitle</th>\n",
       "            <th>Address</th>\n",
       "            <th>City</th>\n",
       "            <th>State</th>\n",
       "        </tr>\n",
       "    </thead>\n",
       "    <tbody>\n",
       "        <tr>\n",
       "            <td>1</td>\n",
       "            <td>Deerfield Tile</td>\n",
       "            <td>Dick Terrcotta</td>\n",
       "            <td>Owner</td>\n",
       "            <td>450 Village Street</td>\n",
       "            <td>Deerfield</td>\n",
       "            <td>IL</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>2</td>\n",
       "            <td>Sagebrush Carpet</td>\n",
       "            <td>Barbara Berber</td>\n",
       "            <td>Director of Installations</td>\n",
       "            <td>10 Industrial Drive</td>\n",
       "            <td>El Paso</td>\n",
       "            <td>TX</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>3</td>\n",
       "            <td>Floor Co.</td>\n",
       "            <td>Jim Wood</td>\n",
       "            <td>Installer</td>\n",
       "            <td>34218 Private Lane</td>\n",
       "            <td>Monclair</td>\n",
       "            <td>NJ</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>4</td>\n",
       "            <td>Main Tile and Bath</td>\n",
       "            <td>Toni Faucet</td>\n",
       "            <td>Owner</td>\n",
       "            <td>Suite 23, Henry Building</td>\n",
       "            <td>Orlando</td>\n",
       "            <td>FL</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <td>5</td>\n",
       "            <td>Slots Carpet</td>\n",
       "            <td>Jack Diamond III</td>\n",
       "            <td>Purchaser</td>\n",
       "            <td>3024 Jackpot Drive</td>\n",
       "            <td>Las Vegas</td>\n",
       "            <td>NV</td>\n",
       "        </tr>\n",
       "    </tbody>\n",
       "</table>"
      ],
      "text/plain": [
       "[(1, 'Deerfield Tile', 'Dick Terrcotta', 'Owner', '450 Village Street', 'Deerfield', 'IL'),\n",
       " (2, 'Sagebrush Carpet', 'Barbara Berber', 'Director of Installations', '10 Industrial Drive', 'El Paso', 'TX'),\n",
       " (3, 'Floor Co.', 'Jim Wood', 'Installer', '34218 Private Lane', 'Monclair', 'NJ'),\n",
       " (4, 'Main Tile and Bath', 'Toni Faucet', 'Owner', 'Suite 23, Henry Building', 'Orlando', 'FL'),\n",
       " (5, 'Slots Carpet', 'Jack Diamond III', 'Purchaser', '3024 Jackpot Drive', 'Las Vegas', 'NV')]"
      ]
     },
     "execution_count": 76,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "%sql SELECT * FROM Customers"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "If the database does not exist, SQLite will create a new database with the provided name in the home directory. The following cell will create a new database named `test.db` in the current working directory. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 77,
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "%sql sqlite:///test.db"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "vweobvFVe4RB"
   },
   "source": [
    "<a name='references'></a>\n",
    "\n",
    "## References\n",
    "\n",
    "1. SQL Tutorial, available at [https://www.sqltutorial.org/](https://www.sqltutorial.org/).\n",
    "2. Practice SQL with SQLite and Jupyter Notebook, by Chonghua Yin, available at [https://github.com/royalosyin/Practice-SQL-with-SQLite-and-Jupyter-Notebook](https://github.com/royalosyin/Practice-SQL-with-SQLite-and-Jupyter-Notebook).\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "bDbzcXmWe4RB"
   },
   "source": [
    "[BACK TO TOP](#top)"
   ]
  }
 ],
 "metadata": {
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  "gpuClass": "premium",
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   "display_name": "Python 3 (ipykernel)",
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