Pandas Tutorial.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "U7CPLLTABoDF"
   },
   "source": [
    "### Python Pandas Tutorial"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 208
    },
    "colab_type": "code",
    "executionInfo": {
     "elapsed": 1556,
     "status": "ok",
     "timestamp": 1564932395902,
     "user": {
      "displayName": "Krzysztof Bruszewski",
      "photoUrl": "https://lh4.googleusercontent.com/-uV0-wDJ-R2g/AAAAAAAAAAI/AAAAAAAALRA/TW0TOh0OXuo/s64/photo.jpg",
      "userId": "11139975063881261812"
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     "user_tz": -120
    },
    "id": "Pfue5O_oBoYV",
    "outputId": "6704ea76-3f66-476e-8a10-05aa48410c72"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0    1.0\n",
      "1    3.0\n",
      "2    5.0\n",
      "3    NaN\n",
      "4    6.0\n",
      "5    8.0\n",
      "dtype: float64\n",
      "0    0\n",
      "1    1\n",
      "2    4\n",
      "Name: Squares, dtype: int32\n"
     ]
    }
   ],
   "source": [
    "import warnings\n",
    "warnings.filterwarnings(\"ignore\")\n",
    "\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "from IPython.display import display\n",
    "\n",
    "series_list = pd.Series([1, 3, 5, np.nan, 6, 8])\n",
    "series_np = pd.Series(np.array([0, 1, 4, 9, 16, 25]), name='Squares')\n",
    "\n",
    "print(series_list)\n",
    "print(series_np[:3])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>apples</th>\n",
       "      <th>oranges</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>3</td>\n",
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       "      <th>2</th>\n",
       "      <td>0</td>\n",
       "      <td>7</td>\n",
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       "      <th>3</th>\n",
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       "      <td>2</td>\n",
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      ],
      "text/plain": [
       "   apples  oranges\n",
       "0       3        0\n",
       "1       2        3\n",
       "2       0        7\n",
       "3       1        2"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "data = {\n",
    "    'apples': [3, 2, 0, 1], \n",
    "    'oranges': [0, 3, 7, 2]\n",
    "}\n",
    "\n",
    "purchases = pd.DataFrame(data)\n",
    "display(purchases)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
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       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>apples</th>\n",
       "      <th>oranges</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>June</th>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Robert</th>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Lily</th>\n",
       "      <td>0</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>David</th>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
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       "</table>\n",
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      ],
      "text/plain": [
       "        apples  oranges\n",
       "June         3        0\n",
       "Robert       2        3\n",
       "Lily         0        7\n",
       "David        1        2"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "purchases = pd.DataFrame(data, index=['June', 'Robert', 'Lily', 'David'])\n",
    "display(purchases)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "apples     3\n",
       "oranges    0\n",
       "Name: June, dtype: int64"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "purchases.loc['June']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
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      "text/plain": [
       "Empty DataFrame\n",
       "Columns: []\n",
       "Index: []"
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       "      <th></th>\n",
       "      <th>Name</th>\n",
       "      <th>Age</th>\n",
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       "      <td>Alex</td>\n",
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       "      <td>Bob</td>\n",
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      "text/plain": [
       "     Name   Age\n",
       "0    Alex  10.0\n",
       "1     Bob  12.0\n",
       "2  Clarke  13.0"
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       "      <td>Tom</td>\n",
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       "      <td>Jack</td>\n",
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       "      <td>Steve</td>\n",
       "      <td>29.0</td>\n",
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       "      <td>Ricky</td>\n",
       "      <td>42.0</td>\n",
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      "text/plain": [
       "    Name   Age\n",
       "0    Tom  28.0\n",
       "1   Jack  34.0\n",
       "2  Steve  29.0\n",
       "3  Ricky  42.0"
      ]
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   ],
   "source": [
    "df = pd.DataFrame()\n",
    "display(df)\n",
    "\n",
    "data = [['Alex',10],['Bob',12],['Clarke',13]]\n",
    "df = pd.DataFrame(data,columns=['Name','Age'],dtype=float)\n",
    "display(df)\n",
    "\n",
    "data = {'Name':['Tom', 'Jack', 'Steve', 'Ricky'],'Age':[28,34,29,42]}\n",
    "df = pd.DataFrame(data,dtype=float)\n",
    "display(df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
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       "      <td>Tom</td>\n",
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       "      <td>Ricky</td>\n",
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      "text/plain": [
       "    Name\n",
       "0    Tom\n",
       "1   Jack\n",
       "2  Steve\n",
       "3  Ricky"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "col = pd.DataFrame(df['Name'])\n",
    "display(col)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
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      "text/plain": [
       "    Name   Age\n",
       "0    Tom  28.0\n",
       "2  Steve  29.0\n",
       "1   Jack  34.0\n",
       "3  Ricky  42.0"
      ]
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       "         1\n",
       "Name  Jack\n",
       "Age     34"
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       "      <td>Ricky</td>\n",
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       "          3\n",
       "Name  Ricky\n",
       "Age      42"
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   ],
   "source": [
    "df = df.sort_values(by='Age')\n",
    "display(df)\n",
    "\n",
    "row = pd.DataFrame(df.iloc[2])\n",
    "display(row)\n",
    "\n",
    "row = pd.DataFrame(df.loc[3])\n",
    "display(row)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th>a</th>\n",
       "      <td>2.255886</td>\n",
       "      <td>3.070715</td>\n",
       "      <td>0.196333</td>\n",
       "      <td>-0.881413</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>b</th>\n",
       "      <td>-1.837882</td>\n",
       "      <td>-0.861416</td>\n",
       "      <td>-1.008404</td>\n",
       "      <td>1.371812</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>c</th>\n",
       "      <td>0.549241</td>\n",
       "      <td>-0.118438</td>\n",
       "      <td>0.521802</td>\n",
       "      <td>-0.610682</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>d</th>\n",
       "      <td>0.404846</td>\n",
       "      <td>-0.450172</td>\n",
       "      <td>-1.157401</td>\n",
       "      <td>0.400450</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>e</th>\n",
       "      <td>-0.517218</td>\n",
       "      <td>0.289338</td>\n",
       "      <td>-1.560531</td>\n",
       "      <td>-0.900231</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>f</th>\n",
       "      <td>0.264137</td>\n",
       "      <td>1.950847</td>\n",
       "      <td>0.084668</td>\n",
       "      <td>-0.083794</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>g</th>\n",
       "      <td>-1.247032</td>\n",
       "      <td>0.585988</td>\n",
       "      <td>-0.102587</td>\n",
       "      <td>1.431847</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>h</th>\n",
       "      <td>0.415488</td>\n",
       "      <td>0.021810</td>\n",
       "      <td>0.579152</td>\n",
       "      <td>-0.628987</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          A         B         C         D\n",
       "a  2.255886  3.070715  0.196333 -0.881413\n",
       "b -1.837882 -0.861416 -1.008404  1.371812\n",
       "c  0.549241 -0.118438  0.521802 -0.610682\n",
       "d  0.404846 -0.450172 -1.157401  0.400450\n",
       "e -0.517218  0.289338 -1.560531 -0.900231\n",
       "f  0.264137  1.950847  0.084668 -0.083794\n",
       "g -1.247032  0.585988 -0.102587  1.431847\n",
       "h  0.415488  0.021810  0.579152 -0.628987"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#.loc() - Label based\n",
    "#.iloc() - Integer based\n",
    "df = pd.DataFrame(np.random.randn(8, 4),\n",
    "index = ['a','b','c','d','e','f','g','h'], columns = ['A', 'B', 'C', 'D'])\n",
    "display(df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "\n",
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       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>A</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>a</th>\n",
       "      <td>2.255886</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>b</th>\n",
       "      <td>-1.837882</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>c</th>\n",
       "      <td>0.549241</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>d</th>\n",
       "      <td>0.404846</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>e</th>\n",
       "      <td>-0.517218</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>f</th>\n",
       "      <td>0.264137</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>g</th>\n",
       "      <td>-1.247032</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>h</th>\n",
       "      <td>0.415488</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          A\n",
       "a  2.255886\n",
       "b -1.837882\n",
       "c  0.549241\n",
       "d  0.404846\n",
       "e -0.517218\n",
       "f  0.264137\n",
       "g -1.247032\n",
       "h  0.415488"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#select all rows for a specific column\n",
    "col = pd.DataFrame(df.loc[:,'A'])\n",
    "display(col)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>A</th>\n",
       "      <th>C</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>a</th>\n",
       "      <td>2.255886</td>\n",
       "      <td>0.196333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>b</th>\n",
       "      <td>-1.837882</td>\n",
       "      <td>-1.008404</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>c</th>\n",
       "      <td>0.549241</td>\n",
       "      <td>0.521802</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>d</th>\n",
       "      <td>0.404846</td>\n",
       "      <td>-1.157401</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>e</th>\n",
       "      <td>-0.517218</td>\n",
       "      <td>-1.560531</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>f</th>\n",
       "      <td>0.264137</td>\n",
       "      <td>0.084668</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>g</th>\n",
       "      <td>-1.247032</td>\n",
       "      <td>-0.102587</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>h</th>\n",
       "      <td>0.415488</td>\n",
       "      <td>0.579152</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          A         C\n",
       "a  2.255886  0.196333\n",
       "b -1.837882 -1.008404\n",
       "c  0.549241  0.521802\n",
       "d  0.404846 -1.157401\n",
       "e -0.517218 -1.560531\n",
       "f  0.264137  0.084668\n",
       "g -1.247032 -0.102587\n",
       "h  0.415488  0.579152"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Select all rows for multiple columns, say list[]\n",
    "cols = pd.DataFrame(df.loc[:,['A','C']])\n",
    "display(cols)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "    .dataframe tbody tr th:only-of-type {\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
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       "\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
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       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>A</th>\n",
       "      <th>C</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>a</th>\n",
       "      <td>2.255886</td>\n",
       "      <td>0.196333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>b</th>\n",
       "      <td>-1.837882</td>\n",
       "      <td>-1.008404</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>f</th>\n",
       "      <td>0.264137</td>\n",
       "      <td>0.084668</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>h</th>\n",
       "      <td>0.415488</td>\n",
       "      <td>0.579152</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          A         C\n",
       "a  2.255886  0.196333\n",
       "b -1.837882 -1.008404\n",
       "f  0.264137  0.084668\n",
       "h  0.415488  0.579152"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Select few rows for multiple columns, say list[]\n",
    "cols_rows = pd.DataFrame(df.loc[['a','b','f','h'],['A','C']])\n",
    "display(cols_rows)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "      <th>C</th>\n",
       "      <th>D</th>\n",
       "    </tr>\n",
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       "  <tbody>\n",
       "    <tr>\n",
       "      <th>a</th>\n",
       "      <td>2.255886</td>\n",
       "      <td>3.070715</td>\n",
       "      <td>0.196333</td>\n",
       "      <td>-0.881413</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>b</th>\n",
       "      <td>-1.837882</td>\n",
       "      <td>-0.861416</td>\n",
       "      <td>-1.008404</td>\n",
       "      <td>1.371812</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>c</th>\n",
       "      <td>0.549241</td>\n",
       "      <td>-0.118438</td>\n",
       "      <td>0.521802</td>\n",
       "      <td>-0.610682</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>d</th>\n",
       "      <td>0.404846</td>\n",
       "      <td>-0.450172</td>\n",
       "      <td>-1.157401</td>\n",
       "      <td>0.400450</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>e</th>\n",
       "      <td>-0.517218</td>\n",
       "      <td>0.289338</td>\n",
       "      <td>-1.560531</td>\n",
       "      <td>-0.900231</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>f</th>\n",
       "      <td>0.264137</td>\n",
       "      <td>1.950847</td>\n",
       "      <td>0.084668</td>\n",
       "      <td>-0.083794</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>g</th>\n",
       "      <td>-1.247032</td>\n",
       "      <td>0.585988</td>\n",
       "      <td>-0.102587</td>\n",
       "      <td>1.431847</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>h</th>\n",
       "      <td>0.415488</td>\n",
       "      <td>0.021810</td>\n",
       "      <td>0.579152</td>\n",
       "      <td>-0.628987</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          A         B         C         D\n",
       "a  2.255886  3.070715  0.196333 -0.881413\n",
       "b -1.837882 -0.861416 -1.008404  1.371812\n",
       "c  0.549241 -0.118438  0.521802 -0.610682\n",
       "d  0.404846 -0.450172 -1.157401  0.400450\n",
       "e -0.517218  0.289338 -1.560531 -0.900231\n",
       "f  0.264137  1.950847  0.084668 -0.083794\n",
       "g -1.247032  0.585988 -0.102587  1.431847\n",
       "h  0.415488  0.021810  0.579152 -0.628987"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Select range of rows for all columns\n",
    "rows = pd.DataFrame(df.loc['a':'h'])\n",
    "display(rows)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
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       "      <th>C</th>\n",
       "      <th>D</th>\n",
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       "  <tbody>\n",
       "    <tr>\n",
       "      <th>a</th>\n",
       "      <td>2.255886</td>\n",
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       "      <td>-0.881413</td>\n",
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       "    <tr>\n",
       "      <th>b</th>\n",
       "      <td>-1.837882</td>\n",
       "      <td>-0.861416</td>\n",
       "      <td>-1.008404</td>\n",
       "      <td>1.371812</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>c</th>\n",
       "      <td>0.549241</td>\n",
       "      <td>-0.118438</td>\n",
       "      <td>0.521802</td>\n",
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       "    </tr>\n",
       "    <tr>\n",
       "      <th>d</th>\n",
       "      <td>0.404846</td>\n",
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      ],
      "text/plain": [
       "          A         B         C         D\n",
       "a  2.255886  3.070715  0.196333 -0.881413\n",
       "b -1.837882 -0.861416 -1.008404  1.371812\n",
       "c  0.549241 -0.118438  0.521802 -0.610682\n",
       "d  0.404846 -0.450172 -1.157401  0.400450"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# select all rows for a specific column\n",
    "rows = pd.DataFrame(df.iloc[:4])\n",
    "display(rows)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "          A         B         C         D\n",
       "a  2.255886  3.070715  0.196333 -0.881413"
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     "metadata": {},
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       "          A         B         C         D\n",
       "a  2.255886  3.070715  0.196333 -0.881413\n",
       "b -1.837882 -0.861416 -1.008404  1.371812\n",
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       "          C         D\n",
       "b -1.008404  1.371812\n",
       "c  0.521802 -0.610682\n",
       "d -1.157401  0.400450\n",
       "e -1.560531 -0.900231"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#.iloc() - Integer based\n",
    "# Integer slicing\n",
    "rows1 = pd.DataFrame(df.iloc[:1])\n",
    "rows4 = pd.DataFrame(df.iloc[:4])\n",
    "rows5 = pd.DataFrame(df.iloc[1:5, 2:4])\n",
    "display(rows1)\n",
    "display(rows4)\n",
    "display(rows5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>B</th>\n",
       "      <th>D</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>b</th>\n",
       "      <td>-0.861416</td>\n",
       "      <td>1.371812</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>d</th>\n",
       "      <td>-0.450172</td>\n",
       "      <td>0.400450</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>f</th>\n",
       "      <td>1.950847</td>\n",
       "      <td>-0.083794</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          B         D\n",
       "b -0.861416  1.371812\n",
       "d -0.450172  0.400450\n",
       "f  1.950847 -0.083794"
      ]
     },
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>A</th>\n",
       "      <th>B</th>\n",
       "      <th>C</th>\n",
       "      <th>D</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>b</th>\n",
       "      <td>-1.837882</td>\n",
       "      <td>-0.861416</td>\n",
       "      <td>-1.008404</td>\n",
       "      <td>1.371812</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>c</th>\n",
       "      <td>0.549241</td>\n",
       "      <td>-0.118438</td>\n",
       "      <td>0.521802</td>\n",
       "      <td>-0.610682</td>\n",
       "    </tr>\n",
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       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          A         B         C         D\n",
       "b -1.837882 -0.861416 -1.008404  1.371812\n",
       "c  0.549241 -0.118438  0.521802 -0.610682"
      ]
     },
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    },
    {
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       "      <th>C</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>a</th>\n",
       "      <td>3.070715</td>\n",
       "      <td>0.196333</td>\n",
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       "    <tr>\n",
       "      <th>b</th>\n",
       "      <td>-0.861416</td>\n",
       "      <td>-1.008404</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>c</th>\n",
       "      <td>-0.118438</td>\n",
       "      <td>0.521802</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>d</th>\n",
       "      <td>-0.450172</td>\n",
       "      <td>-1.157401</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>e</th>\n",
       "      <td>0.289338</td>\n",
       "      <td>-1.560531</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>f</th>\n",
       "      <td>1.950847</td>\n",
       "      <td>0.084668</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>g</th>\n",
       "      <td>0.585988</td>\n",
       "      <td>-0.102587</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>h</th>\n",
       "      <td>0.021810</td>\n",
       "      <td>0.579152</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          B         C\n",
       "a  3.070715  0.196333\n",
       "b -0.861416 -1.008404\n",
       "c -0.118438  0.521802\n",
       "d -0.450172 -1.157401\n",
       "e  0.289338 -1.560531\n",
       "f  1.950847  0.084668\n",
       "g  0.585988 -0.102587\n",
       "h  0.021810  0.579152"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Slicing through list of values\n",
    "cols2 = pd.DataFrame(df.iloc[[1, 3, 5], [1, 3]])\n",
    "cols4 = pd.DataFrame(df.iloc[1:3, :])\n",
    "cols3 = pd.DataFrame(df.iloc[:,1:3])\n",
    "display(cols2)\n",
    "display(cols4)\n",
    "display(cols3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th>A</th>\n",
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       "    <tr>\n",
       "      <th>a</th>\n",
       "      <td>2.255886</td>\n",
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       "    <tr>\n",
       "      <th>b</th>\n",
       "      <td>-1.837882</td>\n",
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       "    <tr>\n",
       "      <th>c</th>\n",
       "      <td>0.549241</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>d</th>\n",
       "      <td>0.404846</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>e</th>\n",
       "      <td>-0.517218</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>f</th>\n",
       "      <td>0.264137</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>g</th>\n",
       "      <td>-1.247032</td>\n",
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       "      <th>h</th>\n",
       "      <td>0.415488</td>\n",
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       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          A\n",
       "a  2.255886\n",
       "b -1.837882\n",
       "c  0.549241\n",
       "d  0.404846\n",
       "e -0.517218\n",
       "f  0.264137\n",
       "g -1.247032\n",
       "h  0.415488"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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       "      <th></th>\n",
       "      <th>A</th>\n",
       "      <th>B</th>\n",
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       "  <tbody>\n",
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       "      <td>2.255886</td>\n",
       "      <td>3.070715</td>\n",
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       "    <tr>\n",
       "      <th>b</th>\n",
       "      <td>-1.837882</td>\n",
       "      <td>-0.861416</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>c</th>\n",
       "      <td>0.549241</td>\n",
       "      <td>-0.118438</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>d</th>\n",
       "      <td>0.404846</td>\n",
       "      <td>-0.450172</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>e</th>\n",
       "      <td>-0.517218</td>\n",
       "      <td>0.289338</td>\n",
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       "    <tr>\n",
       "      <th>f</th>\n",
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       "      <td>1.950847</td>\n",
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       "    <tr>\n",
       "      <th>g</th>\n",
       "      <td>-1.247032</td>\n",
       "      <td>0.585988</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>h</th>\n",
       "      <td>0.415488</td>\n",
       "      <td>0.021810</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          A         B\n",
       "a  2.255886  3.070715\n",
       "b -1.837882 -0.861416\n",
       "c  0.549241 -0.118438\n",
       "d  0.404846 -0.450172\n",
       "e -0.517218  0.289338\n",
       "f  0.264137  1.950847\n",
       "g -1.247032  0.585988\n",
       "h  0.415488  0.021810"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
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       "      <th>A</th>\n",
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       "  <tbody>\n",
       "    <tr>\n",
       "      <th>a</th>\n",
       "      <td>2.255886</td>\n",
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       "      <th>b</th>\n",
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       "      <th>d</th>\n",
       "      <td>0.404846</td>\n",
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       "    <tr>\n",
       "      <th>e</th>\n",
       "      <td>-0.517218</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>f</th>\n",
       "      <td>0.264137</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>g</th>\n",
       "      <td>-1.247032</td>\n",
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       "      <th>h</th>\n",
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      "text/plain": [
       "          A\n",
       "a  2.255886\n",
       "b -1.837882\n",
       "c  0.549241\n",
       "d  0.404846\n",
       "e -0.517218\n",
       "f  0.264137\n",
       "g -1.247032\n",
       "h  0.415488"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "col = pd.DataFrame(df['A'])\n",
    "cols = pd.DataFrame(df[['A','B']])\n",
    "colA = pd.DataFrame(df.A)\n",
    "display(col)\n",
    "display(cols)\n",
    "display(colA)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
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       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Team</th>\n",
       "      <th>Rank</th>\n",
       "      <th>Year</th>\n",
       "      <th>Points</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Riders</td>\n",
       "      <td>1</td>\n",
       "      <td>2014</td>\n",
       "      <td>876</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Riders</td>\n",
       "      <td>2</td>\n",
       "      <td>2015</td>\n",
       "      <td>789</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Devils</td>\n",
       "      <td>2</td>\n",
       "      <td>2014</td>\n",
       "      <td>863</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Devils</td>\n",
       "      <td>3</td>\n",
       "      <td>2015</td>\n",
       "      <td>673</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Kings</td>\n",
       "      <td>3</td>\n",
       "      <td>2014</td>\n",
       "      <td>741</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>kings</td>\n",
       "      <td>4</td>\n",
       "      <td>2015</td>\n",
       "      <td>812</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>Kings</td>\n",
       "      <td>1</td>\n",
       "      <td>2016</td>\n",
       "      <td>756</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>Kings</td>\n",
       "      <td>1</td>\n",
       "      <td>2017</td>\n",
       "      <td>788</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>Riders</td>\n",
       "      <td>2</td>\n",
       "      <td>2016</td>\n",
       "      <td>694</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>Royals</td>\n",
       "      <td>4</td>\n",
       "      <td>2014</td>\n",
       "      <td>701</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>Royals</td>\n",
       "      <td>1</td>\n",
       "      <td>2015</td>\n",
       "      <td>804</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>Riders</td>\n",
       "      <td>2</td>\n",
       "      <td>2017</td>\n",
       "      <td>690</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      Team  Rank  Year  Points\n",
       "0   Riders     1  2014     876\n",
       "1   Riders     2  2015     789\n",
       "2   Devils     2  2014     863\n",
       "3   Devils     3  2015     673\n",
       "4    Kings     3  2014     741\n",
       "5    kings     4  2015     812\n",
       "6    Kings     1  2016     756\n",
       "7    Kings     1  2017     788\n",
       "8   Riders     2  2016     694\n",
       "9   Royals     4  2014     701\n",
       "10  Royals     1  2015     804\n",
       "11  Riders     2  2017     690"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ipl_data = {'Team': ['Riders', 'Riders', 'Devils', 'Devils', 'Kings',\n",
    "   'kings', 'Kings', 'Kings', 'Riders', 'Royals', 'Royals', 'Riders'],\n",
    "   'Rank': [1, 2, 2, 3, 3,4 ,1 ,1,2 , 4,1,2],\n",
    "   'Year': [2014,2015,2014,2015,2014,2015,2016,2017,2016,2014,2015,2017],\n",
    "   'Points':[876,789,863,673,741,812,756,788,694,701,804,690]}\n",
    "df = pd.DataFrame(ipl_data)\n",
    "display(df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{'Devils': [2, 3], 'Kings': [4, 6, 7], 'Riders': [0, 1, 8, 11], 'Royals': [9, 10], 'kings': [5]}\n",
      "{('Devils', 2014): [2], ('Devils', 2015): [3], ('Kings', 2014): [4], ('Kings', 2016): [6], ('Kings', 2017): [7], ('Riders', 2014): [0], ('Riders', 2015): [1], ('Riders', 2016): [8], ('Riders', 2017): [11], ('Royals', 2014): [9], ('Royals', 2015): [10], ('kings', 2015): [5]}\n"
     ]
    }
   ],
   "source": [
    "print(df.groupby('Team').groups)\n",
    "print(df.groupby(['Team','Year']).groups)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Team</th>\n",
       "      <th>Rank</th>\n",
       "      <th>Year</th>\n",
       "      <th>Points</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Riders</td>\n",
       "      <td>1</td>\n",
       "      <td>2014</td>\n",
       "      <td>876</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Devils</td>\n",
       "      <td>2</td>\n",
       "      <td>2014</td>\n",
       "      <td>863</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Kings</td>\n",
       "      <td>3</td>\n",
       "      <td>2014</td>\n",
       "      <td>741</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>Royals</td>\n",
       "      <td>4</td>\n",
       "      <td>2014</td>\n",
       "      <td>701</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     Team  Rank  Year  Points\n",
       "0  Riders     1  2014     876\n",
       "2  Devils     2  2014     863\n",
       "4   Kings     3  2014     741\n",
       "9  Royals     4  2014     701"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "grouped = df.groupby('Year')\n",
    "display(grouped.get_group(2014))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Points</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Year</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2014</th>\n",
       "      <td>795.25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015</th>\n",
       "      <td>769.50</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016</th>\n",
       "      <td>725.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017</th>\n",
       "      <td>739.00</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      Points\n",
       "Year        \n",
       "2014  795.25\n",
       "2015  769.50\n",
       "2016  725.00\n",
       "2017  739.00"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "grouped = df.groupby('Year')\n",
    "mean = pd.DataFrame(grouped['Points'].agg(np.mean))\n",
    "display(mean)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
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       "\n",
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       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Team</th>\n",
       "      <th>Year</th>\n",
       "      <th>Points</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Devils</td>\n",
       "      <td>2014</td>\n",
       "      <td>863</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Devils</td>\n",
       "      <td>2015</td>\n",
       "      <td>673</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Kings</td>\n",
       "      <td>2014</td>\n",
       "      <td>741</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Kings</td>\n",
       "      <td>2016</td>\n",
       "      <td>756</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Kings</td>\n",
       "      <td>2017</td>\n",
       "      <td>788</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Riders</td>\n",
       "      <td>2014</td>\n",
       "      <td>876</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>Riders</td>\n",
       "      <td>2015</td>\n",
       "      <td>789</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>Riders</td>\n",
       "      <td>2016</td>\n",
       "      <td>694</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>Riders</td>\n",
       "      <td>2017</td>\n",
       "      <td>690</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>Royals</td>\n",
       "      <td>2014</td>\n",
       "      <td>701</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>Royals</td>\n",
       "      <td>2015</td>\n",
       "      <td>804</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>kings</td>\n",
       "      <td>2015</td>\n",
       "      <td>812</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      Team  Year  Points\n",
       "0   Devils  2014     863\n",
       "1   Devils  2015     673\n",
       "2    Kings  2014     741\n",
       "3    Kings  2016     756\n",
       "4    Kings  2017     788\n",
       "5   Riders  2014     876\n",
       "6   Riders  2015     789\n",
       "7   Riders  2016     694\n",
       "8   Riders  2017     690\n",
       "9   Royals  2014     701\n",
       "10  Royals  2015     804\n",
       "11   kings  2015     812"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "grouped = df.groupby(['Team', 'Year'], as_index=False)\n",
    "mean = pd.DataFrame(grouped['Points'].agg(np.mean))\n",
    "display(mean)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>sum</th>\n",
       "      <th>mean</th>\n",
       "      <th>std</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Team</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Devils</th>\n",
       "      <td>1536</td>\n",
       "      <td>768.000000</td>\n",
       "      <td>134.350288</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Kings</th>\n",
       "      <td>2285</td>\n",
       "      <td>761.666667</td>\n",
       "      <td>24.006943</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Riders</th>\n",
       "      <td>3049</td>\n",
       "      <td>762.250000</td>\n",
       "      <td>88.567771</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Royals</th>\n",
       "      <td>1505</td>\n",
       "      <td>752.500000</td>\n",
       "      <td>72.831998</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>kings</th>\n",
       "      <td>812</td>\n",
       "      <td>812.000000</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         sum        mean         std\n",
       "Team                                \n",
       "Devils  1536  768.000000  134.350288\n",
       "Kings   2285  761.666667   24.006943\n",
       "Riders  3049  762.250000   88.567771\n",
       "Royals  1505  752.500000   72.831998\n",
       "kings    812  812.000000         NaN"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "grouped = df.groupby('Team')\n",
    "display(grouped['Points'].agg([np.sum, np.mean, np.std]))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
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       "\n",
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       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Rank</th>\n",
       "      <th>Year</th>\n",
       "      <th>Points</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>-15.000000</td>\n",
       "      <td>-11.618950</td>\n",
       "      <td>12.843272</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>5.000000</td>\n",
       "      <td>-3.872983</td>\n",
       "      <td>3.020286</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>-7.071068</td>\n",
       "      <td>-7.071068</td>\n",
       "      <td>7.071068</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>7.071068</td>\n",
       "      <td>7.071068</td>\n",
       "      <td>-7.071068</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>11.547005</td>\n",
       "      <td>-10.910895</td>\n",
       "      <td>-8.608621</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>-5.773503</td>\n",
       "      <td>2.182179</td>\n",
       "      <td>-2.360428</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>-5.773503</td>\n",
       "      <td>8.728716</td>\n",
       "      <td>10.969049</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>5.000000</td>\n",
       "      <td>3.872983</td>\n",
       "      <td>-7.705963</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>7.071068</td>\n",
       "      <td>-7.071068</td>\n",
       "      <td>-7.071068</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>-7.071068</td>\n",
       "      <td>7.071068</td>\n",
       "      <td>7.071068</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>5.000000</td>\n",
       "      <td>11.618950</td>\n",
       "      <td>-8.157595</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         Rank       Year     Points\n",
       "0  -15.000000 -11.618950  12.843272\n",
       "1    5.000000  -3.872983   3.020286\n",
       "2   -7.071068  -7.071068   7.071068\n",
       "3    7.071068   7.071068  -7.071068\n",
       "4   11.547005 -10.910895  -8.608621\n",
       "5         NaN        NaN        NaN\n",
       "6   -5.773503   2.182179  -2.360428\n",
       "7   -5.773503   8.728716  10.969049\n",
       "8    5.000000   3.872983  -7.705963\n",
       "9    7.071068  -7.071068  -7.071068\n",
       "10  -7.071068   7.071068   7.071068\n",
       "11   5.000000  11.618950  -8.157595"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "grouped = df.groupby('Team')\n",
    "score = lambda x: (x - x.mean()) / x.std()*10\n",
    "display(grouped.transform(score))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
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       "\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>A</th>\n",
       "      <th>B</th>\n",
       "      <th>C</th>\n",
       "      <th>D</th>\n",
       "      <th>E</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>foo</td>\n",
       "      <td>one</td>\n",
       "      <td>small</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>foo</td>\n",
       "      <td>one</td>\n",
       "      <td>large</td>\n",
       "      <td>2</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>foo</td>\n",
       "      <td>one</td>\n",
       "      <td>large</td>\n",
       "      <td>2</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>foo</td>\n",
       "      <td>two</td>\n",
       "      <td>small</td>\n",
       "      <td>3</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>foo</td>\n",
       "      <td>two</td>\n",
       "      <td>small</td>\n",
       "      <td>3</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>bar</td>\n",
       "      <td>one</td>\n",
       "      <td>large</td>\n",
       "      <td>4</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>bar</td>\n",
       "      <td>one</td>\n",
       "      <td>small</td>\n",
       "      <td>5</td>\n",
       "      <td>8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>bar</td>\n",
       "      <td>two</td>\n",
       "      <td>small</td>\n",
       "      <td>6</td>\n",
       "      <td>9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>bar</td>\n",
       "      <td>two</td>\n",
       "      <td>large</td>\n",
       "      <td>7</td>\n",
       "      <td>9</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     A    B      C  D  E\n",
       "0  foo  one  small  1  2\n",
       "1  foo  one  large  2  4\n",
       "2  foo  one  large  2  5\n",
       "3  foo  two  small  3  5\n",
       "4  foo  two  small  3  6\n",
       "5  bar  one  large  4  6\n",
       "6  bar  one  small  5  8\n",
       "7  bar  two  small  6  9\n",
       "8  bar  two  large  7  9"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df = pd.DataFrame({\"A\": [\"foo\", \"foo\", \"foo\", \"foo\", \"foo\",\n",
    "                         \"bar\", \"bar\", \"bar\", \"bar\"],\n",
    "                   \"B\": [\"one\", \"one\", \"one\", \"two\", \"two\",\n",
    "                         \"one\", \"one\", \"two\", \"two\"],\n",
    "                   \"C\": [\"small\", \"large\", \"large\", \"small\",\n",
    "                         \"small\", \"large\", \"small\", \"small\",\n",
    "                         \"large\"],\n",
    "                   \"D\": [1, 2, 2, 3, 3, 4, 5, 6, 7],\n",
    "                   \"E\": [2, 4, 5, 5, 6, 6, 8, 9, 9]})\n",
    "\n",
    "display(df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>C</th>\n",
       "      <th>large</th>\n",
       "      <th>small</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>A</th>\n",
       "      <th>B</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">bar</th>\n",
       "      <th>one</th>\n",
       "      <td>4.0</td>\n",
       "      <td>5.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>two</th>\n",
       "      <td>7.0</td>\n",
       "      <td>6.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">foo</th>\n",
       "      <th>one</th>\n",
       "      <td>4.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>two</th>\n",
       "      <td>NaN</td>\n",
       "      <td>6.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "C        large  small\n",
       "A   B                \n",
       "bar one    4.0    5.0\n",
       "    two    7.0    6.0\n",
       "foo one    4.0    1.0\n",
       "    two    NaN    6.0"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "table = pd.pivot_table(df, values='D', index=['A', 'B'],\n",
    "                    columns=['C'], aggfunc=np.sum)\n",
    "\n",
    "display(table)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "    .dataframe tbody tr th:only-of-type {\n",
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       "      <th></th>\n",
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       "      <th>large</th>\n",
       "      <th>small</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>A</th>\n",
       "      <th>B</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">bar</th>\n",
       "      <th>one</th>\n",
       "      <td>4</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>two</th>\n",
       "      <td>7</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">foo</th>\n",
       "      <th>one</th>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>two</th>\n",
       "      <td>0</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "C        large  small\n",
       "A   B                \n",
       "bar one      4      5\n",
       "    two      7      6\n",
       "foo one      4      1\n",
       "    two      0      6"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "table = pd.pivot_table(df, values='D', index=['A', 'B'],\n",
    "                    columns=['C'], aggfunc=np.sum, fill_value=0)\n",
    "\n",
    "display(table)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "\n",
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       "        text-align: right;\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th>D</th>\n",
       "      <th>E</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>A</th>\n",
       "      <th>C</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">bar</th>\n",
       "      <th>large</th>\n",
       "      <td>5.500000</td>\n",
       "      <td>7.500000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>small</th>\n",
       "      <td>5.500000</td>\n",
       "      <td>8.500000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">foo</th>\n",
       "      <th>large</th>\n",
       "      <td>2.000000</td>\n",
       "      <td>4.500000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>small</th>\n",
       "      <td>2.333333</td>\n",
       "      <td>4.333333</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                  D         E\n",
       "A   C                        \n",
       "bar large  5.500000  7.500000\n",
       "    small  5.500000  8.500000\n",
       "foo large  2.000000  4.500000\n",
       "    small  2.333333  4.333333"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "table = pd.pivot_table(df, values=['D', 'E'], index=['A', 'C'],\n",
    "                    aggfunc={'D': np.mean,\n",
    "                             'E': np.mean})\n",
    "\n",
    "display(table)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['sepal_length' 'sepal_width' 'petal_length' 'petal_width' 'species']\n"
     ]
    },
    {
     "data": {
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>sepal_length</th>\n",
       "      <th>sepal_width</th>\n",
       "      <th>petal_length</th>\n",
       "      <th>petal_width</th>\n",
       "      <th>species</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>5.1</td>\n",
       "      <td>3.5</td>\n",
       "      <td>1.4</td>\n",
       "      <td>0.2</td>\n",
       "      <td>setosa</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>4.9</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1.4</td>\n",
       "      <td>0.2</td>\n",
       "      <td>setosa</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>4.7</td>\n",
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       "      <td>1.3</td>\n",
       "      <td>0.2</td>\n",
       "      <td>setosa</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4.6</td>\n",
       "      <td>3.1</td>\n",
       "      <td>1.5</td>\n",
       "      <td>0.2</td>\n",
       "      <td>setosa</td>\n",
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       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5.0</td>\n",
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       "      <td>6.7</td>\n",
       "      <td>3.0</td>\n",
       "      <td>5.2</td>\n",
       "      <td>2.3</td>\n",
       "      <td>virginica</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>146</th>\n",
       "      <td>6.3</td>\n",
       "      <td>2.5</td>\n",
       "      <td>5.0</td>\n",
       "      <td>1.9</td>\n",
       "      <td>virginica</td>\n",
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       "    <tr>\n",
       "      <th>147</th>\n",
       "      <td>6.5</td>\n",
       "      <td>3.0</td>\n",
       "      <td>5.2</td>\n",
       "      <td>2.0</td>\n",
       "      <td>virginica</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>148</th>\n",
       "      <td>6.2</td>\n",
       "      <td>3.4</td>\n",
       "      <td>5.4</td>\n",
       "      <td>2.3</td>\n",
       "      <td>virginica</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>149</th>\n",
       "      <td>5.9</td>\n",
       "      <td>3.0</td>\n",
       "      <td>5.1</td>\n",
       "      <td>1.8</td>\n",
       "      <td>virginica</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>150 rows × 5 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     sepal_length  sepal_width  petal_length  petal_width    species\n",
       "0             5.1          3.5           1.4          0.2     setosa\n",
       "1             4.9          3.0           1.4          0.2     setosa\n",
       "2             4.7          3.2           1.3          0.2     setosa\n",
       "3             4.6          3.1           1.5          0.2     setosa\n",
       "4             5.0          3.6           1.4          0.2     setosa\n",
       "..            ...          ...           ...          ...        ...\n",
       "145           6.7          3.0           5.2          2.3  virginica\n",
       "146           6.3          2.5           5.0          1.9  virginica\n",
       "147           6.5          3.0           5.2          2.0  virginica\n",
       "148           6.2          3.4           5.4          2.3  virginica\n",
       "149           5.9          3.0           5.1          1.8  virginica\n",
       "\n",
       "[150 rows x 5 columns]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "iris = pd.read_excel('iris.xlsx', sheet_name='iris')\n",
    "print(iris.columns.ravel())\n",
    "display(iris)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [],
   "source": [
    "iris.to_json('iris.json', orient='records')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "      <th>sepal_length</th>\n",
       "      <th>sepal_width</th>\n",
       "      <th>petal_length</th>\n",
       "      <th>petal_width</th>\n",
       "      <th>species</th>\n",
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       "      <td>6.7</td>\n",
       "      <td>3.0</td>\n",
       "      <td>5.2</td>\n",
       "      <td>2.3</td>\n",
       "      <td>virginica</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>146</th>\n",
       "      <td>6.3</td>\n",
       "      <td>2.5</td>\n",
       "      <td>5.0</td>\n",
       "      <td>1.9</td>\n",
       "      <td>virginica</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>147</th>\n",
       "      <td>6.5</td>\n",
       "      <td>3.0</td>\n",
       "      <td>5.2</td>\n",
       "      <td>2.0</td>\n",
       "      <td>virginica</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>148</th>\n",
       "      <td>6.2</td>\n",
       "      <td>3.4</td>\n",
       "      <td>5.4</td>\n",
       "      <td>2.3</td>\n",
       "      <td>virginica</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>149</th>\n",
       "      <td>5.9</td>\n",
       "      <td>3.0</td>\n",
       "      <td>5.1</td>\n",
       "      <td>1.8</td>\n",
       "      <td>virginica</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>150 rows × 5 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     sepal_length  sepal_width  petal_length  petal_width    species\n",
       "0             5.1          3.5           1.4          0.2     setosa\n",
       "1             4.9          3.0           1.4          0.2     setosa\n",
       "2             4.7          3.2           1.3          0.2     setosa\n",
       "3             4.6          3.1           1.5          0.2     setosa\n",
       "4             5.0          3.6           1.4          0.2     setosa\n",
       "..            ...          ...           ...          ...        ...\n",
       "145           6.7          3.0           5.2          2.3  virginica\n",
       "146           6.3          2.5           5.0          1.9  virginica\n",
       "147           6.5          3.0           5.2          2.0  virginica\n",
       "148           6.2          3.4           5.4          2.3  virginica\n",
       "149           5.9          3.0           5.1          1.8  virginica\n",
       "\n",
       "[150 rows x 5 columns]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "iris_json = pd.read_json('iris.json')\n",
    "display(iris_json)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
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       "      <th></th>\n",
       "      <th>sepal_length</th>\n",
       "      <th>sepal_width</th>\n",
       "      <th>petal_length</th>\n",
       "      <th>petal_width</th>\n",
       "      <th>species</th>\n",
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       "      <th>50</th>\n",
       "      <td>7.0</td>\n",
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       "      <td>versicolor</td>\n",
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       "    <tr>\n",
       "      <th>52</th>\n",
       "      <td>6.9</td>\n",
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       "      <td>versicolor</td>\n",
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       "    <tr>\n",
       "      <th>58</th>\n",
       "      <td>6.6</td>\n",
       "      <td>2.9</td>\n",
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       "      <td>1.3</td>\n",
       "      <td>versicolor</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>65</th>\n",
       "      <td>6.7</td>\n",
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       "      <td>1.4</td>\n",
       "      <td>versicolor</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75</th>\n",
       "      <td>6.6</td>\n",
       "      <td>3.0</td>\n",
       "      <td>4.4</td>\n",
       "      <td>1.4</td>\n",
       "      <td>versicolor</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>76</th>\n",
       "      <td>6.8</td>\n",
       "      <td>2.8</td>\n",
       "      <td>4.8</td>\n",
       "      <td>1.4</td>\n",
       "      <td>versicolor</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>77</th>\n",
       "      <td>6.7</td>\n",
       "      <td>3.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>1.7</td>\n",
       "      <td>versicolor</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>86</th>\n",
       "      <td>6.7</td>\n",
       "      <td>3.1</td>\n",
       "      <td>4.7</td>\n",
       "      <td>1.5</td>\n",
       "      <td>versicolor</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    sepal_length  sepal_width  petal_length  petal_width     species\n",
       "50           7.0          3.2           4.7          1.4  versicolor\n",
       "52           6.9          3.1           4.9          1.5  versicolor\n",
       "58           6.6          2.9           4.6          1.3  versicolor\n",
       "65           6.7          3.1           4.4          1.4  versicolor\n",
       "75           6.6          3.0           4.4          1.4  versicolor\n",
       "76           6.8          2.8           4.8          1.4  versicolor\n",
       "77           6.7          3.0           5.0          1.7  versicolor\n",
       "86           6.7          3.1           4.7          1.5  versicolor"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "query = iris_json.query(\"species == 'versicolor' & sepal_length > 6.5\")\n",
    "display(query)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
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       "</div>"
      ],
      "text/plain": [
       "    sepal_length  sepal_width  petal_length  petal_width     species\n",
       "43           5.0          3.5           1.6          0.6      setosa\n",
       "57           4.9          2.4           3.3          1.0  versicolor\n",
       "60           5.0          2.0           3.5          1.0  versicolor\n",
       "62           6.0          2.2           4.0          1.0  versicolor\n",
       "67           5.8          2.7           4.1          1.0  versicolor\n",
       "79           5.7          2.6           3.5          1.0  versicolor\n",
       "81           5.5          2.4           3.7          1.0  versicolor\n",
       "93           5.0          2.3           3.3          1.0  versicolor"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "query = iris_json.query(\"species in ['setosa', 'versicolor'] & petal_width > 0.5 & petal_width <= 1\")\n",
    "display(query)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
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       "      <th>key</th>\n",
       "      <th>lvalue</th>\n",
       "      <th>rvalue</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>foo</td>\n",
       "      <td>1</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>foo</td>\n",
       "      <td>1</td>\n",
       "      <td>8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>foo</td>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>foo</td>\n",
       "      <td>5</td>\n",
       "      <td>8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>bar</td>\n",
       "      <td>2</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>baz</td>\n",
       "      <td>3</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   key  lvalue  rvalue\n",
       "0  foo       1       5\n",
       "1  foo       1       8\n",
       "2  foo       5       5\n",
       "3  foo       5       8\n",
       "4  bar       2       6\n",
       "5  baz       3       7"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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       "      <td>7</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   key  lvalue  rvalue\n",
       "0  foo       1       5\n",
       "1  foo       5       5\n",
       "2  foo       1       8\n",
       "3  foo       5       8\n",
       "4  bar       2       6\n",
       "5  baz       3       7"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df1 = pd.DataFrame({'key': ['foo', 'bar', 'baz', 'foo'],\n",
    "                    'lvalue': [1, 2, 3, 5]})\n",
    "df2 = pd.DataFrame({'key': ['foo', 'bar', 'baz', 'foo'],\n",
    "                    'rvalue': [5, 6, 7, 8]})\n",
    "\n",
    "display(df1)\n",
    "display(df2)\n",
    "\n",
    "result = pd.concat([df1, df2])\n",
    "display(result)\n",
    "\n",
    "result = df1.append(df2)\n",
    "display(result)\n",
    "\n",
    "result = pd.concat([df1, df2], ignore_index=True, sort=False)\n",
    "display(result)\n",
    "\n",
    "result = pd.merge(df1, df2, on='key')\n",
    "display(result)\n",
    "\n",
    "result = pd.merge(df1, df2, how='inner', on=['key', 'key'])\n",
    "display(result)\n",
    "\n",
    "result = pd.merge(df1, df2, how='right', on=['key', 'key'])\n",
    "display(result)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 225
    },
    "colab_type": "code",
    "executionInfo": {
     "elapsed": 906,
     "status": "ok",
     "timestamp": 1564904069713,
     "user": {
      "displayName": "Krzysztof Bruszewski",
      "photoUrl": "https://lh4.googleusercontent.com/-uV0-wDJ-R2g/AAAAAAAAAAI/AAAAAAAALRA/TW0TOh0OXuo/s64/photo.jpg",
      "userId": "11139975063881261812"
     },
     "user_tz": -120
    },
    "id": "wsK9plSKMOUD",
    "outputId": "42f1980e-928c-46bf-dcfb-e423f747ecd9"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[RangeIndex(start=0, stop=4, step=1)]\n",
      "False\n",
      "1\n",
      "4\n",
      "[-1.88208986  0.52621279 -1.09531859 -0.62154971]\n",
      "float64\n"
     ]
    },
    {
     "data": {
      "text/html": [
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       "\n",
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       "</style>\n",
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       "      <th></th>\n",
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       "      <th>b</th>\n",
       "      <th>c</th>\n",
       "    </tr>\n",
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       "  <tbody>\n",
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       "      <td>0.054316</td>\n",
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       "    <tr>\n",
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       "      <td>-1.283910</td>\n",
       "      <td>-1.531322</td>\n",
       "      <td>0.838432</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0.650980</td>\n",
       "      <td>-0.169529</td>\n",
       "      <td>-3.839934</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>-0.240341</td>\n",
       "      <td>-1.142895</td>\n",
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       "    </tr>\n",
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       "      <th>4</th>\n",
       "      <td>NaN</td>\n",
       "      <td>0.817178</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          a         b         c\n",
       "0  0.054316  0.154039  0.352609\n",
       "1 -1.283910 -1.531322  0.838432\n",
       "2  0.650980 -0.169529 -3.839934\n",
       "3 -0.240341 -1.142895  0.210291\n",
       "4       NaN  0.817178       NaN"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "s = pd.Series(np.random.randn(4))\n",
    "\n",
    "print(s.axes)\n",
    "print(s.empty)\n",
    "print(s.ndim)\n",
    "print(s.size)\n",
    "print(s.values)\n",
    "print(s.dtypes)\n",
    "\n",
    "a = pd.Series(np.random.randn(4))\n",
    "b = pd.Series(np.random.randn(5))\n",
    "\n",
    "frame = { 'a': a, 'b': b} \n",
    "result = pd.DataFrame(frame) \n",
    "result['c'] = a/b\n",
    "display(result) "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th></th>\n",
       "      <th>a</th>\n",
       "      <th>b</th>\n",
       "      <th>c</th>\n",
       "      <th>d</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0.054316</td>\n",
       "      <td>0.154039</td>\n",
       "      <td>0.352609</td>\n",
       "      <td>-0.282817</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>-1.283910</td>\n",
       "      <td>-1.531322</td>\n",
       "      <td>0.838432</td>\n",
       "      <td>0.295089</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0.650980</td>\n",
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       "      <td>-3.839934</td>\n",
       "      <td>-0.213678</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>-0.240341</td>\n",
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       "      <td>0.210291</td>\n",
       "      <td>4.291930</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>NaN</td>\n",
       "      <td>0.817178</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          a         b         c         d\n",
       "0  0.054316  0.154039  0.352609 -0.282817\n",
       "1 -1.283910 -1.531322  0.838432  0.295089\n",
       "2  0.650980 -0.169529 -3.839934 -0.213678\n",
       "3 -0.240341 -1.142895  0.210291  4.291930\n",
       "4       NaN  0.817178       NaN       NaN"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "result.eval('d = (a - b) / c', inplace=True)\n",
    "display(result) "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<style scoped>\n",
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       "      <th>1</th>\n",
       "      <td>-1.283910</td>\n",
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       "      <th>2</th>\n",
       "      <td>0.650980</td>\n",
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       "      <th>3</th>\n",
       "      <td>-0.240341</td>\n",
       "      <td>-1.142895</td>\n",
       "      <td>0.210291</td>\n",
       "      <td>4.291930</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>NaN</td>\n",
       "      <td>0.817178</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          a         b         c         d  d_max\n",
       "0  0.054316  0.154039  0.352609 -0.282817      0\n",
       "1 -1.283910 -1.531322  0.838432  0.295089      0\n",
       "2  0.650980 -0.169529 -3.839934 -0.213678      0\n",
       "3 -0.240341 -1.142895  0.210291  4.291930      1\n",
       "4       NaN  0.817178       NaN       NaN      0"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "result['d_max'] = np.where(result['d']==max(result['d']), 1, 0)\n",
    "display(result)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 780
    },
    "colab_type": "code",
    "executionInfo": {
     "elapsed": 2504,
     "status": "ok",
     "timestamp": 1564932407521,
     "user": {
      "displayName": "Krzysztof Bruszewski",
      "photoUrl": "https://lh4.googleusercontent.com/-uV0-wDJ-R2g/AAAAAAAAAAI/AAAAAAAALRA/TW0TOh0OXuo/s64/photo.jpg",
      "userId": "11139975063881261812"
     },
     "user_tz": -120
    },
    "id": "BRKn7DrARNYw",
    "outputId": "28e1c189-ca61-4223-cfcd-889866b8de81"
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
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       "\n",
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       "    }\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Name</th>\n",
       "      <th>Age</th>\n",
       "      <th>Rating</th>\n",
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       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Tom</td>\n",
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       "      <td>4.23</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>James</td>\n",
       "      <td>26</td>\n",
       "      <td>3.24</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Ricky</td>\n",
       "      <td>25</td>\n",
       "      <td>3.98</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Vin</td>\n",
       "      <td>23</td>\n",
       "      <td>2.56</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Steve</td>\n",
       "      <td>30</td>\n",
       "      <td>3.20</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Smith</td>\n",
       "      <td>29</td>\n",
       "      <td>4.60</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>Jack</td>\n",
       "      <td>23</td>\n",
       "      <td>3.80</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>Lee</td>\n",
       "      <td>34</td>\n",
       "      <td>3.78</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>David</td>\n",
       "      <td>40</td>\n",
       "      <td>2.98</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>Gasper</td>\n",
       "      <td>30</td>\n",
       "      <td>4.80</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>Betina</td>\n",
       "      <td>51</td>\n",
       "      <td>4.10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>Andres</td>\n",
       "      <td>46</td>\n",
       "      <td>3.65</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      Name  Age  Rating\n",
       "0      Tom   25    4.23\n",
       "1    James   26    3.24\n",
       "2    Ricky   25    3.98\n",
       "3      Vin   23    2.56\n",
       "4    Steve   30    3.20\n",
       "5    Smith   29    4.60\n",
       "6     Jack   23    3.80\n",
       "7      Lee   34    3.78\n",
       "8    David   40    2.98\n",
       "9   Gasper   30    4.80\n",
       "10  Betina   51    4.10\n",
       "11  Andres   46    3.65"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Name\n",
      "Age\n",
      "Rating\n",
      "Name      TomJamesRickyVinSteveSmithJackLeeDavidGasperBe...\n",
      "Age                                                     382\n",
      "Rating                                                44.92\n",
      "dtype: object\n",
      "Age       31.833333\n",
      "Rating     3.743333\n",
      "dtype: float64\n",
      "             Age     Rating\n",
      "count  12.000000  12.000000\n",
      "mean   31.833333   3.743333\n",
      "std     9.232682   0.661628\n",
      "min    23.000000   2.560000\n",
      "25%    25.000000   3.230000\n",
      "50%    29.500000   3.790000\n",
      "75%    35.500000   4.132500\n",
      "max    51.000000   4.800000\n",
      "          Name        Age     Rating\n",
      "count       12  12.000000  12.000000\n",
      "unique      12        NaN        NaN\n",
      "top     Betina        NaN        NaN\n",
      "freq         1        NaN        NaN\n",
      "mean       NaN  31.833333   3.743333\n",
      "std        NaN   9.232682   0.661628\n",
      "min        NaN  23.000000   2.560000\n",
      "25%        NaN  25.000000   3.230000\n",
      "50%        NaN  29.500000   3.790000\n",
      "75%        NaN  35.500000   4.132500\n",
      "max        NaN  51.000000   4.800000\n"
     ]
    }
   ],
   "source": [
    "d = {'Name':pd.Series(['Tom','James','Ricky','Vin','Steve','Smith','Jack',\n",
    "   'Lee','David','Gasper','Betina','Andres']),\n",
    "   'Age':pd.Series([25,26,25,23,30,29,23,34,40,30,51,46]),\n",
    "   'Rating':pd.Series([4.23,3.24,3.98,2.56,3.20,4.6,3.8,3.78,2.98,4.80,4.10,3.65])\n",
    "}\n",
    "\n",
    "df = pd.DataFrame(d)\n",
    "display(df)\n",
    "\n",
    "for col in df:\n",
    "   print(col)\n",
    "\n",
    "print (df.sum())\n",
    "print (df.mean())\n",
    "print (df.describe())\n",
    "print (df.describe(include='all'))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 401
    },
    "colab_type": "code",
    "executionInfo": {
     "elapsed": 2041,
     "status": "ok",
     "timestamp": 1564908098663,
     "user": {
      "displayName": "Krzysztof Bruszewski",
      "photoUrl": "https://lh4.googleusercontent.com/-uV0-wDJ-R2g/AAAAAAAAAAI/AAAAAAAALRA/TW0TOh0OXuo/s64/photo.jpg",
      "userId": "11139975063881261812"
     },
     "user_tz": -120
    },
    "id": "lCPLEPgFkBWk",
    "outputId": "59875eee-f88c-4f01-c03d-c0ae6bf0e18e"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['anagrams', 'anscombe', 'attention', 'brain_networks', 'car_crashes', 'diamonds', 'dots', 'exercise', 'flights', 'fmri', 'gammas', 'geyser', 'iris', 'mpg', 'penguins', 'planets', 'tips', 'titanic']\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>sepal_length</th>\n",
       "      <th>sepal_width</th>\n",
       "      <th>petal_length</th>\n",
       "      <th>petal_width</th>\n",
       "      <th>species</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>5.1</td>\n",
       "      <td>3.5</td>\n",
       "      <td>1.4</td>\n",
       "      <td>0.2</td>\n",
       "      <td>setosa</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>4.9</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1.4</td>\n",
       "      <td>0.2</td>\n",
       "      <td>setosa</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>4.7</td>\n",
       "      <td>3.2</td>\n",
       "      <td>1.3</td>\n",
       "      <td>0.2</td>\n",
       "      <td>setosa</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4.6</td>\n",
       "      <td>3.1</td>\n",
       "      <td>1.5</td>\n",
       "      <td>0.2</td>\n",
       "      <td>setosa</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5.0</td>\n",
       "      <td>3.6</td>\n",
       "      <td>1.4</td>\n",
       "      <td>0.2</td>\n",
       "      <td>setosa</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   sepal_length  sepal_width  petal_length  petal_width species\n",
       "0           5.1          3.5           1.4          0.2  setosa\n",
       "1           4.9          3.0           1.4          0.2  setosa\n",
       "2           4.7          3.2           1.3          0.2  setosa\n",
       "3           4.6          3.1           1.5          0.2  setosa\n",
       "4           5.0          3.6           1.4          0.2  setosa"
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import warnings\n",
    "warnings.filterwarnings(\"ignore\")\n",
    "\n",
    "import seaborn as sns\n",
    "print(sns.get_dataset_names())\n",
    "iris = sns.load_dataset('iris')\n",
    "iris.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>sepal_length</th>\n",
       "      <th>sepal_width</th>\n",
       "      <th>petal_length</th>\n",
       "      <th>petal_width</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>150.000000</td>\n",
       "      <td>150.000000</td>\n",
       "      <td>150.000000</td>\n",
       "      <td>150.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>5.843333</td>\n",
       "      <td>3.057333</td>\n",
       "      <td>3.758000</td>\n",
       "      <td>1.199333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>0.828066</td>\n",
       "      <td>0.435866</td>\n",
       "      <td>1.765298</td>\n",
       "      <td>0.762238</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>4.300000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.100000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>5.100000</td>\n",
       "      <td>2.800000</td>\n",
       "      <td>1.600000</td>\n",
       "      <td>0.300000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>5.800000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>4.350000</td>\n",
       "      <td>1.300000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>6.400000</td>\n",
       "      <td>3.300000</td>\n",
       "      <td>5.100000</td>\n",
       "      <td>1.800000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>7.900000</td>\n",
       "      <td>4.400000</td>\n",
       "      <td>6.900000</td>\n",
       "      <td>2.500000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       sepal_length  sepal_width  petal_length  petal_width\n",
       "count    150.000000   150.000000    150.000000   150.000000\n",
       "mean       5.843333     3.057333      3.758000     1.199333\n",
       "std        0.828066     0.435866      1.765298     0.762238\n",
       "min        4.300000     2.000000      1.000000     0.100000\n",
       "25%        5.100000     2.800000      1.600000     0.300000\n",
       "50%        5.800000     3.000000      4.350000     1.300000\n",
       "75%        6.400000     3.300000      5.100000     1.800000\n",
       "max        7.900000     4.400000      6.900000     2.500000"
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "iris.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Date</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2011-01-01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2011-01-02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2011-01-03</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2011-01-04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2011-01-05</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        Date\n",
       "0 2011-01-01\n",
       "1 2011-01-02\n",
       "2 2011-01-03\n",
       "3 2011-01-04\n",
       "4 2011-01-05"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "start = pd.datetime(2011, 1, 1)\n",
    "end = pd.datetime(2011, 1, 5)\n",
    "date = pd.DataFrame(pd.date_range(start, end))\n",
    "date.columns = ['Date']\n",
    "display(date)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Category</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>a</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>b</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>c</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>a</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  Category\n",
       "0        a\n",
       "1        b\n",
       "2        c\n",
       "3        a"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "s = pd.Series([\"a\",\"b\",\"c\",\"a\"], dtype=\"category\")\n",
    "df = pd.DataFrame(s)\n",
    "df.columns = ['Category']\n",
    "display(df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Category</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>unique</th>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>top</th>\n",
       "      <td>a</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>freq</th>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       Category\n",
       "count         4\n",
       "unique        3\n",
       "top           a\n",
       "freq          2"
      ]
     },
     "execution_count": 42,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.describe()"
   ]
  }
 ],
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   "name": "Pandas Tutorial.ipynb",
   "provenance": [],
   "version": "0.3.2"
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   "language": "python",
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  "language_info": {
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    "version": 3
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   "file_extension": ".py",
   "mimetype": "text/x-python",
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