Practice1-5_Basic_InputDataFrame_KK.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 파이썬 데이터분석 특화 데이터 형태: Pandas\n",
    "\n",
    "- **목적:** Python에서 가장 널리 사용되는 데이터 핸들링 패키지   \n",
    "(https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.html)\n",
    "> - Wes McKinney가 투자운용 회사인 AQR에 재직중이던 2008년 초에 개발됨\n",
    "> - NumPy를 기반으로 개발\n",
    "> - Python을 사용한 데이터 분석 및 관리의 표준으로 없어서는 안될 도구\n",
    "> - Python 기반 데이터 전문가, Kaggle 도전 또는 데이터 프로세스를 자동화가 필요한 사람에게 필수적\n",
    ">> - Series는 1차원의 배열같은 구조의 데이터를 저장하기 위한 Python 데이터 형태\n",
    ">> - DataFrame는 Table형식의 2D 데이터를 저장하기위한 Python 데이터 형태\n",
    ">> - DataFrame은 복수의 Series가 합쳐진 것으로 각 Series는 동일한 자료형을 가짐\n",
    ">> - 데이터에는 여러 행과 열이있을 수 있으며, 각 행은 데이터 샘플이고 각 열은 샘플(행)을 설명하는 변수\n",
    ">> - 일반적으로 Excel 데이터 세트와 유사하나 DataFrames는 누락 된 값을 피하고 행이나 열 사이에 간격과 빈 값이 없음\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Series & DataFrame 생성"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-03-15T06:56:22.330579Z",
     "start_time": "2021-03-15T06:56:21.849864Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0    1\n",
       "1    2\n",
       "2    3\n",
       "3    4\n",
       "4    5\n",
       "dtype: int64"
      ]
     },
     "execution_count": 1,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Series\n",
    "import pandas as pd \n",
    "ds = pd.Series([1,2,3,4,5])\n",
    "ds"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-03-15T06:56:22.345539Z",
     "start_time": "2021-03-15T06:56:22.332574Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([1, 2, 3, 4, 5], dtype=int64)"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ds.values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-03-15T06:56:22.360500Z",
     "start_time": "2021-03-15T06:56:22.347534Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "RangeIndex(start=0, stop=5, step=1)"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ds.index"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-03-15T06:56:22.375459Z",
     "start_time": "2021-03-15T06:56:22.364490Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "a    1\n",
       "b    2\n",
       "c    3\n",
       "d    4\n",
       "e    5\n",
       "dtype: int64"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ds = pd.Series([1,2,3,4,5], index=['a','b','c','d','e'])\n",
    "ds"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-03-15T06:56:22.390418Z",
     "start_time": "2021-03-15T06:56:22.377455Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "3"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ds['c']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-03-15T06:56:22.435302Z",
     "start_time": "2021-03-15T06:56:22.391416Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "a    False\n",
      "b    False\n",
      "c    False\n",
      "d     True\n",
      "e     True\n",
      "dtype: bool\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "d    4\n",
       "e    5\n",
       "dtype: int64"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "print(ds>3)\n",
    "ds[ds>3]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-03-15T06:56:22.450257Z",
     "start_time": "2021-03-15T06:56:22.438291Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "a     2\n",
       "b     4\n",
       "c     6\n",
       "d     8\n",
       "e    10\n",
       "dtype: int64"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Numpy 연산이 Pandas 자료구조에서 적용가능\n",
    "ds*2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-03-15T06:56:22.464902Z",
     "start_time": "2021-03-15T06:56:22.451937Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "a    False\n",
       "b    False\n",
       "c    False\n",
       "d    False\n",
       "e    False\n",
       "dtype: bool"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ds.isnull()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-03-15T06:56:22.479865Z",
     "start_time": "2021-03-15T06:56:22.467896Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "a    True\n",
       "b    True\n",
       "c    True\n",
       "d    True\n",
       "e    True\n",
       "dtype: bool"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ds.notnull()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-03-15T06:56:22.494824Z",
     "start_time": "2021-03-15T06:56:22.483854Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{'column1': [1, 2, 3, 4, 5], 'another_column': ['this', 'column', 'has', 'strings', 'inside!'], 'float_column': [0.1, 0.5, 33, 48, 42.5555], 'binary_column': [True, False, True, True, False]}\n",
      "[1, 2, 3, 4, 5]\n"
     ]
    }
   ],
   "source": [
    "# DataFrame\n",
    "df = {'column1':[1,2,3,4,5],\n",
    "      'another_column':['this', 'column', 'has', 'strings', 'inside!'],\n",
    "      'float_column':[0.1, 0.5, 33, 48, 42.5555],\n",
    "      'binary_column':[True, False, True, True, False]}\n",
    "print(df)\n",
    "print(df['column1'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-03-15T06:56:22.509783Z",
     "start_time": "2021-03-15T06:56:22.496818Z"
    }
   },
   "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",
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       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>column1</th>\n",
       "      <th>another_column</th>\n",
       "      <th>float_column</th>\n",
       "      <th>binary_column</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>this</td>\n",
       "      <td>0.1000</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>column</td>\n",
       "      <td>0.5000</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>has</td>\n",
       "      <td>33.0000</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>strings</td>\n",
       "      <td>48.0000</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>inside!</td>\n",
       "      <td>42.5555</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   column1 another_column  float_column  binary_column\n",
       "0        1           this        0.1000           True\n",
       "1        2         column        0.5000          False\n",
       "2        3            has       33.0000           True\n",
       "3        4        strings       48.0000           True\n",
       "4        5        inside!       42.5555          False"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pd.DataFrame(df)\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-03-15T06:56:22.524742Z",
     "start_time": "2021-03-15T06:56:22.511779Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>column1</th>\n",
       "      <th>another_column</th>\n",
       "      <th>float_column</th>\n",
       "      <th>binary_column</th>\n",
       "      <th>column_test</th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
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       "      <th>0</th>\n",
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       "      <td>this</td>\n",
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       "      <td>True</td>\n",
       "      <td>100</td>\n",
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       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>column</td>\n",
       "      <td>0.5000</td>\n",
       "      <td>False</td>\n",
       "      <td>100</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>has</td>\n",
       "      <td>33.0000</td>\n",
       "      <td>True</td>\n",
       "      <td>100</td>\n",
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       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>strings</td>\n",
       "      <td>48.0000</td>\n",
       "      <td>True</td>\n",
       "      <td>100</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>inside!</td>\n",
       "      <td>42.5555</td>\n",
       "      <td>False</td>\n",
       "      <td>100</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   column1 another_column  float_column  binary_column  column_test\n",
       "0        1           this        0.1000           True          100\n",
       "1        2         column        0.5000          False          100\n",
       "2        3            has       33.0000           True          100\n",
       "3        4        strings       48.0000           True          100\n",
       "4        5        inside!       42.5555          False          100"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['column_test'] = 100\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-03-15T06:56:22.539705Z",
     "start_time": "2021-03-15T06:56:22.526738Z"
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    {
     "data": {
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       "    .dataframe tbody tr th:only-of-type {\n",
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>column1</th>\n",
       "      <th>another_column</th>\n",
       "      <th>float_column</th>\n",
       "      <th>binary_column</th>\n",
       "      <th>column_test</th>\n",
       "      <th>seq_test</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>this</td>\n",
       "      <td>0.1000</td>\n",
       "      <td>True</td>\n",
       "      <td>100</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>column</td>\n",
       "      <td>0.5000</td>\n",
       "      <td>False</td>\n",
       "      <td>100</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>has</td>\n",
       "      <td>33.0000</td>\n",
       "      <td>True</td>\n",
       "      <td>100</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>strings</td>\n",
       "      <td>48.0000</td>\n",
       "      <td>True</td>\n",
       "      <td>100</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>inside!</td>\n",
       "      <td>42.5555</td>\n",
       "      <td>False</td>\n",
       "      <td>100</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   column1 another_column  float_column  binary_column  column_test  seq_test\n",
       "0        1           this        0.1000           True          100         0\n",
       "1        2         column        0.5000          False          100         1\n",
       "2        3            has       33.0000           True          100         2\n",
       "3        4        strings       48.0000           True          100         3\n",
       "4        5        inside!       42.5555          False          100         4"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import numpy as np\n",
    "df['seq_test'] = np.arange(5)\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-03-15T06:56:22.569624Z",
     "start_time": "2021-03-15T06:56:22.541700Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
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       "    }\n",
       "\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>column1</th>\n",
       "      <th>another_column</th>\n",
       "      <th>float_column</th>\n",
       "      <th>binary_column</th>\n",
       "      <th>seq_test</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>this</td>\n",
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       "      <td>True</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>column</td>\n",
       "      <td>0.5000</td>\n",
       "      <td>False</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>has</td>\n",
       "      <td>33.0000</td>\n",
       "      <td>True</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>strings</td>\n",
       "      <td>48.0000</td>\n",
       "      <td>True</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>inside!</td>\n",
       "      <td>42.5555</td>\n",
       "      <td>False</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   column1 another_column  float_column  binary_column  seq_test\n",
       "0        1           this        0.1000           True         0\n",
       "1        2         column        0.5000          False         1\n",
       "2        3            has       33.0000           True         2\n",
       "3        4        strings       48.0000           True         3\n",
       "4        5        inside!       42.5555          False         4"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "del df['column_test']\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-03-15T06:56:22.584584Z",
     "start_time": "2021-03-15T06:56:22.571618Z"
    }
   },
   "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>0</th>\n",
       "      <th>1</th>\n",
       "      <th>2</th>\n",
       "      <th>3</th>\n",
       "      <th>4</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>column1</th>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>4</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>another_column</th>\n",
       "      <td>this</td>\n",
       "      <td>column</td>\n",
       "      <td>has</td>\n",
       "      <td>strings</td>\n",
       "      <td>inside!</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>float_column</th>\n",
       "      <td>0.1</td>\n",
       "      <td>0.5</td>\n",
       "      <td>33</td>\n",
       "      <td>48</td>\n",
       "      <td>42.5555</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>binary_column</th>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>seq_test</th>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                   0       1     2        3        4\n",
       "column1            1       2     3        4        5\n",
       "another_column  this  column   has  strings  inside!\n",
       "float_column     0.1     0.5    33       48  42.5555\n",
       "binary_column   True   False  True     True    False\n",
       "seq_test           0       1     2        3        4"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.T"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-03-15T06:56:22.599542Z",
     "start_time": "2021-03-15T06:56:22.586582Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['column1', 'another_column', 'float_column', 'binary_column',\n",
       "       'seq_test'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-03-15T06:56:22.614509Z",
     "start_time": "2021-03-15T06:56:22.602537Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "RangeIndex(start=0, stop=5, step=1)"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.index"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-03-15T06:56:22.629462Z",
     "start_time": "2021-03-15T06:56:22.617501Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[1, 'this', 0.1, True, 0],\n",
       "       [2, 'column', 0.5, False, 1],\n",
       "       [3, 'has', 33.0, True, 2],\n",
       "       [4, 'strings', 48.0, True, 3],\n",
       "       [5, 'inside!', 42.5555, False, 4]], dtype=object)"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.values"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 실제 데이터 불러오기(from CSV to DataFrame)\n",
    "\n",
    "**1) CSV는 무엇인가?**\n",
    "> - CSV(쉼표 구분 값)파일은 숫자와 텍스트 데이터를 저장하는 일반적인 파일 형식\n",
    "> - Python을 사용하여 CSV 파일을 불러오고 핸들링하고 출력하는 기능은 모든 데이터 과학자 또는 비즈니스 분석가에게 핵심 기술\n",
    "\n",
    "**2) 데이터 위치확인 및 파일입력 방법**\n",
    "> - **절대경로:** \"컴퓨터\" 기준 로딩할 데이터의 폴더위치로 어디서 분석 하든 바뀌지 않을 경로\n",
    ">> - 데이터폴더와 작업공간을 분리시킬 수 있음\n",
    ">> - 데이터위치가 변경되면 코드를 변경해야 함\n",
    ">> - 작업공간이 어디에 있든 실행됨\n",
    "> - **상대경로:** \"작업파일\" 기준 로딩할 데이터의 폴더위치로 분석파일 위치에 따라 바뀔수 있는 경로\n",
    ">> - 데이터폴더와 작업공간을 함께 위치시킴\n",
    ">> - 데이터위치가 변경되어도 코드를 변경할 필요가 없음\n",
    ">> - 데이터를 포함하지 않으면 실행되지 않음\n",
    "\n",
    "**3) 데이터 불러오기**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-03-15T06:56:22.644427Z",
     "start_time": "2021-03-15T06:56:22.631457Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "D:\\DataScience\\Lecture\\[데이터싸이언스]\\Data\\FoodAgricultureOrganization\\Food_Agriculture_Organization_UN_Full.csv\n",
      ".\\Data\\FoodAgricultureOrganization\\Food_Agriculture_Organization_UN_Full.csv\n"
     ]
    }
   ],
   "source": [
    "location_abs = r'D:\\DataScience\\Lecture\\[데이터싸이언스]\\Data\\FoodAgricultureOrganization\\Food_Agriculture_Organization_UN_Full.csv'\n",
    "location_rel = r'.\\Data\\FoodAgricultureOrganization\\Food_Agriculture_Organization_UN_Full.csv'\n",
    "print(location_abs)\n",
    "print(location_rel)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-03-15T06:56:22.823970Z",
     "start_time": "2021-03-15T06:56:22.646420Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "\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>Area Abbreviation</th>\n",
       "      <th>Area Code</th>\n",
       "      <th>Area</th>\n",
       "      <th>Item Code</th>\n",
       "      <th>Item</th>\n",
       "      <th>Element Code</th>\n",
       "      <th>Element</th>\n",
       "      <th>Unit</th>\n",
       "      <th>latitude</th>\n",
       "      <th>longitude</th>\n",
       "      <th>...</th>\n",
       "      <th>Y2004</th>\n",
       "      <th>Y2005</th>\n",
       "      <th>Y2006</th>\n",
       "      <th>Y2007</th>\n",
       "      <th>Y2008</th>\n",
       "      <th>Y2009</th>\n",
       "      <th>Y2010</th>\n",
       "      <th>Y2011</th>\n",
       "      <th>Y2012</th>\n",
       "      <th>Y2013</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>AF</td>\n",
       "      <td>2</td>\n",
       "      <td>Afghanistan</td>\n",
       "      <td>2511</td>\n",
       "      <td>Wheat and products</td>\n",
       "      <td>5142</td>\n",
       "      <td>Food</td>\n",
       "      <td>1000 tonnes</td>\n",
       "      <td>33.94</td>\n",
       "      <td>67.71</td>\n",
       "      <td>...</td>\n",
       "      <td>3249.0</td>\n",
       "      <td>3486.0</td>\n",
       "      <td>3704.0</td>\n",
       "      <td>4164.0</td>\n",
       "      <td>4252.0</td>\n",
       "      <td>4538.0</td>\n",
       "      <td>4605.0</td>\n",
       "      <td>4711.0</td>\n",
       "      <td>4810</td>\n",
       "      <td>4895</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>AF</td>\n",
       "      <td>2</td>\n",
       "      <td>Afghanistan</td>\n",
       "      <td>2805</td>\n",
       "      <td>Rice (Milled Equivalent)</td>\n",
       "      <td>5142</td>\n",
       "      <td>Food</td>\n",
       "      <td>1000 tonnes</td>\n",
       "      <td>33.94</td>\n",
       "      <td>67.71</td>\n",
       "      <td>...</td>\n",
       "      <td>419.0</td>\n",
       "      <td>445.0</td>\n",
       "      <td>546.0</td>\n",
       "      <td>455.0</td>\n",
       "      <td>490.0</td>\n",
       "      <td>415.0</td>\n",
       "      <td>442.0</td>\n",
       "      <td>476.0</td>\n",
       "      <td>425</td>\n",
       "      <td>422</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>AF</td>\n",
       "      <td>2</td>\n",
       "      <td>Afghanistan</td>\n",
       "      <td>2513</td>\n",
       "      <td>Barley and products</td>\n",
       "      <td>5521</td>\n",
       "      <td>Feed</td>\n",
       "      <td>1000 tonnes</td>\n",
       "      <td>33.94</td>\n",
       "      <td>67.71</td>\n",
       "      <td>...</td>\n",
       "      <td>58.0</td>\n",
       "      <td>236.0</td>\n",
       "      <td>262.0</td>\n",
       "      <td>263.0</td>\n",
       "      <td>230.0</td>\n",
       "      <td>379.0</td>\n",
       "      <td>315.0</td>\n",
       "      <td>203.0</td>\n",
       "      <td>367</td>\n",
       "      <td>360</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>AF</td>\n",
       "      <td>2</td>\n",
       "      <td>Afghanistan</td>\n",
       "      <td>2513</td>\n",
       "      <td>Barley and products</td>\n",
       "      <td>5142</td>\n",
       "      <td>Food</td>\n",
       "      <td>1000 tonnes</td>\n",
       "      <td>33.94</td>\n",
       "      <td>67.71</td>\n",
       "      <td>...</td>\n",
       "      <td>185.0</td>\n",
       "      <td>43.0</td>\n",
       "      <td>44.0</td>\n",
       "      <td>48.0</td>\n",
       "      <td>62.0</td>\n",
       "      <td>55.0</td>\n",
       "      <td>60.0</td>\n",
       "      <td>72.0</td>\n",
       "      <td>78</td>\n",
       "      <td>89</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>AF</td>\n",
       "      <td>2</td>\n",
       "      <td>Afghanistan</td>\n",
       "      <td>2514</td>\n",
       "      <td>Maize and products</td>\n",
       "      <td>5521</td>\n",
       "      <td>Feed</td>\n",
       "      <td>1000 tonnes</td>\n",
       "      <td>33.94</td>\n",
       "      <td>67.71</td>\n",
       "      <td>...</td>\n",
       "      <td>120.0</td>\n",
       "      <td>208.0</td>\n",
       "      <td>233.0</td>\n",
       "      <td>249.0</td>\n",
       "      <td>247.0</td>\n",
       "      <td>195.0</td>\n",
       "      <td>178.0</td>\n",
       "      <td>191.0</td>\n",
       "      <td>200</td>\n",
       "      <td>200</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
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       "      <td>...</td>\n",
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       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21472</th>\n",
       "      <td>ZW</td>\n",
       "      <td>181</td>\n",
       "      <td>Zimbabwe</td>\n",
       "      <td>2948</td>\n",
       "      <td>Milk - Excluding Butter</td>\n",
       "      <td>5142</td>\n",
       "      <td>Food</td>\n",
       "      <td>1000 tonnes</td>\n",
       "      <td>-19.02</td>\n",
       "      <td>29.15</td>\n",
       "      <td>...</td>\n",
       "      <td>373.0</td>\n",
       "      <td>357.0</td>\n",
       "      <td>359.0</td>\n",
       "      <td>356.0</td>\n",
       "      <td>341.0</td>\n",
       "      <td>385.0</td>\n",
       "      <td>418.0</td>\n",
       "      <td>457.0</td>\n",
       "      <td>426</td>\n",
       "      <td>451</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21473</th>\n",
       "      <td>ZW</td>\n",
       "      <td>181</td>\n",
       "      <td>Zimbabwe</td>\n",
       "      <td>2960</td>\n",
       "      <td>Fish, Seafood</td>\n",
       "      <td>5521</td>\n",
       "      <td>Feed</td>\n",
       "      <td>1000 tonnes</td>\n",
       "      <td>-19.02</td>\n",
       "      <td>29.15</td>\n",
       "      <td>...</td>\n",
       "      <td>5.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>15.0</td>\n",
       "      <td>15.0</td>\n",
       "      <td>15</td>\n",
       "      <td>15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21474</th>\n",
       "      <td>ZW</td>\n",
       "      <td>181</td>\n",
       "      <td>Zimbabwe</td>\n",
       "      <td>2960</td>\n",
       "      <td>Fish, Seafood</td>\n",
       "      <td>5142</td>\n",
       "      <td>Food</td>\n",
       "      <td>1000 tonnes</td>\n",
       "      <td>-19.02</td>\n",
       "      <td>29.15</td>\n",
       "      <td>...</td>\n",
       "      <td>18.0</td>\n",
       "      <td>14.0</td>\n",
       "      <td>17.0</td>\n",
       "      <td>14.0</td>\n",
       "      <td>15.0</td>\n",
       "      <td>18.0</td>\n",
       "      <td>29.0</td>\n",
       "      <td>40.0</td>\n",
       "      <td>40</td>\n",
       "      <td>40</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21475</th>\n",
       "      <td>ZW</td>\n",
       "      <td>181</td>\n",
       "      <td>Zimbabwe</td>\n",
       "      <td>2961</td>\n",
       "      <td>Aquatic Products, Other</td>\n",
       "      <td>5142</td>\n",
       "      <td>Food</td>\n",
       "      <td>1000 tonnes</td>\n",
       "      <td>-19.02</td>\n",
       "      <td>29.15</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21476</th>\n",
       "      <td>ZW</td>\n",
       "      <td>181</td>\n",
       "      <td>Zimbabwe</td>\n",
       "      <td>2928</td>\n",
       "      <td>Miscellaneous</td>\n",
       "      <td>5142</td>\n",
       "      <td>Food</td>\n",
       "      <td>1000 tonnes</td>\n",
       "      <td>-19.02</td>\n",
       "      <td>29.15</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>21477 rows × 63 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      Area Abbreviation  Area Code         Area  Item Code  \\\n",
       "0                    AF          2  Afghanistan       2511   \n",
       "1                    AF          2  Afghanistan       2805   \n",
       "2                    AF          2  Afghanistan       2513   \n",
       "3                    AF          2  Afghanistan       2513   \n",
       "4                    AF          2  Afghanistan       2514   \n",
       "...                 ...        ...          ...        ...   \n",
       "21472                ZW        181     Zimbabwe       2948   \n",
       "21473                ZW        181     Zimbabwe       2960   \n",
       "21474                ZW        181     Zimbabwe       2960   \n",
       "21475                ZW        181     Zimbabwe       2961   \n",
       "21476                ZW        181     Zimbabwe       2928   \n",
       "\n",
       "                           Item  Element Code Element         Unit  latitude  \\\n",
       "0            Wheat and products          5142    Food  1000 tonnes     33.94   \n",
       "1      Rice (Milled Equivalent)          5142    Food  1000 tonnes     33.94   \n",
       "2           Barley and products          5521    Feed  1000 tonnes     33.94   \n",
       "3           Barley and products          5142    Food  1000 tonnes     33.94   \n",
       "4            Maize and products          5521    Feed  1000 tonnes     33.94   \n",
       "...                         ...           ...     ...          ...       ...   \n",
       "21472   Milk - Excluding Butter          5142    Food  1000 tonnes    -19.02   \n",
       "21473             Fish, Seafood          5521    Feed  1000 tonnes    -19.02   \n",
       "21474             Fish, Seafood          5142    Food  1000 tonnes    -19.02   \n",
       "21475   Aquatic Products, Other          5142    Food  1000 tonnes    -19.02   \n",
       "21476             Miscellaneous          5142    Food  1000 tonnes    -19.02   \n",
       "\n",
       "       longitude  ...   Y2004   Y2005   Y2006   Y2007   Y2008   Y2009   Y2010  \\\n",
       "0          67.71  ...  3249.0  3486.0  3704.0  4164.0  4252.0  4538.0  4605.0   \n",
       "1          67.71  ...   419.0   445.0   546.0   455.0   490.0   415.0   442.0   \n",
       "2          67.71  ...    58.0   236.0   262.0   263.0   230.0   379.0   315.0   \n",
       "3          67.71  ...   185.0    43.0    44.0    48.0    62.0    55.0    60.0   \n",
       "4          67.71  ...   120.0   208.0   233.0   249.0   247.0   195.0   178.0   \n",
       "...          ...  ...     ...     ...     ...     ...     ...     ...     ...   \n",
       "21472      29.15  ...   373.0   357.0   359.0   356.0   341.0   385.0   418.0   \n",
       "21473      29.15  ...     5.0     4.0     9.0     6.0     9.0     5.0    15.0   \n",
       "21474      29.15  ...    18.0    14.0    17.0    14.0    15.0    18.0    29.0   \n",
       "21475      29.15  ...     0.0     0.0     0.0     0.0     0.0     0.0     0.0   \n",
       "21476      29.15  ...     0.0     0.0     0.0     0.0     0.0     0.0     0.0   \n",
       "\n",
       "        Y2011  Y2012  Y2013  \n",
       "0      4711.0   4810   4895  \n",
       "1       476.0    425    422  \n",
       "2       203.0    367    360  \n",
       "3        72.0     78     89  \n",
       "4       191.0    200    200  \n",
       "...       ...    ...    ...  \n",
       "21472   457.0    426    451  \n",
       "21473    15.0     15     15  \n",
       "21474    40.0     40     40  \n",
       "21475     0.0      0      0  \n",
       "21476     0.0      0      0  \n",
       "\n",
       "[21477 rows x 63 columns]"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# File Loading from \"Absolute\" and \"Relative\" paths\n",
    "import pandas as pd\n",
    "\n",
    "df_abs = pd.read_csv(location_abs)\n",
    "df_abs"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-03-15T06:56:23.019421Z",
     "start_time": "2021-03-15T06:56:22.824939Z"
    }
   },
   "outputs": [
    {
     "data": {
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       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
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       "    }\n",
       "\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>Area Abbreviation</th>\n",
       "      <th>Area Code</th>\n",
       "      <th>Area</th>\n",
       "      <th>Item Code</th>\n",
       "      <th>Item</th>\n",
       "      <th>Element Code</th>\n",
       "      <th>Element</th>\n",
       "      <th>Unit</th>\n",
       "      <th>latitude</th>\n",
       "      <th>longitude</th>\n",
       "      <th>...</th>\n",
       "      <th>Y2004</th>\n",
       "      <th>Y2005</th>\n",
       "      <th>Y2006</th>\n",
       "      <th>Y2007</th>\n",
       "      <th>Y2008</th>\n",
       "      <th>Y2009</th>\n",
       "      <th>Y2010</th>\n",
       "      <th>Y2011</th>\n",
       "      <th>Y2012</th>\n",
       "      <th>Y2013</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>AF</td>\n",
       "      <td>2</td>\n",
       "      <td>Afghanistan</td>\n",
       "      <td>2511</td>\n",
       "      <td>Wheat and products</td>\n",
       "      <td>5142</td>\n",
       "      <td>Food</td>\n",
       "      <td>1000 tonnes</td>\n",
       "      <td>33.94</td>\n",
       "      <td>67.71</td>\n",
       "      <td>...</td>\n",
       "      <td>3249.0</td>\n",
       "      <td>3486.0</td>\n",
       "      <td>3704.0</td>\n",
       "      <td>4164.0</td>\n",
       "      <td>4252.0</td>\n",
       "      <td>4538.0</td>\n",
       "      <td>4605.0</td>\n",
       "      <td>4711.0</td>\n",
       "      <td>4810</td>\n",
       "      <td>4895</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>AF</td>\n",
       "      <td>2</td>\n",
       "      <td>Afghanistan</td>\n",
       "      <td>2805</td>\n",
       "      <td>Rice (Milled Equivalent)</td>\n",
       "      <td>5142</td>\n",
       "      <td>Food</td>\n",
       "      <td>1000 tonnes</td>\n",
       "      <td>33.94</td>\n",
       "      <td>67.71</td>\n",
       "      <td>...</td>\n",
       "      <td>419.0</td>\n",
       "      <td>445.0</td>\n",
       "      <td>546.0</td>\n",
       "      <td>455.0</td>\n",
       "      <td>490.0</td>\n",
       "      <td>415.0</td>\n",
       "      <td>442.0</td>\n",
       "      <td>476.0</td>\n",
       "      <td>425</td>\n",
       "      <td>422</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>AF</td>\n",
       "      <td>2</td>\n",
       "      <td>Afghanistan</td>\n",
       "      <td>2513</td>\n",
       "      <td>Barley and products</td>\n",
       "      <td>5521</td>\n",
       "      <td>Feed</td>\n",
       "      <td>1000 tonnes</td>\n",
       "      <td>33.94</td>\n",
       "      <td>67.71</td>\n",
       "      <td>...</td>\n",
       "      <td>58.0</td>\n",
       "      <td>236.0</td>\n",
       "      <td>262.0</td>\n",
       "      <td>263.0</td>\n",
       "      <td>230.0</td>\n",
       "      <td>379.0</td>\n",
       "      <td>315.0</td>\n",
       "      <td>203.0</td>\n",
       "      <td>367</td>\n",
       "      <td>360</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>AF</td>\n",
       "      <td>2</td>\n",
       "      <td>Afghanistan</td>\n",
       "      <td>2513</td>\n",
       "      <td>Barley and products</td>\n",
       "      <td>5142</td>\n",
       "      <td>Food</td>\n",
       "      <td>1000 tonnes</td>\n",
       "      <td>33.94</td>\n",
       "      <td>67.71</td>\n",
       "      <td>...</td>\n",
       "      <td>185.0</td>\n",
       "      <td>43.0</td>\n",
       "      <td>44.0</td>\n",
       "      <td>48.0</td>\n",
       "      <td>62.0</td>\n",
       "      <td>55.0</td>\n",
       "      <td>60.0</td>\n",
       "      <td>72.0</td>\n",
       "      <td>78</td>\n",
       "      <td>89</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>AF</td>\n",
       "      <td>2</td>\n",
       "      <td>Afghanistan</td>\n",
       "      <td>2514</td>\n",
       "      <td>Maize and products</td>\n",
       "      <td>5521</td>\n",
       "      <td>Feed</td>\n",
       "      <td>1000 tonnes</td>\n",
       "      <td>33.94</td>\n",
       "      <td>67.71</td>\n",
       "      <td>...</td>\n",
       "      <td>120.0</td>\n",
       "      <td>208.0</td>\n",
       "      <td>233.0</td>\n",
       "      <td>249.0</td>\n",
       "      <td>247.0</td>\n",
       "      <td>195.0</td>\n",
       "      <td>178.0</td>\n",
       "      <td>191.0</td>\n",
       "      <td>200</td>\n",
       "      <td>200</td>\n",
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       "      <th>...</th>\n",
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       "      <td>...</td>\n",
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       "      <td>...</td>\n",
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       "      <td>...</td>\n",
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       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21472</th>\n",
       "      <td>ZW</td>\n",
       "      <td>181</td>\n",
       "      <td>Zimbabwe</td>\n",
       "      <td>2948</td>\n",
       "      <td>Milk - Excluding Butter</td>\n",
       "      <td>5142</td>\n",
       "      <td>Food</td>\n",
       "      <td>1000 tonnes</td>\n",
       "      <td>-19.02</td>\n",
       "      <td>29.15</td>\n",
       "      <td>...</td>\n",
       "      <td>373.0</td>\n",
       "      <td>357.0</td>\n",
       "      <td>359.0</td>\n",
       "      <td>356.0</td>\n",
       "      <td>341.0</td>\n",
       "      <td>385.0</td>\n",
       "      <td>418.0</td>\n",
       "      <td>457.0</td>\n",
       "      <td>426</td>\n",
       "      <td>451</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21473</th>\n",
       "      <td>ZW</td>\n",
       "      <td>181</td>\n",
       "      <td>Zimbabwe</td>\n",
       "      <td>2960</td>\n",
       "      <td>Fish, Seafood</td>\n",
       "      <td>5521</td>\n",
       "      <td>Feed</td>\n",
       "      <td>1000 tonnes</td>\n",
       "      <td>-19.02</td>\n",
       "      <td>29.15</td>\n",
       "      <td>...</td>\n",
       "      <td>5.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>15.0</td>\n",
       "      <td>15.0</td>\n",
       "      <td>15</td>\n",
       "      <td>15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21474</th>\n",
       "      <td>ZW</td>\n",
       "      <td>181</td>\n",
       "      <td>Zimbabwe</td>\n",
       "      <td>2960</td>\n",
       "      <td>Fish, Seafood</td>\n",
       "      <td>5142</td>\n",
       "      <td>Food</td>\n",
       "      <td>1000 tonnes</td>\n",
       "      <td>-19.02</td>\n",
       "      <td>29.15</td>\n",
       "      <td>...</td>\n",
       "      <td>18.0</td>\n",
       "      <td>14.0</td>\n",
       "      <td>17.0</td>\n",
       "      <td>14.0</td>\n",
       "      <td>15.0</td>\n",
       "      <td>18.0</td>\n",
       "      <td>29.0</td>\n",
       "      <td>40.0</td>\n",
       "      <td>40</td>\n",
       "      <td>40</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21475</th>\n",
       "      <td>ZW</td>\n",
       "      <td>181</td>\n",
       "      <td>Zimbabwe</td>\n",
       "      <td>2961</td>\n",
       "      <td>Aquatic Products, Other</td>\n",
       "      <td>5142</td>\n",
       "      <td>Food</td>\n",
       "      <td>1000 tonnes</td>\n",
       "      <td>-19.02</td>\n",
       "      <td>29.15</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
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       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21476</th>\n",
       "      <td>ZW</td>\n",
       "      <td>181</td>\n",
       "      <td>Zimbabwe</td>\n",
       "      <td>2928</td>\n",
       "      <td>Miscellaneous</td>\n",
       "      <td>5142</td>\n",
       "      <td>Food</td>\n",
       "      <td>1000 tonnes</td>\n",
       "      <td>-19.02</td>\n",
       "      <td>29.15</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
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       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>21477 rows × 63 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      Area Abbreviation  Area Code         Area  Item Code  \\\n",
       "0                    AF          2  Afghanistan       2511   \n",
       "1                    AF          2  Afghanistan       2805   \n",
       "2                    AF          2  Afghanistan       2513   \n",
       "3                    AF          2  Afghanistan       2513   \n",
       "4                    AF          2  Afghanistan       2514   \n",
       "...                 ...        ...          ...        ...   \n",
       "21472                ZW        181     Zimbabwe       2948   \n",
       "21473                ZW        181     Zimbabwe       2960   \n",
       "21474                ZW        181     Zimbabwe       2960   \n",
       "21475                ZW        181     Zimbabwe       2961   \n",
       "21476                ZW        181     Zimbabwe       2928   \n",
       "\n",
       "                           Item  Element Code Element         Unit  latitude  \\\n",
       "0            Wheat and products          5142    Food  1000 tonnes     33.94   \n",
       "1      Rice (Milled Equivalent)          5142    Food  1000 tonnes     33.94   \n",
       "2           Barley and products          5521    Feed  1000 tonnes     33.94   \n",
       "3           Barley and products          5142    Food  1000 tonnes     33.94   \n",
       "4            Maize and products          5521    Feed  1000 tonnes     33.94   \n",
       "...                         ...           ...     ...          ...       ...   \n",
       "21472   Milk - Excluding Butter          5142    Food  1000 tonnes    -19.02   \n",
       "21473             Fish, Seafood          5521    Feed  1000 tonnes    -19.02   \n",
       "21474             Fish, Seafood          5142    Food  1000 tonnes    -19.02   \n",
       "21475   Aquatic Products, Other          5142    Food  1000 tonnes    -19.02   \n",
       "21476             Miscellaneous          5142    Food  1000 tonnes    -19.02   \n",
       "\n",
       "       longitude  ...   Y2004   Y2005   Y2006   Y2007   Y2008   Y2009   Y2010  \\\n",
       "0          67.71  ...  3249.0  3486.0  3704.0  4164.0  4252.0  4538.0  4605.0   \n",
       "1          67.71  ...   419.0   445.0   546.0   455.0   490.0   415.0   442.0   \n",
       "2          67.71  ...    58.0   236.0   262.0   263.0   230.0   379.0   315.0   \n",
       "3          67.71  ...   185.0    43.0    44.0    48.0    62.0    55.0    60.0   \n",
       "4          67.71  ...   120.0   208.0   233.0   249.0   247.0   195.0   178.0   \n",
       "...          ...  ...     ...     ...     ...     ...     ...     ...     ...   \n",
       "21472      29.15  ...   373.0   357.0   359.0   356.0   341.0   385.0   418.0   \n",
       "21473      29.15  ...     5.0     4.0     9.0     6.0     9.0     5.0    15.0   \n",
       "21474      29.15  ...    18.0    14.0    17.0    14.0    15.0    18.0    29.0   \n",
       "21475      29.15  ...     0.0     0.0     0.0     0.0     0.0     0.0     0.0   \n",
       "21476      29.15  ...     0.0     0.0     0.0     0.0     0.0     0.0     0.0   \n",
       "\n",
       "        Y2011  Y2012  Y2013  \n",
       "0      4711.0   4810   4895  \n",
       "1       476.0    425    422  \n",
       "2       203.0    367    360  \n",
       "3        72.0     78     89  \n",
       "4       191.0    200    200  \n",
       "...       ...    ...    ...  \n",
       "21472   457.0    426    451  \n",
       "21473    15.0     15     15  \n",
       "21474    40.0     40     40  \n",
       "21475     0.0      0      0  \n",
       "21476     0.0      0      0  \n",
       "\n",
       "[21477 rows x 63 columns]"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import pandas as pd\n",
    "\n",
    "df_rel = pd.read_csv(location_rel)\n",
    "df_rel"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "- Pandas는 DataFrame을 기본적으로 20개의 열과 60개의 행만 표시(나머지 중간부분은 자름)\n",
    "- DataFrame 출력 제한을 변경하는 옵션 존재(pd.display.options.func_name = 값)     \n",
    "(https://pandas.pydata.org/pandas-docs/stable/options.html)\n",
    "> - pd.options.display.width: 문자로 표시되는 디스플레이의 너비로 둘 이상의 행에 걸쳐 행을 줄 바꿈하는 경우\n",
    "> - pd.options.display.max_rows: 표시되는 최대 행 수\n",
    "> - pd.options.display.max_columns: 표시되는 최대 열 수"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-03-15T06:56:23.034381Z",
     "start_time": "2021-03-15T06:56:23.023412Z"
    }
   },
   "outputs": [],
   "source": [
    "pd.options.display.max_rows = 10\n",
    "pd.options.display.max_columns = 10"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-03-15T06:56:23.079291Z",
     "start_time": "2021-03-15T06:56:23.037371Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
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       "\n",
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       "\n",
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       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Area Abbreviation</th>\n",
       "      <th>Area Code</th>\n",
       "      <th>Area</th>\n",
       "      <th>Item Code</th>\n",
       "      <th>Item</th>\n",
       "      <th>...</th>\n",
       "      <th>Y2009</th>\n",
       "      <th>Y2010</th>\n",
       "      <th>Y2011</th>\n",
       "      <th>Y2012</th>\n",
       "      <th>Y2013</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>AF</td>\n",
       "      <td>2</td>\n",
       "      <td>Afghanistan</td>\n",
       "      <td>2511</td>\n",
       "      <td>Wheat and products</td>\n",
       "      <td>...</td>\n",
       "      <td>4538.0</td>\n",
       "      <td>4605.0</td>\n",
       "      <td>4711.0</td>\n",
       "      <td>4810</td>\n",
       "      <td>4895</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>AF</td>\n",
       "      <td>2</td>\n",
       "      <td>Afghanistan</td>\n",
       "      <td>2805</td>\n",
       "      <td>Rice (Milled Equivalent)</td>\n",
       "      <td>...</td>\n",
       "      <td>415.0</td>\n",
       "      <td>442.0</td>\n",
       "      <td>476.0</td>\n",
       "      <td>425</td>\n",
       "      <td>422</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>AF</td>\n",
       "      <td>2</td>\n",
       "      <td>Afghanistan</td>\n",
       "      <td>2513</td>\n",
       "      <td>Barley and products</td>\n",
       "      <td>...</td>\n",
       "      <td>379.0</td>\n",
       "      <td>315.0</td>\n",
       "      <td>203.0</td>\n",
       "      <td>367</td>\n",
       "      <td>360</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>AF</td>\n",
       "      <td>2</td>\n",
       "      <td>Afghanistan</td>\n",
       "      <td>2513</td>\n",
       "      <td>Barley and products</td>\n",
       "      <td>...</td>\n",
       "      <td>55.0</td>\n",
       "      <td>60.0</td>\n",
       "      <td>72.0</td>\n",
       "      <td>78</td>\n",
       "      <td>89</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>AF</td>\n",
       "      <td>2</td>\n",
       "      <td>Afghanistan</td>\n",
       "      <td>2514</td>\n",
       "      <td>Maize and products</td>\n",
       "      <td>...</td>\n",
       "      <td>195.0</td>\n",
       "      <td>178.0</td>\n",
       "      <td>191.0</td>\n",
       "      <td>200</td>\n",
       "      <td>200</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21472</th>\n",
       "      <td>ZW</td>\n",
       "      <td>181</td>\n",
       "      <td>Zimbabwe</td>\n",
       "      <td>2948</td>\n",
       "      <td>Milk - Excluding Butter</td>\n",
       "      <td>...</td>\n",
       "      <td>385.0</td>\n",
       "      <td>418.0</td>\n",
       "      <td>457.0</td>\n",
       "      <td>426</td>\n",
       "      <td>451</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21473</th>\n",
       "      <td>ZW</td>\n",
       "      <td>181</td>\n",
       "      <td>Zimbabwe</td>\n",
       "      <td>2960</td>\n",
       "      <td>Fish, Seafood</td>\n",
       "      <td>...</td>\n",
       "      <td>5.0</td>\n",
       "      <td>15.0</td>\n",
       "      <td>15.0</td>\n",
       "      <td>15</td>\n",
       "      <td>15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21474</th>\n",
       "      <td>ZW</td>\n",
       "      <td>181</td>\n",
       "      <td>Zimbabwe</td>\n",
       "      <td>2960</td>\n",
       "      <td>Fish, Seafood</td>\n",
       "      <td>...</td>\n",
       "      <td>18.0</td>\n",
       "      <td>29.0</td>\n",
       "      <td>40.0</td>\n",
       "      <td>40</td>\n",
       "      <td>40</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21475</th>\n",
       "      <td>ZW</td>\n",
       "      <td>181</td>\n",
       "      <td>Zimbabwe</td>\n",
       "      <td>2961</td>\n",
       "      <td>Aquatic Products, Other</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21476</th>\n",
       "      <td>ZW</td>\n",
       "      <td>181</td>\n",
       "      <td>Zimbabwe</td>\n",
       "      <td>2928</td>\n",
       "      <td>Miscellaneous</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>21477 rows × 63 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      Area Abbreviation  Area Code         Area  Item Code  \\\n",
       "0                    AF          2  Afghanistan       2511   \n",
       "1                    AF          2  Afghanistan       2805   \n",
       "2                    AF          2  Afghanistan       2513   \n",
       "3                    AF          2  Afghanistan       2513   \n",
       "4                    AF          2  Afghanistan       2514   \n",
       "...                 ...        ...          ...        ...   \n",
       "21472                ZW        181     Zimbabwe       2948   \n",
       "21473                ZW        181     Zimbabwe       2960   \n",
       "21474                ZW        181     Zimbabwe       2960   \n",
       "21475                ZW        181     Zimbabwe       2961   \n",
       "21476                ZW        181     Zimbabwe       2928   \n",
       "\n",
       "                           Item  ...   Y2009   Y2010   Y2011  Y2012  Y2013  \n",
       "0            Wheat and products  ...  4538.0  4605.0  4711.0   4810   4895  \n",
       "1      Rice (Milled Equivalent)  ...   415.0   442.0   476.0    425    422  \n",
       "2           Barley and products  ...   379.0   315.0   203.0    367    360  \n",
       "3           Barley and products  ...    55.0    60.0    72.0     78     89  \n",
       "4            Maize and products  ...   195.0   178.0   191.0    200    200  \n",
       "...                         ...  ...     ...     ...     ...    ...    ...  \n",
       "21472   Milk - Excluding Butter  ...   385.0   418.0   457.0    426    451  \n",
       "21473             Fish, Seafood  ...     5.0    15.0    15.0     15     15  \n",
       "21474             Fish, Seafood  ...    18.0    29.0    40.0     40     40  \n",
       "21475   Aquatic Products, Other  ...     0.0     0.0     0.0      0      0  \n",
       "21476             Miscellaneous  ...     0.0     0.0     0.0      0      0  \n",
       "\n",
       "[21477 rows x 63 columns]"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_rel"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 값 선택과 다루기(Selection and Indexing)\n",
    "\n",
    "**1) Series**\n",
    "> - NumPy 배열과 유사한 원리로 작동되는데 Series는 정수가 아니어도 Indexing이 가능"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-03-15T06:56:23.094252Z",
     "start_time": "2021-03-15T06:56:23.080287Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0        AF\n",
       "1        AF\n",
       "2        AF\n",
       "3        AF\n",
       "4        AF\n",
       "         ..\n",
       "21472    ZW\n",
       "21473    ZW\n",
       "21474    ZW\n",
       "21475    ZW\n",
       "21476    ZW\n",
       "Name: Area Abbreviation, Length: 21477, dtype: object"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_series = df_rel['Area Abbreviation'].copy()\n",
    "df_series"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-03-15T06:56:23.109209Z",
     "start_time": "2021-03-15T06:56:23.096213Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1    AF\n",
       "3    AF\n",
       "Name: Area Abbreviation, dtype: object"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_series[[1,3]]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-03-15T06:56:23.124169Z",
     "start_time": "2021-03-15T06:56:23.110177Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0    AF\n",
       "1    AF\n",
       "2    AF\n",
       "3    AF\n",
       "4    AF\n",
       "5    AF\n",
       "6    AF\n",
       "7    AF\n",
       "8    AF\n",
       "9    AF\n",
       "Name: Area Abbreviation, dtype: object"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_series[df_series.index < 10]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-03-15T06:56:23.139127Z",
     "start_time": "2021-03-15T06:56:23.125161Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1    AF\n",
       "2    AF\n",
       "3    AF\n",
       "4    AF\n",
       "Name: Area Abbreviation, dtype: object"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_series[1:5]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-03-15T06:56:23.154090Z",
     "start_time": "2021-03-15T06:56:23.140127Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0          AF\n",
       "1        Test\n",
       "2        Test\n",
       "3          AF\n",
       "4          AF\n",
       "         ... \n",
       "21472      ZW\n",
       "21473      ZW\n",
       "21474      ZW\n",
       "21475      ZW\n",
       "21476      ZW\n",
       "Name: Area Abbreviation, Length: 21477, dtype: object"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_series[1:3] = 'Test'\n",
    "df_series"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**2) DataFrame**\n",
    "- 값을 선택하고 Indexing하는 두 가지 주요 옵션이 있으며 특정 목록이나 단일 값을 선택하여 출력가능     \n",
    "(http://pandas.pydata.org/pandas-docs/stable/indexing.html#selection-by-label)\n",
    "> - **iloc:** \n",
    ">> - 하나의 행이 선택되면 Series를 반환하고 여러 행이 선택되면 DataFrame을 반환\n",
    ">> - 여러 열 또는 여러 행을 선택할 때 선택항목([1:5])에서 선택한 행/열은 첫 번째 숫자에서 1에서 두 번째 숫자를 뺀 값으로 실행됩니다. [1:5]는 1,2,3,4로 이동하고 [x,y]는 x에서 y-1로 이동\n",
    "> - **loc:**\n",
    ">> - Labal / Index / Bool / Logical Indexing 기반 값을 전달하여 Series나 DataFrame의 값을 반환\n",
    "<center><img src='Image/Basic_Pandas_Selection.PNG' width='600'></center>\n",
    "\n",
    "> - **행과 열의 삭제:** \"drop\"기능 사용\n",
    ">> - 열 또는 여러 열을 삭제하려면 열 이름을 사용하고 \"axis\"를 1로 지정\n",
    ">> - drop 함수는 열이 제거 된 새 DataFrame을 반환하며 원래 DataFrame 값이 수정되려면 drop 함수 내 \"inplace\" 변수를 True로 설정\n",
    ">> - \"axis = 0\"을 지정하여“drop”기능을 사용하면 행이 제거\n",
    ">> - drop 함수는 숫자 인덱싱이 아닌 \"Label\" 기반으로 행을 제거하며 숫자위치나 Index를 기준으로 행을 삭제하려면 iloc을 사용하여 가능"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-03-15T06:56:23.169019Z",
     "start_time": "2021-03-15T06:56:23.155085Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Area Abbreviation                    AF\n",
       "Area Code                             2\n",
       "Area                        Afghanistan\n",
       "Item Code                          2511\n",
       "Item                 Wheat and products\n",
       "                            ...        \n",
       "Y2009                              4538\n",
       "Y2010                              4605\n",
       "Y2011                              4711\n",
       "Y2012                              4810\n",
       "Y2013                              4895\n",
       "Name: 0, Length: 63, dtype: object"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Selecting and manipulating data\n",
    "df_rel.iloc[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-03-15T06:56:23.198945Z",
     "start_time": "2021-03-15T06:56:23.172013Z"
    }
   },
   "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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       "    .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>Area Abbreviation</th>\n",
       "      <th>Area Code</th>\n",
       "      <th>Area</th>\n",
       "      <th>Item Code</th>\n",
       "      <th>Item</th>\n",
       "      <th>...</th>\n",
       "      <th>Y2009</th>\n",
       "      <th>Y2010</th>\n",
       "      <th>Y2011</th>\n",
       "      <th>Y2012</th>\n",
       "      <th>Y2013</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>AF</td>\n",
       "      <td>2</td>\n",
       "      <td>Afghanistan</td>\n",
       "      <td>2805</td>\n",
       "      <td>Rice (Milled Equivalent)</td>\n",
       "      <td>...</td>\n",
       "      <td>415.0</td>\n",
       "      <td>442.0</td>\n",
       "      <td>476.0</td>\n",
       "      <td>425</td>\n",
       "      <td>422</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1 rows × 63 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "  Area Abbreviation  Area Code         Area  Item Code  \\\n",
       "1                AF          2  Afghanistan       2805   \n",
       "\n",
       "                       Item  ...  Y2009  Y2010  Y2011  Y2012  Y2013  \n",
       "1  Rice (Milled Equivalent)  ...  415.0  442.0  476.0    425    422  \n",
       "\n",
       "[1 rows x 63 columns]"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_rel.iloc[[1]]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-03-15T06:56:23.228863Z",
     "start_time": "2021-03-15T06:56:23.201933Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .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",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Area Abbreviation</th>\n",
       "      <th>Area Code</th>\n",
       "      <th>Area</th>\n",
       "      <th>Item Code</th>\n",
       "      <th>Item</th>\n",
       "      <th>...</th>\n",
       "      <th>Y2009</th>\n",
       "      <th>Y2010</th>\n",
       "      <th>Y2011</th>\n",
       "      <th>Y2012</th>\n",
       "      <th>Y2013</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>21476</th>\n",
       "      <td>ZW</td>\n",
       "      <td>181</td>\n",
       "      <td>Zimbabwe</td>\n",
       "      <td>2928</td>\n",
       "      <td>Miscellaneous</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1 rows × 63 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      Area Abbreviation  Area Code      Area  Item Code           Item  ...  \\\n",
       "21476                ZW        181  Zimbabwe       2928  Miscellaneous  ...   \n",
       "\n",
       "       Y2009 Y2010 Y2011  Y2012  Y2013  \n",
       "21476    0.0   0.0   0.0      0      0  \n",
       "\n",
       "[1 rows x 63 columns]"
      ]
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       "      Area Abbreviation  Area Code\n",
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       "   Area Abbreviation  Element Code Element\n",
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       "   Element Code Element         Unit\n",
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   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-03-15T06:56:23.423349Z",
     "start_time": "2021-03-15T06:56:23.411373Z"
    }
   },
   "outputs": [],
   "source": [
    "# df_rel.iloc[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-03-15T06:56:23.438299Z",
     "start_time": "2021-03-15T06:56:23.427332Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Area Abbreviation                    AF\n",
       "Area Code                             2\n",
       "Area                        Afghanistan\n",
       "Item Code                          2511\n",
       "Item                 Wheat and products\n",
       "                            ...        \n",
       "Y2009                              4538\n",
       "Y2010                              4605\n",
       "Y2011                              4711\n",
       "Y2012                              4810\n",
       "Y2013                              4895\n",
       "Name: 0, Length: 63, dtype: object"
      ]
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_rel.loc[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-03-15T06:56:23.453259Z",
     "start_time": "2021-03-15T06:56:23.439296Z"
    }
   },
   "outputs": [
    {
     "data": {
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       "      <td>2805</td>\n",
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       "      <td>415.0</td>\n",
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       "      <td>425</td>\n",
       "      <td>422</td>\n",
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       "  Area Abbreviation  Area Code         Area  Item Code  \\\n",
       "1                AF          2  Afghanistan       2805   \n",
       "\n",
       "                       Item  ...  Y2009  Y2010  Y2011  Y2012  Y2013  \n",
       "1  Rice (Milled Equivalent)  ...  415.0  442.0  476.0    425    422  \n",
       "\n",
       "[1 rows x 63 columns]"
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_rel.loc[[1]]"
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  {
   "cell_type": "code",
   "execution_count": 42,
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    "ExecuteTime": {
     "end_time": "2021-03-15T06:56:23.468223Z",
     "start_time": "2021-03-15T06:56:23.454257Z"
    }
   },
   "outputs": [
    {
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       "      <td>78</td>\n",
       "      <td>89</td>\n",
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       "  Area Abbreviation  Area Code         Area  Item Code  \\\n",
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       "\n",
       "                       Item  ...  Y2009  Y2010  Y2011  Y2012  Y2013  \n",
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       "3       Barley and products  ...   55.0   60.0   72.0     78     89  \n",
       "\n",
       "[2 rows x 63 columns]"
      ]
     },
     "execution_count": 42,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_rel.loc[[1,3]]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-03-15T06:56:23.483184Z",
     "start_time": "2021-03-15T06:56:23.469220Z"
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   "outputs": [
    {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Item</th>\n",
       "      <th>Y2013</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Rice (Milled Equivalent)</td>\n",
       "      <td>422</td>\n",
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      "text/plain": [
       "                       Item  Y2013\n",
       "1  Rice (Milled Equivalent)    422\n",
       "3       Barley and products     89"
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     "metadata": {},
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   ],
   "source": [
    "df_rel.loc[[1,3],['Item','Y2013']]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-03-15T06:56:23.498143Z",
     "start_time": "2021-03-15T06:56:23.484180Z"
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   "outputs": [
    {
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       "      <td>89</td>\n",
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       "                       Item  Element Code Element         Unit  latitude  ...  \\\n",
       "1  Rice (Milled Equivalent)          5142    Food  1000 tonnes     33.94  ...   \n",
       "3       Barley and products          5142    Food  1000 tonnes     33.94  ...   \n",
       "\n",
       "   Y2009  Y2010  Y2011  Y2012  Y2013  \n",
       "1  415.0  442.0  476.0    425    422  \n",
       "3   55.0   60.0   72.0     78     89  \n",
       "\n",
       "[2 rows x 59 columns]"
      ]
     },
     "execution_count": 44,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_rel.loc[[1,3],'Item':'Y2013']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-03-15T06:56:23.513106Z",
     "start_time": "2021-03-15T06:56:23.499141Z"
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   },
   "outputs": [
    {
     "data": {
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       "                       Item  Element Code Element         Unit  latitude  ...  \\\n",
       "1  Rice (Milled Equivalent)          5142    Food  1000 tonnes     33.94  ...   \n",
       "2       Barley and products          5521    Feed  1000 tonnes     33.94  ...   \n",
       "3       Barley and products          5142    Food  1000 tonnes     33.94  ...   \n",
       "\n",
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       "2  379.0  315.0  203.0    367    360  \n",
       "3   55.0   60.0   72.0     78     89  \n",
       "\n",
       "[3 rows x 59 columns]"
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     },
     "execution_count": 45,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_rel.loc[1:3,'Item':'Y2013']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-03-15T06:56:23.544020Z",
     "start_time": "2021-03-15T06:56:23.516095Z"
    }
   },
   "outputs": [
    {
     "data": {
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       "          Item  Element Code Element         Unit  latitude  ...  Y2009  \\\n",
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   "source": [
    "df_test = df_rel.loc[10:,'Item':'Y2013']\n",
    "df_test.iloc[[0]]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-03-15T06:56:23.558980Z",
     "start_time": "2021-03-15T06:56:23.546017Z"
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   },
   "outputs": [
    {
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       "          Item  Element Code Element         Unit  latitude  ...  Y2009  \\\n",
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     "start_time": "2021-03-15T06:56:23.560976Z"
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   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0        False\n",
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     "execution_count": 48,
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   "source": [
    "df_rel['Item'] == 'Sugar beet'"
   ]
  },
  {
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   "execution_count": 49,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-03-15T06:56:23.603859Z",
     "start_time": "2021-03-15T06:56:23.574937Z"
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    {
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       "      <td>2537</td>\n",
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       "      Area Abbreviation  Area Code                                Area  \\\n",
       "10                   AF          2                         Afghanistan   \n",
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       "699                  AM          1                             Armenia   \n",
       "832                  AU         10                           Australia   \n",
       "1099                 AZ         52                          Azerbaijan   \n",
       "...                 ...        ...                                 ...   \n",
       "20020                AE        225                United Arab Emirates   \n",
       "20676                UZ        235                          Uzbekistan   \n",
       "20900                VE        236  Venezuela (Bolivarian Republic of)   \n",
       "21135                YE        249                               Yemen   \n",
       "21374                ZW        181                            Zimbabwe   \n",
       "\n",
       "       Item Code        Item  ...  Y2009 Y2010 Y2011  Y2012  Y2013  \n",
       "10          2537  Sugar beet  ...    0.0   0.0   0.0      0      0  \n",
       "103         2537  Sugar beet  ...    1.0   1.0   1.0      1      1  \n",
       "699         2537  Sugar beet  ...    3.0   1.0   1.0      0      1  \n",
       "832         2537  Sugar beet  ...    0.0   0.0   0.0      0      0  \n",
       "1099        2537  Sugar beet  ...    4.0   6.0   6.0      4      4  \n",
       "...          ...         ...  ...    ...   ...   ...    ...    ...  \n",
       "20020       2537  Sugar beet  ...    0.0   0.0   0.0      0      0  \n",
       "20676       2537  Sugar beet  ...    0.0   0.0   0.0      0      0  \n",
       "20900       2537  Sugar beet  ...   21.0  30.0  35.0     20     22  \n",
       "21135       2537  Sugar beet  ...    0.0   0.0   0.0      0      0  \n",
       "21374       2537  Sugar beet  ...    0.0   0.0   0.0      0      0  \n",
       "\n",
       "[66 rows x 63 columns]"
      ]
     },
     "execution_count": 49,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_rel.loc[df_rel['Item'] == 'Sugar beet']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-03-15T06:56:23.633780Z",
     "start_time": "2021-03-15T06:56:23.604857Z"
    }
   },
   "outputs": [
    {
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       "      <td>2537</td>\n",
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       "      <td>2537</td>\n",
       "      <td>Sugar beet</td>\n",
       "      <td>...</td>\n",
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       "      <td>Yemen</td>\n",
       "      <td>2537</td>\n",
       "      <td>Sugar beet</td>\n",
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      ],
      "text/plain": [
       "      Area Abbreviation  Area Code                                Area  \\\n",
       "10                   AF          2                         Afghanistan   \n",
       "103                  AL          3                             Albania   \n",
       "699                  AM          1                             Armenia   \n",
       "832                  AU         10                           Australia   \n",
       "1099                 AZ         52                          Azerbaijan   \n",
       "...                 ...        ...                                 ...   \n",
       "20020                AE        225                United Arab Emirates   \n",
       "20676                UZ        235                          Uzbekistan   \n",
       "20900                VE        236  Venezuela (Bolivarian Republic of)   \n",
       "21135                YE        249                               Yemen   \n",
       "21374                ZW        181                            Zimbabwe   \n",
       "\n",
       "       Item Code        Item  ...  Y2009 Y2010 Y2011  Y2012  Y2013  \n",
       "10          2537  Sugar beet  ...    0.0   0.0   0.0      0      0  \n",
       "103         2537  Sugar beet  ...    1.0   1.0   1.0      1      1  \n",
       "699         2537  Sugar beet  ...    3.0   1.0   1.0      0      1  \n",
       "832         2537  Sugar beet  ...    0.0   0.0   0.0      0      0  \n",
       "1099        2537  Sugar beet  ...    4.0   6.0   6.0      4      4  \n",
       "...          ...         ...  ...    ...   ...   ...    ...    ...  \n",
       "20020       2537  Sugar beet  ...    0.0   0.0   0.0      0      0  \n",
       "20676       2537  Sugar beet  ...    0.0   0.0   0.0      0      0  \n",
       "20900       2537  Sugar beet  ...   21.0  30.0  35.0     20     22  \n",
       "21135       2537  Sugar beet  ...    0.0   0.0   0.0      0      0  \n",
       "21374       2537  Sugar beet  ...    0.0   0.0   0.0      0      0  \n",
       "\n",
       "[66 rows x 63 columns]"
      ]
     },
     "execution_count": 50,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# is same as\n",
    "df_rel[df_rel['Item'] == 'Sugar beet']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-03-15T06:56:23.648742Z",
     "start_time": "2021-03-15T06:56:23.634778Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "10                              Afghanistan\n",
       "103                                 Albania\n",
       "699                                 Armenia\n",
       "832                               Australia\n",
       "1099                             Azerbaijan\n",
       "                        ...                \n",
       "20020                  United Arab Emirates\n",
       "20676                            Uzbekistan\n",
       "20900    Venezuela (Bolivarian Republic of)\n",
       "21135                                 Yemen\n",
       "21374                              Zimbabwe\n",
       "Name: Area, Length: 66, dtype: object"
      ]
     },
     "execution_count": 51,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_rel.loc[df_rel['Item'] == 'Sugar beet', 'Area']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-03-15T06:56:23.663702Z",
     "start_time": "2021-03-15T06:56:23.651733Z"
    }
   },
   "outputs": [
    {
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       "      <th>103</th>\n",
       "      <td>Albania</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>699</th>\n",
       "      <td>Armenia</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>832</th>\n",
       "      <td>Australia</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1099</th>\n",
       "      <td>Azerbaijan</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20020</th>\n",
       "      <td>United Arab Emirates</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20676</th>\n",
       "      <td>Uzbekistan</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20900</th>\n",
       "      <td>Venezuela (Bolivarian Republic of)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21135</th>\n",
       "      <td>Yemen</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21374</th>\n",
       "      <td>Zimbabwe</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>66 rows × 1 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                     Area\n",
       "10                            Afghanistan\n",
       "103                               Albania\n",
       "699                               Armenia\n",
       "832                             Australia\n",
       "1099                           Azerbaijan\n",
       "...                                   ...\n",
       "20020                United Arab Emirates\n",
       "20676                          Uzbekistan\n",
       "20900  Venezuela (Bolivarian Republic of)\n",
       "21135                               Yemen\n",
       "21374                            Zimbabwe\n",
       "\n",
       "[66 rows x 1 columns]"
      ]
     },
     "execution_count": 52,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_rel.loc[df_rel['Item'] == 'Sugar beet', ['Area']]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-03-15T06:56:23.678664Z",
     "start_time": "2021-03-15T06:56:23.665694Z"
    }
   },
   "outputs": [],
   "source": [
    "# is not same as\n",
    "# df_rel[df_rel['Item'] == 'Sugar beet', ['Area']]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-03-15T06:56:23.693621Z",
     "start_time": "2021-03-15T06:56:23.680658Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
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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>Area</th>\n",
       "      <th>Item</th>\n",
       "      <th>latitude</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>Afghanistan</td>\n",
       "      <td>Sugar beet</td>\n",
       "      <td>33.94</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>103</th>\n",
       "      <td>Albania</td>\n",
       "      <td>Sugar beet</td>\n",
       "      <td>41.15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>699</th>\n",
       "      <td>Armenia</td>\n",
       "      <td>Sugar beet</td>\n",
       "      <td>40.07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>832</th>\n",
       "      <td>Australia</td>\n",
       "      <td>Sugar beet</td>\n",
       "      <td>-25.27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1099</th>\n",
       "      <td>Azerbaijan</td>\n",
       "      <td>Sugar beet</td>\n",
       "      <td>40.14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20020</th>\n",
       "      <td>United Arab Emirates</td>\n",
       "      <td>Sugar beet</td>\n",
       "      <td>23.42</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20676</th>\n",
       "      <td>Uzbekistan</td>\n",
       "      <td>Sugar beet</td>\n",
       "      <td>41.38</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20900</th>\n",
       "      <td>Venezuela (Bolivarian Republic of)</td>\n",
       "      <td>Sugar beet</td>\n",
       "      <td>6.42</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21135</th>\n",
       "      <td>Yemen</td>\n",
       "      <td>Sugar beet</td>\n",
       "      <td>15.55</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21374</th>\n",
       "      <td>Zimbabwe</td>\n",
       "      <td>Sugar beet</td>\n",
       "      <td>-19.02</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>66 rows × 3 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                     Area        Item  latitude\n",
       "10                            Afghanistan  Sugar beet     33.94\n",
       "103                               Albania  Sugar beet     41.15\n",
       "699                               Armenia  Sugar beet     40.07\n",
       "832                             Australia  Sugar beet    -25.27\n",
       "1099                           Azerbaijan  Sugar beet     40.14\n",
       "...                                   ...         ...       ...\n",
       "20020                United Arab Emirates  Sugar beet     23.42\n",
       "20676                          Uzbekistan  Sugar beet     41.38\n",
       "20900  Venezuela (Bolivarian Republic of)  Sugar beet      6.42\n",
       "21135                               Yemen  Sugar beet     15.55\n",
       "21374                            Zimbabwe  Sugar beet    -19.02\n",
       "\n",
       "[66 rows x 3 columns]"
      ]
     },
     "execution_count": 54,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_rel.loc[df_rel['Item'] == 'Sugar beet', ['Area', 'Item', 'latitude']]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-03-15T06:56:23.723540Z",
     "start_time": "2021-03-15T06:56:23.695614Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "    .dataframe tbody tr th:only-of-type {\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
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       "      <th></th>\n",
       "      <th>Area</th>\n",
       "      <th>Item Code</th>\n",
       "      <th>Item</th>\n",
       "      <th>Element Code</th>\n",
       "      <th>Element</th>\n",
       "      <th>Unit</th>\n",
       "      <th>latitude</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>Afghanistan</td>\n",
       "      <td>2537</td>\n",
       "      <td>Sugar beet</td>\n",
       "      <td>5521</td>\n",
       "      <td>Feed</td>\n",
       "      <td>1000 tonnes</td>\n",
       "      <td>33.94</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>103</th>\n",
       "      <td>Albania</td>\n",
       "      <td>2537</td>\n",
       "      <td>Sugar beet</td>\n",
       "      <td>5521</td>\n",
       "      <td>Feed</td>\n",
       "      <td>1000 tonnes</td>\n",
       "      <td>41.15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>699</th>\n",
       "      <td>Armenia</td>\n",
       "      <td>2537</td>\n",
       "      <td>Sugar beet</td>\n",
       "      <td>5521</td>\n",
       "      <td>Feed</td>\n",
       "      <td>1000 tonnes</td>\n",
       "      <td>40.07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>832</th>\n",
       "      <td>Australia</td>\n",
       "      <td>2537</td>\n",
       "      <td>Sugar beet</td>\n",
       "      <td>5521</td>\n",
       "      <td>Feed</td>\n",
       "      <td>1000 tonnes</td>\n",
       "      <td>-25.27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1099</th>\n",
       "      <td>Azerbaijan</td>\n",
       "      <td>2537</td>\n",
       "      <td>Sugar beet</td>\n",
       "      <td>5521</td>\n",
       "      <td>Feed</td>\n",
       "      <td>1000 tonnes</td>\n",
       "      <td>40.14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20020</th>\n",
       "      <td>United Arab Emirates</td>\n",
       "      <td>2537</td>\n",
       "      <td>Sugar beet</td>\n",
       "      <td>5521</td>\n",
       "      <td>Feed</td>\n",
       "      <td>1000 tonnes</td>\n",
       "      <td>23.42</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20676</th>\n",
       "      <td>Uzbekistan</td>\n",
       "      <td>2537</td>\n",
       "      <td>Sugar beet</td>\n",
       "      <td>5521</td>\n",
       "      <td>Feed</td>\n",
       "      <td>1000 tonnes</td>\n",
       "      <td>41.38</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20900</th>\n",
       "      <td>Venezuela (Bolivarian Republic of)</td>\n",
       "      <td>2537</td>\n",
       "      <td>Sugar beet</td>\n",
       "      <td>5142</td>\n",
       "      <td>Food</td>\n",
       "      <td>1000 tonnes</td>\n",
       "      <td>6.42</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21135</th>\n",
       "      <td>Yemen</td>\n",
       "      <td>2537</td>\n",
       "      <td>Sugar beet</td>\n",
       "      <td>5521</td>\n",
       "      <td>Feed</td>\n",
       "      <td>1000 tonnes</td>\n",
       "      <td>15.55</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21374</th>\n",
       "      <td>Zimbabwe</td>\n",
       "      <td>2537</td>\n",
       "      <td>Sugar beet</td>\n",
       "      <td>5142</td>\n",
       "      <td>Food</td>\n",
       "      <td>1000 tonnes</td>\n",
       "      <td>-19.02</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>66 rows × 7 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                     Area  Item Code        Item  \\\n",
       "10                            Afghanistan       2537  Sugar beet   \n",
       "103                               Albania       2537  Sugar beet   \n",
       "699                               Armenia       2537  Sugar beet   \n",
       "832                             Australia       2537  Sugar beet   \n",
       "1099                           Azerbaijan       2537  Sugar beet   \n",
       "...                                   ...        ...         ...   \n",
       "20020                United Arab Emirates       2537  Sugar beet   \n",
       "20676                          Uzbekistan       2537  Sugar beet   \n",
       "20900  Venezuela (Bolivarian Republic of)       2537  Sugar beet   \n",
       "21135                               Yemen       2537  Sugar beet   \n",
       "21374                            Zimbabwe       2537  Sugar beet   \n",
       "\n",
       "       Element Code Element         Unit  latitude  \n",
       "10             5521    Feed  1000 tonnes     33.94  \n",
       "103            5521    Feed  1000 tonnes     41.15  \n",
       "699            5521    Feed  1000 tonnes     40.07  \n",
       "832            5521    Feed  1000 tonnes    -25.27  \n",
       "1099           5521    Feed  1000 tonnes     40.14  \n",
       "...             ...     ...          ...       ...  \n",
       "20020          5521    Feed  1000 tonnes     23.42  \n",
       "20676          5521    Feed  1000 tonnes     41.38  \n",
       "20900          5142    Food  1000 tonnes      6.42  \n",
       "21135          5521    Feed  1000 tonnes     15.55  \n",
       "21374          5142    Food  1000 tonnes    -19.02  \n",
       "\n",
       "[66 rows x 7 columns]"
      ]
     },
     "execution_count": 55,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_rel.loc[df_rel['Item'] == 'Sugar beet', 'Area':'latitude']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-03-15T06:56:23.768448Z",
     "start_time": "2021-03-15T06:56:23.724538Z"
    }
   },
   "outputs": [
    {
     "data": {
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       "</table>\n",
       "<p>21477 rows × 62 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      Area Abbreviation  Area Code  Item Code                      Item  \\\n",
       "0                    AF          2       2511        Wheat and products   \n",
       "1                    AF          2       2805  Rice (Milled Equivalent)   \n",
       "2                    AF          2       2513       Barley and products   \n",
       "3                    AF          2       2513       Barley and products   \n",
       "4                    AF          2       2514        Maize and products   \n",
       "...                 ...        ...        ...                       ...   \n",
       "21472                ZW        181       2948   Milk - Excluding Butter   \n",
       "21473                ZW        181       2960             Fish, Seafood   \n",
       "21474                ZW        181       2960             Fish, Seafood   \n",
       "21475                ZW        181       2961   Aquatic Products, Other   \n",
       "21476                ZW        181       2928             Miscellaneous   \n",
       "\n",
       "       Element Code  ...   Y2009   Y2010   Y2011  Y2012  Y2013  \n",
       "0              5142  ...  4538.0  4605.0  4711.0   4810   4895  \n",
       "1              5142  ...   415.0   442.0   476.0    425    422  \n",
       "2              5521  ...   379.0   315.0   203.0    367    360  \n",
       "3              5142  ...    55.0    60.0    72.0     78     89  \n",
       "4              5521  ...   195.0   178.0   191.0    200    200  \n",
       "...             ...  ...     ...     ...     ...    ...    ...  \n",
       "21472          5142  ...   385.0   418.0   457.0    426    451  \n",
       "21473          5521  ...     5.0    15.0    15.0     15     15  \n",
       "21474          5142  ...    18.0    29.0    40.0     40     40  \n",
       "21475          5142  ...     0.0     0.0     0.0      0      0  \n",
       "21476          5142  ...     0.0     0.0     0.0      0      0  \n",
       "\n",
       "[21477 rows x 62 columns]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "Index(['Area Abbreviation', 'Area Code', 'Area', 'Item Code', 'Item',\n",
       "       'Element Code', 'Element', 'Unit', 'latitude', 'longitude', 'Y1961',\n",
       "       'Y1962', 'Y1963', 'Y1964', 'Y1965', 'Y1966', 'Y1967', 'Y1968', 'Y1969',\n",
       "       'Y1970', 'Y1971', 'Y1972', 'Y1973', 'Y1974', 'Y1975', 'Y1976', 'Y1977',\n",
       "       'Y1978', 'Y1979', 'Y1980', 'Y1981', 'Y1982', 'Y1983', 'Y1984', 'Y1985',\n",
       "       'Y1986', 'Y1987', 'Y1988', 'Y1989', 'Y1990', 'Y1991', 'Y1992', 'Y1993',\n",
       "       'Y1994', 'Y1995', 'Y1996', 'Y1997', 'Y1998', 'Y1999', 'Y2000', 'Y2001',\n",
       "       'Y2002', 'Y2003', 'Y2004', 'Y2005', 'Y2006', 'Y2007', 'Y2008', 'Y2009',\n",
       "       'Y2010', 'Y2011', 'Y2012', 'Y2013'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 56,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Delete the \"Area\" column from the dataframe\n",
    "df_rel.drop(\"Area\", axis=1)\n",
    "display(df_rel.drop(\"Area\", axis=1))\n",
    "df_rel.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-03-15T06:56:23.813337Z",
     "start_time": "2021-03-15T06:56:23.769417Z"
    }
   },
   "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>Area Abbreviation</th>\n",
       "      <th>Area Code</th>\n",
       "      <th>Item Code</th>\n",
       "      <th>Item</th>\n",
       "      <th>Element Code</th>\n",
       "      <th>...</th>\n",
       "      <th>Y2009</th>\n",
       "      <th>Y2010</th>\n",
       "      <th>Y2011</th>\n",
       "      <th>Y2012</th>\n",
       "      <th>Y2013</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>AF</td>\n",
       "      <td>2</td>\n",
       "      <td>2511</td>\n",
       "      <td>Wheat and products</td>\n",
       "      <td>5142</td>\n",
       "      <td>...</td>\n",
       "      <td>4538.0</td>\n",
       "      <td>4605.0</td>\n",
       "      <td>4711.0</td>\n",
       "      <td>4810</td>\n",
       "      <td>4895</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>AF</td>\n",
       "      <td>2</td>\n",
       "      <td>2805</td>\n",
       "      <td>Rice (Milled Equivalent)</td>\n",
       "      <td>5142</td>\n",
       "      <td>...</td>\n",
       "      <td>415.0</td>\n",
       "      <td>442.0</td>\n",
       "      <td>476.0</td>\n",
       "      <td>425</td>\n",
       "      <td>422</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>AF</td>\n",
       "      <td>2</td>\n",
       "      <td>2513</td>\n",
       "      <td>Barley and products</td>\n",
       "      <td>5521</td>\n",
       "      <td>...</td>\n",
       "      <td>379.0</td>\n",
       "      <td>315.0</td>\n",
       "      <td>203.0</td>\n",
       "      <td>367</td>\n",
       "      <td>360</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>AF</td>\n",
       "      <td>2</td>\n",
       "      <td>2513</td>\n",
       "      <td>Barley and products</td>\n",
       "      <td>5142</td>\n",
       "      <td>...</td>\n",
       "      <td>55.0</td>\n",
       "      <td>60.0</td>\n",
       "      <td>72.0</td>\n",
       "      <td>78</td>\n",
       "      <td>89</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>AF</td>\n",
       "      <td>2</td>\n",
       "      <td>2514</td>\n",
       "      <td>Maize and products</td>\n",
       "      <td>5521</td>\n",
       "      <td>...</td>\n",
       "      <td>195.0</td>\n",
       "      <td>178.0</td>\n",
       "      <td>191.0</td>\n",
       "      <td>200</td>\n",
       "      <td>200</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21472</th>\n",
       "      <td>ZW</td>\n",
       "      <td>181</td>\n",
       "      <td>2948</td>\n",
       "      <td>Milk - Excluding Butter</td>\n",
       "      <td>5142</td>\n",
       "      <td>...</td>\n",
       "      <td>385.0</td>\n",
       "      <td>418.0</td>\n",
       "      <td>457.0</td>\n",
       "      <td>426</td>\n",
       "      <td>451</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21473</th>\n",
       "      <td>ZW</td>\n",
       "      <td>181</td>\n",
       "      <td>2960</td>\n",
       "      <td>Fish, Seafood</td>\n",
       "      <td>5521</td>\n",
       "      <td>...</td>\n",
       "      <td>5.0</td>\n",
       "      <td>15.0</td>\n",
       "      <td>15.0</td>\n",
       "      <td>15</td>\n",
       "      <td>15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21474</th>\n",
       "      <td>ZW</td>\n",
       "      <td>181</td>\n",
       "      <td>2960</td>\n",
       "      <td>Fish, Seafood</td>\n",
       "      <td>5142</td>\n",
       "      <td>...</td>\n",
       "      <td>18.0</td>\n",
       "      <td>29.0</td>\n",
       "      <td>40.0</td>\n",
       "      <td>40</td>\n",
       "      <td>40</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21475</th>\n",
       "      <td>ZW</td>\n",
       "      <td>181</td>\n",
       "      <td>2961</td>\n",
       "      <td>Aquatic Products, Other</td>\n",
       "      <td>5142</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21476</th>\n",
       "      <td>ZW</td>\n",
       "      <td>181</td>\n",
       "      <td>2928</td>\n",
       "      <td>Miscellaneous</td>\n",
       "      <td>5142</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>21477 rows × 62 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      Area Abbreviation  Area Code  Item Code                      Item  \\\n",
       "0                    AF          2       2511        Wheat and products   \n",
       "1                    AF          2       2805  Rice (Milled Equivalent)   \n",
       "2                    AF          2       2513       Barley and products   \n",
       "3                    AF          2       2513       Barley and products   \n",
       "4                    AF          2       2514        Maize and products   \n",
       "...                 ...        ...        ...                       ...   \n",
       "21472                ZW        181       2948   Milk - Excluding Butter   \n",
       "21473                ZW        181       2960             Fish, Seafood   \n",
       "21474                ZW        181       2960             Fish, Seafood   \n",
       "21475                ZW        181       2961   Aquatic Products, Other   \n",
       "21476                ZW        181       2928             Miscellaneous   \n",
       "\n",
       "       Element Code  ...   Y2009   Y2010   Y2011  Y2012  Y2013  \n",
       "0              5142  ...  4538.0  4605.0  4711.0   4810   4895  \n",
       "1              5142  ...   415.0   442.0   476.0    425    422  \n",
       "2              5521  ...   379.0   315.0   203.0    367    360  \n",
       "3              5142  ...    55.0    60.0    72.0     78     89  \n",
       "4              5521  ...   195.0   178.0   191.0    200    200  \n",
       "...             ...  ...     ...     ...     ...    ...    ...  \n",
       "21472          5142  ...   385.0   418.0   457.0    426    451  \n",
       "21473          5521  ...     5.0    15.0    15.0     15     15  \n",
       "21474          5142  ...    18.0    29.0    40.0     40     40  \n",
       "21475          5142  ...     0.0     0.0     0.0      0      0  \n",
       "21476          5142  ...     0.0     0.0     0.0      0      0  \n",
       "\n",
       "[21477 rows x 62 columns]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "Index(['Area Abbreviation', 'Area Code', 'Area', 'Item Code', 'Item',\n",
       "       'Element Code', 'Element', 'Unit', 'latitude', 'longitude', 'Y1961',\n",
       "       'Y1962', 'Y1963', 'Y1964', 'Y1965', 'Y1966', 'Y1967', 'Y1968', 'Y1969',\n",
       "       'Y1970', 'Y1971', 'Y1972', 'Y1973', 'Y1974', 'Y1975', 'Y1976', 'Y1977',\n",
       "       'Y1978', 'Y1979', 'Y1980', 'Y1981', 'Y1982', 'Y1983', 'Y1984', 'Y1985',\n",
       "       'Y1986', 'Y1987', 'Y1988', 'Y1989', 'Y1990', 'Y1991', 'Y1992', 'Y1993',\n",
       "       'Y1994', 'Y1995', 'Y1996', 'Y1997', 'Y1998', 'Y1999', 'Y2000', 'Y2001',\n",
       "       'Y2002', 'Y2003', 'Y2004', 'Y2005', 'Y2006', 'Y2007', 'Y2008', 'Y2009',\n",
       "       'Y2010', 'Y2011', 'Y2012', 'Y2013'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 57,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# alternatively, delete columns using the columns parameter of drop\n",
    "df_rel.drop(columns=\"Area\")\n",
    "display(df_rel.drop(columns=\"Area\"))\n",
    "df_rel.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-03-15T06:56:23.843247Z",
     "start_time": "2021-03-15T06:56:23.815298Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['Area Abbreviation', 'Area Code', 'Item Code', 'Item', 'Element Code',\n",
       "       'Element', 'Unit', 'latitude', 'longitude', 'Y1961', 'Y1962', 'Y1963',\n",
       "       'Y1964', 'Y1965', 'Y1966', 'Y1967', 'Y1968', 'Y1969', 'Y1970', 'Y1971',\n",
       "       'Y1972', 'Y1973', 'Y1974', 'Y1975', 'Y1976', 'Y1977', 'Y1978', 'Y1979',\n",
       "       'Y1980', 'Y1981', 'Y1982', 'Y1983', 'Y1984', 'Y1985', 'Y1986', 'Y1987',\n",
       "       'Y1988', 'Y1989', 'Y1990', 'Y1991', 'Y1992', 'Y1993', 'Y1994', 'Y1995',\n",
       "       'Y1996', 'Y1997', 'Y1998', 'Y1999', 'Y2000', 'Y2001', 'Y2002', 'Y2003',\n",
       "       'Y2004', 'Y2005', 'Y2006', 'Y2007', 'Y2008', 'Y2009', 'Y2010', 'Y2011',\n",
       "       'Y2012', 'Y2013'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 58,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Delete the Area column from the dataframe and the original 'data' object is changed when inplace=True\n",
    "df_test = df_rel.copy()\n",
    "df_test.drop(\"Area\", axis=1, inplace=True)\n",
    "# is same as\n",
    "# df_test = df_test.drop('Area', axis=1)\n",
    "df_test.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-03-15T06:56:23.873139Z",
     "start_time": "2021-03-15T06:56:23.845216Z"
    }
   },
   "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>Area Abbreviation</th>\n",
       "      <th>Area Code</th>\n",
       "      <th>Area</th>\n",
       "      <th>Item Code</th>\n",
       "      <th>Item</th>\n",
       "      <th>...</th>\n",
       "      <th>Y2006</th>\n",
       "      <th>Y2007</th>\n",
       "      <th>Y2008</th>\n",
       "      <th>Y2009</th>\n",
       "      <th>Y2010</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>AF</td>\n",
       "      <td>2</td>\n",
       "      <td>Afghanistan</td>\n",
       "      <td>2511</td>\n",
       "      <td>Wheat and products</td>\n",
       "      <td>...</td>\n",
       "      <td>3704.0</td>\n",
       "      <td>4164.0</td>\n",
       "      <td>4252.0</td>\n",
       "      <td>4538.0</td>\n",
       "      <td>4605.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>AF</td>\n",
       "      <td>2</td>\n",
       "      <td>Afghanistan</td>\n",
       "      <td>2805</td>\n",
       "      <td>Rice (Milled Equivalent)</td>\n",
       "      <td>...</td>\n",
       "      <td>546.0</td>\n",
       "      <td>455.0</td>\n",
       "      <td>490.0</td>\n",
       "      <td>415.0</td>\n",
       "      <td>442.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>AF</td>\n",
       "      <td>2</td>\n",
       "      <td>Afghanistan</td>\n",
       "      <td>2513</td>\n",
       "      <td>Barley and products</td>\n",
       "      <td>...</td>\n",
       "      <td>262.0</td>\n",
       "      <td>263.0</td>\n",
       "      <td>230.0</td>\n",
       "      <td>379.0</td>\n",
       "      <td>315.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>AF</td>\n",
       "      <td>2</td>\n",
       "      <td>Afghanistan</td>\n",
       "      <td>2513</td>\n",
       "      <td>Barley and products</td>\n",
       "      <td>...</td>\n",
       "      <td>44.0</td>\n",
       "      <td>48.0</td>\n",
       "      <td>62.0</td>\n",
       "      <td>55.0</td>\n",
       "      <td>60.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>AF</td>\n",
       "      <td>2</td>\n",
       "      <td>Afghanistan</td>\n",
       "      <td>2514</td>\n",
       "      <td>Maize and products</td>\n",
       "      <td>...</td>\n",
       "      <td>233.0</td>\n",
       "      <td>249.0</td>\n",
       "      <td>247.0</td>\n",
       "      <td>195.0</td>\n",
       "      <td>178.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21472</th>\n",
       "      <td>ZW</td>\n",
       "      <td>181</td>\n",
       "      <td>Zimbabwe</td>\n",
       "      <td>2948</td>\n",
       "      <td>Milk - Excluding Butter</td>\n",
       "      <td>...</td>\n",
       "      <td>359.0</td>\n",
       "      <td>356.0</td>\n",
       "      <td>341.0</td>\n",
       "      <td>385.0</td>\n",
       "      <td>418.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21473</th>\n",
       "      <td>ZW</td>\n",
       "      <td>181</td>\n",
       "      <td>Zimbabwe</td>\n",
       "      <td>2960</td>\n",
       "      <td>Fish, Seafood</td>\n",
       "      <td>...</td>\n",
       "      <td>9.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>15.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21474</th>\n",
       "      <td>ZW</td>\n",
       "      <td>181</td>\n",
       "      <td>Zimbabwe</td>\n",
       "      <td>2960</td>\n",
       "      <td>Fish, Seafood</td>\n",
       "      <td>...</td>\n",
       "      <td>17.0</td>\n",
       "      <td>14.0</td>\n",
       "      <td>15.0</td>\n",
       "      <td>18.0</td>\n",
       "      <td>29.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21475</th>\n",
       "      <td>ZW</td>\n",
       "      <td>181</td>\n",
       "      <td>Zimbabwe</td>\n",
       "      <td>2961</td>\n",
       "      <td>Aquatic Products, Other</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21476</th>\n",
       "      <td>ZW</td>\n",
       "      <td>181</td>\n",
       "      <td>Zimbabwe</td>\n",
       "      <td>2928</td>\n",
       "      <td>Miscellaneous</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>21477 rows × 60 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      Area Abbreviation  Area Code         Area  Item Code  \\\n",
       "0                    AF          2  Afghanistan       2511   \n",
       "1                    AF          2  Afghanistan       2805   \n",
       "2                    AF          2  Afghanistan       2513   \n",
       "3                    AF          2  Afghanistan       2513   \n",
       "4                    AF          2  Afghanistan       2514   \n",
       "...                 ...        ...          ...        ...   \n",
       "21472                ZW        181     Zimbabwe       2948   \n",
       "21473                ZW        181     Zimbabwe       2960   \n",
       "21474                ZW        181     Zimbabwe       2960   \n",
       "21475                ZW        181     Zimbabwe       2961   \n",
       "21476                ZW        181     Zimbabwe       2928   \n",
       "\n",
       "                           Item  ...   Y2006   Y2007   Y2008   Y2009   Y2010  \n",
       "0            Wheat and products  ...  3704.0  4164.0  4252.0  4538.0  4605.0  \n",
       "1      Rice (Milled Equivalent)  ...   546.0   455.0   490.0   415.0   442.0  \n",
       "2           Barley and products  ...   262.0   263.0   230.0   379.0   315.0  \n",
       "3           Barley and products  ...    44.0    48.0    62.0    55.0    60.0  \n",
       "4            Maize and products  ...   233.0   249.0   247.0   195.0   178.0  \n",
       "...                         ...  ...     ...     ...     ...     ...     ...  \n",
       "21472   Milk - Excluding Butter  ...   359.0   356.0   341.0   385.0   418.0  \n",
       "21473             Fish, Seafood  ...     9.0     6.0     9.0     5.0    15.0  \n",
       "21474             Fish, Seafood  ...    17.0    14.0    15.0    18.0    29.0  \n",
       "21475   Aquatic Products, Other  ...     0.0     0.0     0.0     0.0     0.0  \n",
       "21476             Miscellaneous  ...     0.0     0.0     0.0     0.0     0.0  \n",
       "\n",
       "[21477 rows x 60 columns]"
      ]
     },
     "execution_count": 59,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Delete multiple columns from the dataframe\n",
    "df_rel.drop([\"Y2011\", \"Y2012\", \"Y2013\"], axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-03-15T06:56:23.903058Z",
     "start_time": "2021-03-15T06:56:23.874138Z"
    }
   },
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Area Abbreviation</th>\n",
       "      <th>Area Code</th>\n",
       "      <th>Area</th>\n",
       "      <th>Item Code</th>\n",
       "      <th>Item</th>\n",
       "      <th>...</th>\n",
       "      <th>Y2009</th>\n",
       "      <th>Y2010</th>\n",
       "      <th>Y2011</th>\n",
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       "      <th>Y2013</th>\n",
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       "      <th>2</th>\n",
       "      <td>AF</td>\n",
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       "      <td>Afghanistan</td>\n",
       "      <td>2513</td>\n",
       "      <td>Barley and products</td>\n",
       "      <td>...</td>\n",
       "      <td>379.0</td>\n",
       "      <td>315.0</td>\n",
       "      <td>203.0</td>\n",
       "      <td>367</td>\n",
       "      <td>360</td>\n",
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       "      <th>3</th>\n",
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       "      <td>55.0</td>\n",
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       "      <td>72.0</td>\n",
       "      <td>78</td>\n",
       "      <td>89</td>\n",
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       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>AF</td>\n",
       "      <td>2</td>\n",
       "      <td>Afghanistan</td>\n",
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       "      <td>Maize and products</td>\n",
       "      <td>...</td>\n",
       "      <td>195.0</td>\n",
       "      <td>178.0</td>\n",
       "      <td>191.0</td>\n",
       "      <td>200</td>\n",
       "      <td>200</td>\n",
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       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>AF</td>\n",
       "      <td>2</td>\n",
       "      <td>Afghanistan</td>\n",
       "      <td>2517</td>\n",
       "      <td>Millet and products</td>\n",
       "      <td>...</td>\n",
       "      <td>18.0</td>\n",
       "      <td>14.0</td>\n",
       "      <td>14.0</td>\n",
       "      <td>14</td>\n",
       "      <td>12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>AF</td>\n",
       "      <td>2</td>\n",
       "      <td>Afghanistan</td>\n",
       "      <td>2520</td>\n",
       "      <td>Cereals, Other</td>\n",
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       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21472</th>\n",
       "      <td>ZW</td>\n",
       "      <td>181</td>\n",
       "      <td>Zimbabwe</td>\n",
       "      <td>2948</td>\n",
       "      <td>Milk - Excluding Butter</td>\n",
       "      <td>...</td>\n",
       "      <td>385.0</td>\n",
       "      <td>418.0</td>\n",
       "      <td>457.0</td>\n",
       "      <td>426</td>\n",
       "      <td>451</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21473</th>\n",
       "      <td>ZW</td>\n",
       "      <td>181</td>\n",
       "      <td>Zimbabwe</td>\n",
       "      <td>2960</td>\n",
       "      <td>Fish, Seafood</td>\n",
       "      <td>...</td>\n",
       "      <td>5.0</td>\n",
       "      <td>15.0</td>\n",
       "      <td>15.0</td>\n",
       "      <td>15</td>\n",
       "      <td>15</td>\n",
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       "    <tr>\n",
       "      <th>21474</th>\n",
       "      <td>ZW</td>\n",
       "      <td>181</td>\n",
       "      <td>Zimbabwe</td>\n",
       "      <td>2960</td>\n",
       "      <td>Fish, Seafood</td>\n",
       "      <td>...</td>\n",
       "      <td>18.0</td>\n",
       "      <td>29.0</td>\n",
       "      <td>40.0</td>\n",
       "      <td>40</td>\n",
       "      <td>40</td>\n",
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       "    <tr>\n",
       "      <th>21475</th>\n",
       "      <td>ZW</td>\n",
       "      <td>181</td>\n",
       "      <td>Zimbabwe</td>\n",
       "      <td>2961</td>\n",
       "      <td>Aquatic Products, Other</td>\n",
       "      <td>...</td>\n",
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       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
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       "    <tr>\n",
       "      <th>21476</th>\n",
       "      <td>ZW</td>\n",
       "      <td>181</td>\n",
       "      <td>Zimbabwe</td>\n",
       "      <td>2928</td>\n",
       "      <td>Miscellaneous</td>\n",
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       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
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       "</table>\n",
       "<p>21474 rows × 63 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      Area Abbreviation  Area Code         Area  Item Code  \\\n",
       "2                    AF          2  Afghanistan       2513   \n",
       "3                    AF          2  Afghanistan       2513   \n",
       "4                    AF          2  Afghanistan       2514   \n",
       "6                    AF          2  Afghanistan       2517   \n",
       "7                    AF          2  Afghanistan       2520   \n",
       "...                 ...        ...          ...        ...   \n",
       "21472                ZW        181     Zimbabwe       2948   \n",
       "21473                ZW        181     Zimbabwe       2960   \n",
       "21474                ZW        181     Zimbabwe       2960   \n",
       "21475                ZW        181     Zimbabwe       2961   \n",
       "21476                ZW        181     Zimbabwe       2928   \n",
       "\n",
       "                          Item  ...  Y2009  Y2010  Y2011  Y2012  Y2013  \n",
       "2          Barley and products  ...  379.0  315.0  203.0    367    360  \n",
       "3          Barley and products  ...   55.0   60.0   72.0     78     89  \n",
       "4           Maize and products  ...  195.0  178.0  191.0    200    200  \n",
       "6          Millet and products  ...   18.0   14.0   14.0     14     12  \n",
       "7               Cereals, Other  ...    0.0    0.0    0.0      0      0  \n",
       "...                        ...  ...    ...    ...    ...    ...    ...  \n",
       "21472  Milk - Excluding Butter  ...  385.0  418.0  457.0    426    451  \n",
       "21473            Fish, Seafood  ...    5.0   15.0   15.0     15     15  \n",
       "21474            Fish, Seafood  ...   18.0   29.0   40.0     40     40  \n",
       "21475  Aquatic Products, Other  ...    0.0    0.0    0.0      0      0  \n",
       "21476            Miscellaneous  ...    0.0    0.0    0.0      0      0  \n",
       "\n",
       "[21474 rows x 63 columns]"
      ]
     },
     "execution_count": 60,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Delete the rows with labels 0,1,5\n",
    "df_rel.drop([0,1,5], axis=0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-03-15T06:56:23.932979Z",
     "start_time": "2021-03-15T06:56:23.904056Z"
    }
   },
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Area Abbreviation</th>\n",
       "      <th>Area Code</th>\n",
       "      <th>Area</th>\n",
       "      <th>Item Code</th>\n",
       "      <th>Item</th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>AF</td>\n",
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       "      <td>Afghanistan</td>\n",
       "      <td>2514</td>\n",
       "      <td>Maize and products</td>\n",
       "      <td>...</td>\n",
       "      <td>71.0</td>\n",
       "      <td>82.0</td>\n",
       "      <td>73.0</td>\n",
       "      <td>77</td>\n",
       "      <td>76</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
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       "      <td>12</td>\n",
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       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>AF</td>\n",
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       "      <td>0</td>\n",
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       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>AF</td>\n",
       "      <td>2</td>\n",
       "      <td>Afghanistan</td>\n",
       "      <td>2531</td>\n",
       "      <td>Potatoes and products</td>\n",
       "      <td>...</td>\n",
       "      <td>250.0</td>\n",
       "      <td>192.0</td>\n",
       "      <td>169.0</td>\n",
       "      <td>196</td>\n",
       "      <td>230</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>AF</td>\n",
       "      <td>2</td>\n",
       "      <td>Afghanistan</td>\n",
       "      <td>2536</td>\n",
       "      <td>Sugar cane</td>\n",
       "      <td>...</td>\n",
       "      <td>114.0</td>\n",
       "      <td>83.0</td>\n",
       "      <td>83.0</td>\n",
       "      <td>69</td>\n",
       "      <td>81</td>\n",
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       "    <tr>\n",
       "      <th>...</th>\n",
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       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
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       "    <tr>\n",
       "      <th>21472</th>\n",
       "      <td>ZW</td>\n",
       "      <td>181</td>\n",
       "      <td>Zimbabwe</td>\n",
       "      <td>2948</td>\n",
       "      <td>Milk - Excluding Butter</td>\n",
       "      <td>...</td>\n",
       "      <td>385.0</td>\n",
       "      <td>418.0</td>\n",
       "      <td>457.0</td>\n",
       "      <td>426</td>\n",
       "      <td>451</td>\n",
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       "    <tr>\n",
       "      <th>21473</th>\n",
       "      <td>ZW</td>\n",
       "      <td>181</td>\n",
       "      <td>Zimbabwe</td>\n",
       "      <td>2960</td>\n",
       "      <td>Fish, Seafood</td>\n",
       "      <td>...</td>\n",
       "      <td>5.0</td>\n",
       "      <td>15.0</td>\n",
       "      <td>15.0</td>\n",
       "      <td>15</td>\n",
       "      <td>15</td>\n",
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       "    <tr>\n",
       "      <th>21474</th>\n",
       "      <td>ZW</td>\n",
       "      <td>181</td>\n",
       "      <td>Zimbabwe</td>\n",
       "      <td>2960</td>\n",
       "      <td>Fish, Seafood</td>\n",
       "      <td>...</td>\n",
       "      <td>18.0</td>\n",
       "      <td>29.0</td>\n",
       "      <td>40.0</td>\n",
       "      <td>40</td>\n",
       "      <td>40</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21475</th>\n",
       "      <td>ZW</td>\n",
       "      <td>181</td>\n",
       "      <td>Zimbabwe</td>\n",
       "      <td>2961</td>\n",
       "      <td>Aquatic Products, Other</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
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       "    <tr>\n",
       "      <th>21476</th>\n",
       "      <td>ZW</td>\n",
       "      <td>181</td>\n",
       "      <td>Zimbabwe</td>\n",
       "      <td>2928</td>\n",
       "      <td>Miscellaneous</td>\n",
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       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
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       "</table>\n",
       "<p>21472 rows × 63 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      Area Abbreviation  Area Code         Area  Item Code  \\\n",
       "5                    AF          2  Afghanistan       2514   \n",
       "6                    AF          2  Afghanistan       2517   \n",
       "7                    AF          2  Afghanistan       2520   \n",
       "8                    AF          2  Afghanistan       2531   \n",
       "9                    AF          2  Afghanistan       2536   \n",
       "...                 ...        ...          ...        ...   \n",
       "21472                ZW        181     Zimbabwe       2948   \n",
       "21473                ZW        181     Zimbabwe       2960   \n",
       "21474                ZW        181     Zimbabwe       2960   \n",
       "21475                ZW        181     Zimbabwe       2961   \n",
       "21476                ZW        181     Zimbabwe       2928   \n",
       "\n",
       "                          Item  ...  Y2009  Y2010  Y2011  Y2012  Y2013  \n",
       "5           Maize and products  ...   71.0   82.0   73.0     77     76  \n",
       "6          Millet and products  ...   18.0   14.0   14.0     14     12  \n",
       "7               Cereals, Other  ...    0.0    0.0    0.0      0      0  \n",
       "8        Potatoes and products  ...  250.0  192.0  169.0    196    230  \n",
       "9                   Sugar cane  ...  114.0   83.0   83.0     69     81  \n",
       "...                        ...  ...    ...    ...    ...    ...    ...  \n",
       "21472  Milk - Excluding Butter  ...  385.0  418.0  457.0    426    451  \n",
       "21473            Fish, Seafood  ...    5.0   15.0   15.0     15     15  \n",
       "21474            Fish, Seafood  ...   18.0   29.0   40.0     40     40  \n",
       "21475  Aquatic Products, Other  ...    0.0    0.0    0.0      0      0  \n",
       "21476            Miscellaneous  ...    0.0    0.0    0.0      0      0  \n",
       "\n",
       "[21472 rows x 63 columns]"
      ]
     },
     "execution_count": 61,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Delete the first five rows using iloc selector\n",
    "df_rel.iloc[5:,]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 행과 열의 이름바꾸기(Renaming)\n",
    "\n",
    "- **행 이름 변경**\n",
    "> - DataFrame.index = \"값\" 형태로 수정 가능(\"값\"의 길이는 index의 길이와 같아야 함)\n",
    "> - DataFrame.set_index(column_name) 함수로 특정 column을 index로 반영 가능\n",
    "> - DataFrame.reset_index(...) 함수로 초기 index로 변경 가능\n",
    "\n",
    "- **열 이름 변경**\n",
    "> - DataFrame.columns = \"값\" 형태로 수정 가능(\"값\"의 길이는 column의 길이와 같아야 함)\n",
    "> - DataFrame.rename(columns={'Old':'New'}) 함수로 쉽게 수행 가능\n",
    "> - {'old_column_name': 'new_column_name',…} 형식으로 이전이름과 새이름을 dictionary 형태로 mapping하여 변경\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-03-15T06:56:23.947941Z",
     "start_time": "2021-03-15T06:56:23.933977Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "RangeIndex(start=0, stop=21477, step=1)"
      ]
     },
     "execution_count": 62,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_rel.index"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-03-15T06:56:23.977858Z",
     "start_time": "2021-03-15T06:56:23.950932Z"
    }
   },
   "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>Area Abbreviation</th>\n",
       "      <th>Area Code</th>\n",
       "      <th>Area</th>\n",
       "      <th>Item Code</th>\n",
       "      <th>Item</th>\n",
       "      <th>...</th>\n",
       "      <th>Y2009</th>\n",
       "      <th>Y2010</th>\n",
       "      <th>Y2011</th>\n",
       "      <th>Y2012</th>\n",
       "      <th>Y2013</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>100</th>\n",
       "      <td>AF</td>\n",
       "      <td>2</td>\n",
       "      <td>Afghanistan</td>\n",
       "      <td>2511</td>\n",
       "      <td>Wheat and products</td>\n",
       "      <td>...</td>\n",
       "      <td>4538.0</td>\n",
       "      <td>4605.0</td>\n",
       "      <td>4711.0</td>\n",
       "      <td>4810</td>\n",
       "      <td>4895</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>101</th>\n",
       "      <td>AF</td>\n",
       "      <td>2</td>\n",
       "      <td>Afghanistan</td>\n",
       "      <td>2805</td>\n",
       "      <td>Rice (Milled Equivalent)</td>\n",
       "      <td>...</td>\n",
       "      <td>415.0</td>\n",
       "      <td>442.0</td>\n",
       "      <td>476.0</td>\n",
       "      <td>425</td>\n",
       "      <td>422</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>102</th>\n",
       "      <td>AF</td>\n",
       "      <td>2</td>\n",
       "      <td>Afghanistan</td>\n",
       "      <td>2513</td>\n",
       "      <td>Barley and products</td>\n",
       "      <td>...</td>\n",
       "      <td>379.0</td>\n",
       "      <td>315.0</td>\n",
       "      <td>203.0</td>\n",
       "      <td>367</td>\n",
       "      <td>360</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>103</th>\n",
       "      <td>AF</td>\n",
       "      <td>2</td>\n",
       "      <td>Afghanistan</td>\n",
       "      <td>2513</td>\n",
       "      <td>Barley and products</td>\n",
       "      <td>...</td>\n",
       "      <td>55.0</td>\n",
       "      <td>60.0</td>\n",
       "      <td>72.0</td>\n",
       "      <td>78</td>\n",
       "      <td>89</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>104</th>\n",
       "      <td>AF</td>\n",
       "      <td>2</td>\n",
       "      <td>Afghanistan</td>\n",
       "      <td>2514</td>\n",
       "      <td>Maize and products</td>\n",
       "      <td>...</td>\n",
       "      <td>195.0</td>\n",
       "      <td>178.0</td>\n",
       "      <td>191.0</td>\n",
       "      <td>200</td>\n",
       "      <td>200</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21572</th>\n",
       "      <td>ZW</td>\n",
       "      <td>181</td>\n",
       "      <td>Zimbabwe</td>\n",
       "      <td>2948</td>\n",
       "      <td>Milk - Excluding Butter</td>\n",
       "      <td>...</td>\n",
       "      <td>385.0</td>\n",
       "      <td>418.0</td>\n",
       "      <td>457.0</td>\n",
       "      <td>426</td>\n",
       "      <td>451</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21573</th>\n",
       "      <td>ZW</td>\n",
       "      <td>181</td>\n",
       "      <td>Zimbabwe</td>\n",
       "      <td>2960</td>\n",
       "      <td>Fish, Seafood</td>\n",
       "      <td>...</td>\n",
       "      <td>5.0</td>\n",
       "      <td>15.0</td>\n",
       "      <td>15.0</td>\n",
       "      <td>15</td>\n",
       "      <td>15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21574</th>\n",
       "      <td>ZW</td>\n",
       "      <td>181</td>\n",
       "      <td>Zimbabwe</td>\n",
       "      <td>2960</td>\n",
       "      <td>Fish, Seafood</td>\n",
       "      <td>...</td>\n",
       "      <td>18.0</td>\n",
       "      <td>29.0</td>\n",
       "      <td>40.0</td>\n",
       "      <td>40</td>\n",
       "      <td>40</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21575</th>\n",
       "      <td>ZW</td>\n",
       "      <td>181</td>\n",
       "      <td>Zimbabwe</td>\n",
       "      <td>2961</td>\n",
       "      <td>Aquatic Products, Other</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21576</th>\n",
       "      <td>ZW</td>\n",
       "      <td>181</td>\n",
       "      <td>Zimbabwe</td>\n",
       "      <td>2928</td>\n",
       "      <td>Miscellaneous</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>21477 rows × 63 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      Area Abbreviation  Area Code         Area  Item Code  \\\n",
       "100                  AF          2  Afghanistan       2511   \n",
       "101                  AF          2  Afghanistan       2805   \n",
       "102                  AF          2  Afghanistan       2513   \n",
       "103                  AF          2  Afghanistan       2513   \n",
       "104                  AF          2  Afghanistan       2514   \n",
       "...                 ...        ...          ...        ...   \n",
       "21572                ZW        181     Zimbabwe       2948   \n",
       "21573                ZW        181     Zimbabwe       2960   \n",
       "21574                ZW        181     Zimbabwe       2960   \n",
       "21575                ZW        181     Zimbabwe       2961   \n",
       "21576                ZW        181     Zimbabwe       2928   \n",
       "\n",
       "                           Item  ...   Y2009   Y2010   Y2011  Y2012  Y2013  \n",
       "100          Wheat and products  ...  4538.0  4605.0  4711.0   4810   4895  \n",
       "101    Rice (Milled Equivalent)  ...   415.0   442.0   476.0    425    422  \n",
       "102         Barley and products  ...   379.0   315.0   203.0    367    360  \n",
       "103         Barley and products  ...    55.0    60.0    72.0     78     89  \n",
       "104          Maize and products  ...   195.0   178.0   191.0    200    200  \n",
       "...                         ...  ...     ...     ...     ...    ...    ...  \n",
       "21572   Milk - Excluding Butter  ...   385.0   418.0   457.0    426    451  \n",
       "21573             Fish, Seafood  ...     5.0    15.0    15.0     15     15  \n",
       "21574             Fish, Seafood  ...    18.0    29.0    40.0     40     40  \n",
       "21575   Aquatic Products, Other  ...     0.0     0.0     0.0      0      0  \n",
       "21576             Miscellaneous  ...     0.0     0.0     0.0      0      0  \n",
       "\n",
       "[21477 rows x 63 columns]"
      ]
     },
     "execution_count": 63,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# set index as other values\n",
    "df_rel.index = range(100,21577)\n",
    "df_rel"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-03-15T06:56:24.022738Z",
     "start_time": "2021-03-15T06:56:23.979856Z"
    }
   },
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Area Abbreviation</th>\n",
       "      <th>Area Code</th>\n",
       "      <th>Item Code</th>\n",
       "      <th>Item</th>\n",
       "      <th>Element Code</th>\n",
       "      <th>...</th>\n",
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       "    <tr>\n",
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       "      <th></th>\n",
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       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
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       "  <tbody>\n",
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       "      <th>Afghanistan</th>\n",
       "      <td>AF</td>\n",
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       "      <td>2511</td>\n",
       "      <td>Wheat and products</td>\n",
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       "      <td>...</td>\n",
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       "      <td>4711.0</td>\n",
       "      <td>4810</td>\n",
       "      <td>4895</td>\n",
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       "    <tr>\n",
       "      <th>Afghanistan</th>\n",
       "      <td>AF</td>\n",
       "      <td>2</td>\n",
       "      <td>2805</td>\n",
       "      <td>Rice (Milled Equivalent)</td>\n",
       "      <td>5142</td>\n",
       "      <td>...</td>\n",
       "      <td>415.0</td>\n",
       "      <td>442.0</td>\n",
       "      <td>476.0</td>\n",
       "      <td>425</td>\n",
       "      <td>422</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Afghanistan</th>\n",
       "      <td>AF</td>\n",
       "      <td>2</td>\n",
       "      <td>2513</td>\n",
       "      <td>Barley and products</td>\n",
       "      <td>5521</td>\n",
       "      <td>...</td>\n",
       "      <td>379.0</td>\n",
       "      <td>315.0</td>\n",
       "      <td>203.0</td>\n",
       "      <td>367</td>\n",
       "      <td>360</td>\n",
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       "    <tr>\n",
       "      <th>Afghanistan</th>\n",
       "      <td>AF</td>\n",
       "      <td>2</td>\n",
       "      <td>2513</td>\n",
       "      <td>Barley and products</td>\n",
       "      <td>5142</td>\n",
       "      <td>...</td>\n",
       "      <td>55.0</td>\n",
       "      <td>60.0</td>\n",
       "      <td>72.0</td>\n",
       "      <td>78</td>\n",
       "      <td>89</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Afghanistan</th>\n",
       "      <td>AF</td>\n",
       "      <td>2</td>\n",
       "      <td>2514</td>\n",
       "      <td>Maize and products</td>\n",
       "      <td>5521</td>\n",
       "      <td>...</td>\n",
       "      <td>195.0</td>\n",
       "      <td>178.0</td>\n",
       "      <td>191.0</td>\n",
       "      <td>200</td>\n",
       "      <td>200</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Zimbabwe</th>\n",
       "      <td>ZW</td>\n",
       "      <td>181</td>\n",
       "      <td>2948</td>\n",
       "      <td>Milk - Excluding Butter</td>\n",
       "      <td>5142</td>\n",
       "      <td>...</td>\n",
       "      <td>385.0</td>\n",
       "      <td>418.0</td>\n",
       "      <td>457.0</td>\n",
       "      <td>426</td>\n",
       "      <td>451</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Zimbabwe</th>\n",
       "      <td>ZW</td>\n",
       "      <td>181</td>\n",
       "      <td>2960</td>\n",
       "      <td>Fish, Seafood</td>\n",
       "      <td>5521</td>\n",
       "      <td>...</td>\n",
       "      <td>5.0</td>\n",
       "      <td>15.0</td>\n",
       "      <td>15.0</td>\n",
       "      <td>15</td>\n",
       "      <td>15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Zimbabwe</th>\n",
       "      <td>ZW</td>\n",
       "      <td>181</td>\n",
       "      <td>2960</td>\n",
       "      <td>Fish, Seafood</td>\n",
       "      <td>5142</td>\n",
       "      <td>...</td>\n",
       "      <td>18.0</td>\n",
       "      <td>29.0</td>\n",
       "      <td>40.0</td>\n",
       "      <td>40</td>\n",
       "      <td>40</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Zimbabwe</th>\n",
       "      <td>ZW</td>\n",
       "      <td>181</td>\n",
       "      <td>2961</td>\n",
       "      <td>Aquatic Products, Other</td>\n",
       "      <td>5142</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Zimbabwe</th>\n",
       "      <td>ZW</td>\n",
       "      <td>181</td>\n",
       "      <td>2928</td>\n",
       "      <td>Miscellaneous</td>\n",
       "      <td>5142</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>21477 rows × 62 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "            Area Abbreviation  Area Code  Item Code                      Item  \\\n",
       "Area                                                                            \n",
       "Afghanistan                AF          2       2511        Wheat and products   \n",
       "Afghanistan                AF          2       2805  Rice (Milled Equivalent)   \n",
       "Afghanistan                AF          2       2513       Barley and products   \n",
       "Afghanistan                AF          2       2513       Barley and products   \n",
       "Afghanistan                AF          2       2514        Maize and products   \n",
       "...                       ...        ...        ...                       ...   \n",
       "Zimbabwe                   ZW        181       2948   Milk - Excluding Butter   \n",
       "Zimbabwe                   ZW        181       2960             Fish, Seafood   \n",
       "Zimbabwe                   ZW        181       2960             Fish, Seafood   \n",
       "Zimbabwe                   ZW        181       2961   Aquatic Products, Other   \n",
       "Zimbabwe                   ZW        181       2928             Miscellaneous   \n",
       "\n",
       "             Element Code  ...   Y2009   Y2010   Y2011  Y2012  Y2013  \n",
       "Area                       ...                                        \n",
       "Afghanistan          5142  ...  4538.0  4605.0  4711.0   4810   4895  \n",
       "Afghanistan          5142  ...   415.0   442.0   476.0    425    422  \n",
       "Afghanistan          5521  ...   379.0   315.0   203.0    367    360  \n",
       "Afghanistan          5142  ...    55.0    60.0    72.0     78     89  \n",
       "Afghanistan          5521  ...   195.0   178.0   191.0    200    200  \n",
       "...                   ...  ...     ...     ...     ...    ...    ...  \n",
       "Zimbabwe             5142  ...   385.0   418.0   457.0    426    451  \n",
       "Zimbabwe             5521  ...     5.0    15.0    15.0     15     15  \n",
       "Zimbabwe             5142  ...    18.0    29.0    40.0     40     40  \n",
       "Zimbabwe             5142  ...     0.0     0.0     0.0      0      0  \n",
       "Zimbabwe             5142  ...     0.0     0.0     0.0      0      0  \n",
       "\n",
       "[21477 rows x 62 columns]"
      ]
     },
     "execution_count": 64,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# set index as other columns\n",
    "df_rel.set_index(\"Area\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-03-15T06:56:24.067647Z",
     "start_time": "2021-03-15T06:56:24.023736Z"
    }
   },
   "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>Area Abbreviation</th>\n",
       "      <th>Area Code</th>\n",
       "      <th>Item Code</th>\n",
       "      <th>Item</th>\n",
       "      <th>Element Code</th>\n",
       "      <th>...</th>\n",
       "      <th>Y2009</th>\n",
       "      <th>Y2010</th>\n",
       "      <th>Y2011</th>\n",
       "      <th>Y2012</th>\n",
       "      <th>Y2013</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Area</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Albania</th>\n",
       "      <td>AL</td>\n",
       "      <td>3</td>\n",
       "      <td>2511</td>\n",
       "      <td>Wheat and products</td>\n",
       "      <td>5521</td>\n",
       "      <td>...</td>\n",
       "      <td>30.0</td>\n",
       "      <td>26.0</td>\n",
       "      <td>25.0</td>\n",
       "      <td>20</td>\n",
       "      <td>18</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Albania</th>\n",
       "      <td>AL</td>\n",
       "      <td>3</td>\n",
       "      <td>2511</td>\n",
       "      <td>Wheat and products</td>\n",
       "      <td>5142</td>\n",
       "      <td>...</td>\n",
       "      <td>415.0</td>\n",
       "      <td>432.0</td>\n",
       "      <td>439.0</td>\n",
       "      <td>440</td>\n",
       "      <td>440</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Albania</th>\n",
       "      <td>AL</td>\n",
       "      <td>3</td>\n",
       "      <td>2805</td>\n",
       "      <td>Rice (Milled Equivalent)</td>\n",
       "      <td>5521</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Albania</th>\n",
       "      <td>AL</td>\n",
       "      <td>3</td>\n",
       "      <td>2805</td>\n",
       "      <td>Rice (Milled Equivalent)</td>\n",
       "      <td>5142</td>\n",
       "      <td>...</td>\n",
       "      <td>23.0</td>\n",
       "      <td>24.0</td>\n",
       "      <td>21.0</td>\n",
       "      <td>22</td>\n",
       "      <td>25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Albania</th>\n",
       "      <td>AL</td>\n",
       "      <td>3</td>\n",
       "      <td>2513</td>\n",
       "      <td>Barley and products</td>\n",
       "      <td>5521</td>\n",
       "      <td>...</td>\n",
       "      <td>4.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>7</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Zimbabwe</th>\n",
       "      <td>ZW</td>\n",
       "      <td>181</td>\n",
       "      <td>2948</td>\n",
       "      <td>Milk - Excluding Butter</td>\n",
       "      <td>5142</td>\n",
       "      <td>...</td>\n",
       "      <td>385.0</td>\n",
       "      <td>418.0</td>\n",
       "      <td>457.0</td>\n",
       "      <td>426</td>\n",
       "      <td>451</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Zimbabwe</th>\n",
       "      <td>ZW</td>\n",
       "      <td>181</td>\n",
       "      <td>2960</td>\n",
       "      <td>Fish, Seafood</td>\n",
       "      <td>5521</td>\n",
       "      <td>...</td>\n",
       "      <td>5.0</td>\n",
       "      <td>15.0</td>\n",
       "      <td>15.0</td>\n",
       "      <td>15</td>\n",
       "      <td>15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Zimbabwe</th>\n",
       "      <td>ZW</td>\n",
       "      <td>181</td>\n",
       "      <td>2960</td>\n",
       "      <td>Fish, Seafood</td>\n",
       "      <td>5142</td>\n",
       "      <td>...</td>\n",
       "      <td>18.0</td>\n",
       "      <td>29.0</td>\n",
       "      <td>40.0</td>\n",
       "      <td>40</td>\n",
       "      <td>40</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Zimbabwe</th>\n",
       "      <td>ZW</td>\n",
       "      <td>181</td>\n",
       "      <td>2961</td>\n",
       "      <td>Aquatic Products, Other</td>\n",
       "      <td>5142</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Zimbabwe</th>\n",
       "      <td>ZW</td>\n",
       "      <td>181</td>\n",
       "      <td>2928</td>\n",
       "      <td>Miscellaneous</td>\n",
       "      <td>5142</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>21394 rows × 62 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "         Area Abbreviation  Area Code  Item Code                      Item  \\\n",
       "Area                                                                         \n",
       "Albania                 AL          3       2511        Wheat and products   \n",
       "Albania                 AL          3       2511        Wheat and products   \n",
       "Albania                 AL          3       2805  Rice (Milled Equivalent)   \n",
       "Albania                 AL          3       2805  Rice (Milled Equivalent)   \n",
       "Albania                 AL          3       2513       Barley and products   \n",
       "...                    ...        ...        ...                       ...   \n",
       "Zimbabwe                ZW        181       2948   Milk - Excluding Butter   \n",
       "Zimbabwe                ZW        181       2960             Fish, Seafood   \n",
       "Zimbabwe                ZW        181       2960             Fish, Seafood   \n",
       "Zimbabwe                ZW        181       2961   Aquatic Products, Other   \n",
       "Zimbabwe                ZW        181       2928             Miscellaneous   \n",
       "\n",
       "          Element Code  ...  Y2009  Y2010  Y2011  Y2012  Y2013  \n",
       "Area                    ...                                     \n",
       "Albania           5521  ...   30.0   26.0   25.0     20     18  \n",
       "Albania           5142  ...  415.0  432.0  439.0    440    440  \n",
       "Albania           5521  ...    0.0    0.0    0.0      0      0  \n",
       "Albania           5142  ...   23.0   24.0   21.0     22     25  \n",
       "Albania           5521  ...    4.0    7.0    8.0      7      7  \n",
       "...                ...  ...    ...    ...    ...    ...    ...  \n",
       "Zimbabwe          5142  ...  385.0  418.0  457.0    426    451  \n",
       "Zimbabwe          5521  ...    5.0   15.0   15.0     15     15  \n",
       "Zimbabwe          5142  ...   18.0   29.0   40.0     40     40  \n",
       "Zimbabwe          5142  ...    0.0    0.0    0.0      0      0  \n",
       "Zimbabwe          5142  ...    0.0    0.0    0.0      0      0  \n",
       "\n",
       "[21394 rows x 62 columns]"
      ]
     },
     "execution_count": 65,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Delete the rows with label \"Afghanistan\" by the label-based deletion\n",
    "df_rel.set_index(\"Area\").drop(\"Afghanistan\", axis=0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-03-15T06:56:24.097566Z",
     "start_time": "2021-03-15T06:56:24.068616Z"
    }
   },
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Area Abbreviation</th>\n",
       "      <th>Area Code</th>\n",
       "      <th>Area</th>\n",
       "      <th>Item Code</th>\n",
       "      <th>Item</th>\n",
       "      <th>...</th>\n",
       "      <th>Y2009</th>\n",
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       "      <th>Y2013</th>\n",
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       "    <tr>\n",
       "      <th>100</th>\n",
       "      <td>AF</td>\n",
       "      <td>2</td>\n",
       "      <td>Afghanistan</td>\n",
       "      <td>2511</td>\n",
       "      <td>Wheat and products</td>\n",
       "      <td>...</td>\n",
       "      <td>4538.0</td>\n",
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       "      <td>4895</td>\n",
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       "    <tr>\n",
       "      <th>101</th>\n",
       "      <td>AF</td>\n",
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       "      <td>Rice (Milled Equivalent)</td>\n",
       "      <td>...</td>\n",
       "      <td>415.0</td>\n",
       "      <td>442.0</td>\n",
       "      <td>476.0</td>\n",
       "      <td>425</td>\n",
       "      <td>422</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>102</th>\n",
       "      <td>AF</td>\n",
       "      <td>2</td>\n",
       "      <td>Afghanistan</td>\n",
       "      <td>2513</td>\n",
       "      <td>Barley and products</td>\n",
       "      <td>...</td>\n",
       "      <td>379.0</td>\n",
       "      <td>315.0</td>\n",
       "      <td>203.0</td>\n",
       "      <td>367</td>\n",
       "      <td>360</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>103</th>\n",
       "      <td>AF</td>\n",
       "      <td>2</td>\n",
       "      <td>Afghanistan</td>\n",
       "      <td>2513</td>\n",
       "      <td>Barley and products</td>\n",
       "      <td>...</td>\n",
       "      <td>55.0</td>\n",
       "      <td>60.0</td>\n",
       "      <td>72.0</td>\n",
       "      <td>78</td>\n",
       "      <td>89</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>104</th>\n",
       "      <td>AF</td>\n",
       "      <td>2</td>\n",
       "      <td>Afghanistan</td>\n",
       "      <td>2514</td>\n",
       "      <td>Maize and products</td>\n",
       "      <td>...</td>\n",
       "      <td>195.0</td>\n",
       "      <td>178.0</td>\n",
       "      <td>191.0</td>\n",
       "      <td>200</td>\n",
       "      <td>200</td>\n",
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       "    <tr>\n",
       "      <th>...</th>\n",
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       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21572</th>\n",
       "      <td>ZW</td>\n",
       "      <td>181</td>\n",
       "      <td>Zimbabwe</td>\n",
       "      <td>2948</td>\n",
       "      <td>Milk - Excluding Butter</td>\n",
       "      <td>...</td>\n",
       "      <td>385.0</td>\n",
       "      <td>418.0</td>\n",
       "      <td>457.0</td>\n",
       "      <td>426</td>\n",
       "      <td>451</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21573</th>\n",
       "      <td>ZW</td>\n",
       "      <td>181</td>\n",
       "      <td>Zimbabwe</td>\n",
       "      <td>2960</td>\n",
       "      <td>Fish, Seafood</td>\n",
       "      <td>...</td>\n",
       "      <td>5.0</td>\n",
       "      <td>15.0</td>\n",
       "      <td>15.0</td>\n",
       "      <td>15</td>\n",
       "      <td>15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21574</th>\n",
       "      <td>ZW</td>\n",
       "      <td>181</td>\n",
       "      <td>Zimbabwe</td>\n",
       "      <td>2960</td>\n",
       "      <td>Fish, Seafood</td>\n",
       "      <td>...</td>\n",
       "      <td>18.0</td>\n",
       "      <td>29.0</td>\n",
       "      <td>40.0</td>\n",
       "      <td>40</td>\n",
       "      <td>40</td>\n",
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       "    <tr>\n",
       "      <th>21575</th>\n",
       "      <td>ZW</td>\n",
       "      <td>181</td>\n",
       "      <td>Zimbabwe</td>\n",
       "      <td>2961</td>\n",
       "      <td>Aquatic Products, Other</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21576</th>\n",
       "      <td>ZW</td>\n",
       "      <td>181</td>\n",
       "      <td>Zimbabwe</td>\n",
       "      <td>2928</td>\n",
       "      <td>Miscellaneous</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>21477 rows × 63 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      Area Abbreviation  Area Code         Area  Item Code  \\\n",
       "100                  AF          2  Afghanistan       2511   \n",
       "101                  AF          2  Afghanistan       2805   \n",
       "102                  AF          2  Afghanistan       2513   \n",
       "103                  AF          2  Afghanistan       2513   \n",
       "104                  AF          2  Afghanistan       2514   \n",
       "...                 ...        ...          ...        ...   \n",
       "21572                ZW        181     Zimbabwe       2948   \n",
       "21573                ZW        181     Zimbabwe       2960   \n",
       "21574                ZW        181     Zimbabwe       2960   \n",
       "21575                ZW        181     Zimbabwe       2961   \n",
       "21576                ZW        181     Zimbabwe       2928   \n",
       "\n",
       "                           Item  ...   Y2009   Y2010   Y2011  Y2012  Y2013  \n",
       "100          Wheat and products  ...  4538.0  4605.0  4711.0   4810   4895  \n",
       "101    Rice (Milled Equivalent)  ...   415.0   442.0   476.0    425    422  \n",
       "102         Barley and products  ...   379.0   315.0   203.0    367    360  \n",
       "103         Barley and products  ...    55.0    60.0    72.0     78     89  \n",
       "104          Maize and products  ...   195.0   178.0   191.0    200    200  \n",
       "...                         ...  ...     ...     ...     ...    ...    ...  \n",
       "21572   Milk - Excluding Butter  ...   385.0   418.0   457.0    426    451  \n",
       "21573             Fish, Seafood  ...     5.0    15.0    15.0     15     15  \n",
       "21574             Fish, Seafood  ...    18.0    29.0    40.0     40     40  \n",
       "21575   Aquatic Products, Other  ...     0.0     0.0     0.0      0      0  \n",
       "21576             Miscellaneous  ...     0.0     0.0     0.0      0      0  \n",
       "\n",
       "[21477 rows x 63 columns]"
      ]
     },
     "execution_count": 66,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_rel"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-03-15T06:56:24.142419Z",
     "start_time": "2021-03-15T06:56:24.104520Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Area Abbreviation</th>\n",
       "      <th>Area Code</th>\n",
       "      <th>Area</th>\n",
       "      <th>Item Code</th>\n",
       "      <th>Item</th>\n",
       "      <th>...</th>\n",
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       "      <th>0</th>\n",
       "      <td>AF</td>\n",
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       "      <td>2511</td>\n",
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       "      <td>...</td>\n",
       "      <td>4538.0</td>\n",
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       "    <tr>\n",
       "      <th>1</th>\n",
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       "      <td>...</td>\n",
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       "      <td>425</td>\n",
       "      <td>422</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>AF</td>\n",
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       "      <td>Afghanistan</td>\n",
       "      <td>2513</td>\n",
       "      <td>Barley and products</td>\n",
       "      <td>...</td>\n",
       "      <td>379.0</td>\n",
       "      <td>315.0</td>\n",
       "      <td>203.0</td>\n",
       "      <td>367</td>\n",
       "      <td>360</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>AF</td>\n",
       "      <td>2</td>\n",
       "      <td>Afghanistan</td>\n",
       "      <td>2513</td>\n",
       "      <td>Barley and products</td>\n",
       "      <td>...</td>\n",
       "      <td>55.0</td>\n",
       "      <td>60.0</td>\n",
       "      <td>72.0</td>\n",
       "      <td>78</td>\n",
       "      <td>89</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>AF</td>\n",
       "      <td>2</td>\n",
       "      <td>Afghanistan</td>\n",
       "      <td>2514</td>\n",
       "      <td>Maize and products</td>\n",
       "      <td>...</td>\n",
       "      <td>195.0</td>\n",
       "      <td>178.0</td>\n",
       "      <td>191.0</td>\n",
       "      <td>200</td>\n",
       "      <td>200</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21472</th>\n",
       "      <td>ZW</td>\n",
       "      <td>181</td>\n",
       "      <td>Zimbabwe</td>\n",
       "      <td>2948</td>\n",
       "      <td>Milk - Excluding Butter</td>\n",
       "      <td>...</td>\n",
       "      <td>385.0</td>\n",
       "      <td>418.0</td>\n",
       "      <td>457.0</td>\n",
       "      <td>426</td>\n",
       "      <td>451</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21473</th>\n",
       "      <td>ZW</td>\n",
       "      <td>181</td>\n",
       "      <td>Zimbabwe</td>\n",
       "      <td>2960</td>\n",
       "      <td>Fish, Seafood</td>\n",
       "      <td>...</td>\n",
       "      <td>5.0</td>\n",
       "      <td>15.0</td>\n",
       "      <td>15.0</td>\n",
       "      <td>15</td>\n",
       "      <td>15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21474</th>\n",
       "      <td>ZW</td>\n",
       "      <td>181</td>\n",
       "      <td>Zimbabwe</td>\n",
       "      <td>2960</td>\n",
       "      <td>Fish, Seafood</td>\n",
       "      <td>...</td>\n",
       "      <td>18.0</td>\n",
       "      <td>29.0</td>\n",
       "      <td>40.0</td>\n",
       "      <td>40</td>\n",
       "      <td>40</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21475</th>\n",
       "      <td>ZW</td>\n",
       "      <td>181</td>\n",
       "      <td>Zimbabwe</td>\n",
       "      <td>2961</td>\n",
       "      <td>Aquatic Products, Other</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21476</th>\n",
       "      <td>ZW</td>\n",
       "      <td>181</td>\n",
       "      <td>Zimbabwe</td>\n",
       "      <td>2928</td>\n",
       "      <td>Miscellaneous</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>21477 rows × 63 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      Area Abbreviation  Area Code         Area  Item Code  \\\n",
       "0                    AF          2  Afghanistan       2511   \n",
       "1                    AF          2  Afghanistan       2805   \n",
       "2                    AF          2  Afghanistan       2513   \n",
       "3                    AF          2  Afghanistan       2513   \n",
       "4                    AF          2  Afghanistan       2514   \n",
       "...                 ...        ...          ...        ...   \n",
       "21472                ZW        181     Zimbabwe       2948   \n",
       "21473                ZW        181     Zimbabwe       2960   \n",
       "21474                ZW        181     Zimbabwe       2960   \n",
       "21475                ZW        181     Zimbabwe       2961   \n",
       "21476                ZW        181     Zimbabwe       2928   \n",
       "\n",
       "                           Item  ...   Y2009   Y2010   Y2011  Y2012  Y2013  \n",
       "0            Wheat and products  ...  4538.0  4605.0  4711.0   4810   4895  \n",
       "1      Rice (Milled Equivalent)  ...   415.0   442.0   476.0    425    422  \n",
       "2           Barley and products  ...   379.0   315.0   203.0    367    360  \n",
       "3           Barley and products  ...    55.0    60.0    72.0     78     89  \n",
       "4            Maize and products  ...   195.0   178.0   191.0    200    200  \n",
       "...                         ...  ...     ...     ...     ...    ...    ...  \n",
       "21472   Milk - Excluding Butter  ...   385.0   418.0   457.0    426    451  \n",
       "21473             Fish, Seafood  ...     5.0    15.0    15.0     15     15  \n",
       "21474             Fish, Seafood  ...    18.0    29.0    40.0     40     40  \n",
       "21475   Aquatic Products, Other  ...     0.0     0.0     0.0      0      0  \n",
       "21476             Miscellaneous  ...     0.0     0.0     0.0      0      0  \n",
       "\n",
       "[21477 rows x 63 columns]"
      ]
     },
     "execution_count": 67,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# you can recover the index as origin\n",
    "df_rel.reset_index(drop=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-03-15T06:56:24.202258Z",
     "start_time": "2021-03-15T06:56:24.147409Z"
    }
   },
   "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",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Area Abbreviation</th>\n",
       "      <th>Area Code</th>\n",
       "      <th>Item Code</th>\n",
       "      <th>Item</th>\n",
       "      <th>Element Code</th>\n",
       "      <th>...</th>\n",
       "      <th>Y2009</th>\n",
       "      <th>Y2010</th>\n",
       "      <th>Y2011</th>\n",
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       "  <tbody>\n",
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       "      <th>0</th>\n",
       "      <td>AL</td>\n",
       "      <td>3</td>\n",
       "      <td>2511</td>\n",
       "      <td>Wheat and products</td>\n",
       "      <td>5521</td>\n",
       "      <td>...</td>\n",
       "      <td>30.0</td>\n",
       "      <td>26.0</td>\n",
       "      <td>25.0</td>\n",
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       "      <td>18</td>\n",
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       "      <td>440</td>\n",
       "      <td>440</td>\n",
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       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>AL</td>\n",
       "      <td>3</td>\n",
       "      <td>2805</td>\n",
       "      <td>Rice (Milled Equivalent)</td>\n",
       "      <td>5521</td>\n",
       "      <td>...</td>\n",
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       "      <td>AL</td>\n",
       "      <td>3</td>\n",
       "      <td>2805</td>\n",
       "      <td>Rice (Milled Equivalent)</td>\n",
       "      <td>5142</td>\n",
       "      <td>...</td>\n",
       "      <td>23.0</td>\n",
       "      <td>24.0</td>\n",
       "      <td>21.0</td>\n",
       "      <td>22</td>\n",
       "      <td>25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>AL</td>\n",
       "      <td>3</td>\n",
       "      <td>2513</td>\n",
       "      <td>Barley and products</td>\n",
       "      <td>5521</td>\n",
       "      <td>...</td>\n",
       "      <td>4.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>8.0</td>\n",
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       "      <td>...</td>\n",
       "      <td>...</td>\n",
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       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21389</th>\n",
       "      <td>ZW</td>\n",
       "      <td>181</td>\n",
       "      <td>2948</td>\n",
       "      <td>Milk - Excluding Butter</td>\n",
       "      <td>5142</td>\n",
       "      <td>...</td>\n",
       "      <td>385.0</td>\n",
       "      <td>418.0</td>\n",
       "      <td>457.0</td>\n",
       "      <td>426</td>\n",
       "      <td>451</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21390</th>\n",
       "      <td>ZW</td>\n",
       "      <td>181</td>\n",
       "      <td>2960</td>\n",
       "      <td>Fish, Seafood</td>\n",
       "      <td>5521</td>\n",
       "      <td>...</td>\n",
       "      <td>5.0</td>\n",
       "      <td>15.0</td>\n",
       "      <td>15.0</td>\n",
       "      <td>15</td>\n",
       "      <td>15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21391</th>\n",
       "      <td>ZW</td>\n",
       "      <td>181</td>\n",
       "      <td>2960</td>\n",
       "      <td>Fish, Seafood</td>\n",
       "      <td>5142</td>\n",
       "      <td>...</td>\n",
       "      <td>18.0</td>\n",
       "      <td>29.0</td>\n",
       "      <td>40.0</td>\n",
       "      <td>40</td>\n",
       "      <td>40</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21392</th>\n",
       "      <td>ZW</td>\n",
       "      <td>181</td>\n",
       "      <td>2961</td>\n",
       "      <td>Aquatic Products, Other</td>\n",
       "      <td>5142</td>\n",
       "      <td>...</td>\n",
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       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
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       "      <td>0</td>\n",
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       "    <tr>\n",
       "      <th>21393</th>\n",
       "      <td>ZW</td>\n",
       "      <td>181</td>\n",
       "      <td>2928</td>\n",
       "      <td>Miscellaneous</td>\n",
       "      <td>5142</td>\n",
       "      <td>...</td>\n",
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       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>21394 rows × 62 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      Area Abbreviation  Area Code  Item Code                      Item  \\\n",
       "0                    AL          3       2511        Wheat and products   \n",
       "1                    AL          3       2511        Wheat and products   \n",
       "2                    AL          3       2805  Rice (Milled Equivalent)   \n",
       "3                    AL          3       2805  Rice (Milled Equivalent)   \n",
       "4                    AL          3       2513       Barley and products   \n",
       "...                 ...        ...        ...                       ...   \n",
       "21389                ZW        181       2948   Milk - Excluding Butter   \n",
       "21390                ZW        181       2960             Fish, Seafood   \n",
       "21391                ZW        181       2960             Fish, Seafood   \n",
       "21392                ZW        181       2961   Aquatic Products, Other   \n",
       "21393                ZW        181       2928             Miscellaneous   \n",
       "\n",
       "       Element Code  ...  Y2009  Y2010  Y2011  Y2012  Y2013  \n",
       "0              5521  ...   30.0   26.0   25.0     20     18  \n",
       "1              5142  ...  415.0  432.0  439.0    440    440  \n",
       "2              5521  ...    0.0    0.0    0.0      0      0  \n",
       "3              5142  ...   23.0   24.0   21.0     22     25  \n",
       "4              5521  ...    4.0    7.0    8.0      7      7  \n",
       "...             ...  ...    ...    ...    ...    ...    ...  \n",
       "21389          5142  ...  385.0  418.0  457.0    426    451  \n",
       "21390          5521  ...    5.0   15.0   15.0     15     15  \n",
       "21391          5142  ...   18.0   29.0   40.0     40     40  \n",
       "21392          5142  ...    0.0    0.0    0.0      0      0  \n",
       "21393          5142  ...    0.0    0.0    0.0      0      0  \n",
       "\n",
       "[21394 rows x 62 columns]"
      ]
     },
     "execution_count": 68,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_rel.set_index(\"Area\").drop(\"Afghanistan\", axis=0).reset_index(drop=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-03-15T06:56:24.232179Z",
     "start_time": "2021-03-15T06:56:24.203256Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Test0</th>\n",
       "      <th>Test1</th>\n",
       "      <th>Test2</th>\n",
       "      <th>Test3</th>\n",
       "      <th>Test4</th>\n",
       "      <th>...</th>\n",
       "      <th>Test58</th>\n",
       "      <th>Test59</th>\n",
       "      <th>Test60</th>\n",
       "      <th>Test61</th>\n",
       "      <th>Test62</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>100</th>\n",
       "      <td>AF</td>\n",
       "      <td>2</td>\n",
       "      <td>Afghanistan</td>\n",
       "      <td>2511</td>\n",
       "      <td>Wheat and products</td>\n",
       "      <td>...</td>\n",
       "      <td>4538.0</td>\n",
       "      <td>4605.0</td>\n",
       "      <td>4711.0</td>\n",
       "      <td>4810</td>\n",
       "      <td>4895</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>101</th>\n",
       "      <td>AF</td>\n",
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       "      <td>Rice (Milled Equivalent)</td>\n",
       "      <td>...</td>\n",
       "      <td>415.0</td>\n",
       "      <td>442.0</td>\n",
       "      <td>476.0</td>\n",
       "      <td>425</td>\n",
       "      <td>422</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>102</th>\n",
       "      <td>AF</td>\n",
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       "      <td>...</td>\n",
       "      <td>379.0</td>\n",
       "      <td>315.0</td>\n",
       "      <td>203.0</td>\n",
       "      <td>367</td>\n",
       "      <td>360</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>103</th>\n",
       "      <td>AF</td>\n",
       "      <td>2</td>\n",
       "      <td>Afghanistan</td>\n",
       "      <td>2513</td>\n",
       "      <td>Barley and products</td>\n",
       "      <td>...</td>\n",
       "      <td>55.0</td>\n",
       "      <td>60.0</td>\n",
       "      <td>72.0</td>\n",
       "      <td>78</td>\n",
       "      <td>89</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>104</th>\n",
       "      <td>AF</td>\n",
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       "      <td>Afghanistan</td>\n",
       "      <td>2514</td>\n",
       "      <td>Maize and products</td>\n",
       "      <td>...</td>\n",
       "      <td>195.0</td>\n",
       "      <td>178.0</td>\n",
       "      <td>191.0</td>\n",
       "      <td>200</td>\n",
       "      <td>200</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21572</th>\n",
       "      <td>ZW</td>\n",
       "      <td>181</td>\n",
       "      <td>Zimbabwe</td>\n",
       "      <td>2948</td>\n",
       "      <td>Milk - Excluding Butter</td>\n",
       "      <td>...</td>\n",
       "      <td>385.0</td>\n",
       "      <td>418.0</td>\n",
       "      <td>457.0</td>\n",
       "      <td>426</td>\n",
       "      <td>451</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21573</th>\n",
       "      <td>ZW</td>\n",
       "      <td>181</td>\n",
       "      <td>Zimbabwe</td>\n",
       "      <td>2960</td>\n",
       "      <td>Fish, Seafood</td>\n",
       "      <td>...</td>\n",
       "      <td>5.0</td>\n",
       "      <td>15.0</td>\n",
       "      <td>15.0</td>\n",
       "      <td>15</td>\n",
       "      <td>15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21574</th>\n",
       "      <td>ZW</td>\n",
       "      <td>181</td>\n",
       "      <td>Zimbabwe</td>\n",
       "      <td>2960</td>\n",
       "      <td>Fish, Seafood</td>\n",
       "      <td>...</td>\n",
       "      <td>18.0</td>\n",
       "      <td>29.0</td>\n",
       "      <td>40.0</td>\n",
       "      <td>40</td>\n",
       "      <td>40</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21575</th>\n",
       "      <td>ZW</td>\n",
       "      <td>181</td>\n",
       "      <td>Zimbabwe</td>\n",
       "      <td>2961</td>\n",
       "      <td>Aquatic Products, Other</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21576</th>\n",
       "      <td>ZW</td>\n",
       "      <td>181</td>\n",
       "      <td>Zimbabwe</td>\n",
       "      <td>2928</td>\n",
       "      <td>Miscellaneous</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>21477 rows × 63 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      Test0  Test1        Test2  Test3                     Test4  ...  Test58  \\\n",
       "100      AF      2  Afghanistan   2511        Wheat and products  ...  4538.0   \n",
       "101      AF      2  Afghanistan   2805  Rice (Milled Equivalent)  ...   415.0   \n",
       "102      AF      2  Afghanistan   2513       Barley and products  ...   379.0   \n",
       "103      AF      2  Afghanistan   2513       Barley and products  ...    55.0   \n",
       "104      AF      2  Afghanistan   2514        Maize and products  ...   195.0   \n",
       "...     ...    ...          ...    ...                       ...  ...     ...   \n",
       "21572    ZW    181     Zimbabwe   2948   Milk - Excluding Butter  ...   385.0   \n",
       "21573    ZW    181     Zimbabwe   2960             Fish, Seafood  ...     5.0   \n",
       "21574    ZW    181     Zimbabwe   2960             Fish, Seafood  ...    18.0   \n",
       "21575    ZW    181     Zimbabwe   2961   Aquatic Products, Other  ...     0.0   \n",
       "21576    ZW    181     Zimbabwe   2928             Miscellaneous  ...     0.0   \n",
       "\n",
       "       Test59  Test60  Test61  Test62  \n",
       "100    4605.0  4711.0    4810    4895  \n",
       "101     442.0   476.0     425     422  \n",
       "102     315.0   203.0     367     360  \n",
       "103      60.0    72.0      78      89  \n",
       "104     178.0   191.0     200     200  \n",
       "...       ...     ...     ...     ...  \n",
       "21572   418.0   457.0     426     451  \n",
       "21573    15.0    15.0      15      15  \n",
       "21574    29.0    40.0      40      40  \n",
       "21575     0.0     0.0       0       0  \n",
       "21576     0.0     0.0       0       0  \n",
       "\n",
       "[21477 rows x 63 columns]"
      ]
     },
     "execution_count": 69,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Renaming of columns\n",
    "df_test = df_rel.copy()\n",
    "df_test.columns = ['Test'+str(i) for i in range(len(df_rel.columns))]\n",
    "df_test"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-03-15T06:56:24.277059Z",
     "start_time": "2021-03-15T06:56:24.233177Z"
    }
   },
   "outputs": [
    {
     "data": {
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       "      <th></th>\n",
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       "      <th>102</th>\n",
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       "      <th>103</th>\n",
       "      <td>AF</td>\n",
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       "      <td>ZW</td>\n",
       "      <td>181</td>\n",
       "      <td>Zimbabwe</td>\n",
       "      <td>2948</td>\n",
       "      <td>Milk - Excluding Butter</td>\n",
       "      <td>...</td>\n",
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       "      <td>426</td>\n",
       "      <td>451</td>\n",
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       "      <td>ZW</td>\n",
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       "      <td>2960</td>\n",
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      ],
      "text/plain": [
       "      Area Abbreviation  Area Code     New_Area  Item Code  \\\n",
       "100                  AF          2  Afghanistan       2511   \n",
       "101                  AF          2  Afghanistan       2805   \n",
       "102                  AF          2  Afghanistan       2513   \n",
       "103                  AF          2  Afghanistan       2513   \n",
       "104                  AF          2  Afghanistan       2514   \n",
       "...                 ...        ...          ...        ...   \n",
       "21572                ZW        181     Zimbabwe       2948   \n",
       "21573                ZW        181     Zimbabwe       2960   \n",
       "21574                ZW        181     Zimbabwe       2960   \n",
       "21575                ZW        181     Zimbabwe       2961   \n",
       "21576                ZW        181     Zimbabwe       2928   \n",
       "\n",
       "                           Item  ...   Y2009   Y2010   Y2011  Y2012  Y2013  \n",
       "100          Wheat and products  ...  4538.0  4605.0  4711.0   4810   4895  \n",
       "101    Rice (Milled Equivalent)  ...   415.0   442.0   476.0    425    422  \n",
       "102         Barley and products  ...   379.0   315.0   203.0    367    360  \n",
       "103         Barley and products  ...    55.0    60.0    72.0     78     89  \n",
       "104          Maize and products  ...   195.0   178.0   191.0    200    200  \n",
       "...                         ...  ...     ...     ...     ...    ...    ...  \n",
       "21572   Milk - Excluding Butter  ...   385.0   418.0   457.0    426    451  \n",
       "21573             Fish, Seafood  ...     5.0    15.0    15.0     15     15  \n",
       "21574             Fish, Seafood  ...    18.0    29.0    40.0     40     40  \n",
       "21575   Aquatic Products, Other  ...     0.0     0.0     0.0      0      0  \n",
       "21576             Miscellaneous  ...     0.0     0.0     0.0      0      0  \n",
       "\n",
       "[21477 rows x 63 columns]"
      ]
     },
     "execution_count": 70,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_rel.rename(columns={'Area':'New_Area'})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-03-15T06:56:24.336899Z",
     "start_time": "2021-03-15T06:56:24.279054Z"
    }
   },
   "outputs": [
    {
     "data": {
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       "      <td>Maize and products</td>\n",
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       "      <td>Milk - Excluding Butter</td>\n",
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       "      <td>451</td>\n",
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       "      <th>21573</th>\n",
       "      <td>ZW</td>\n",
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       "      <td>ZW</td>\n",
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       "      <td>Aquatic Products, Other</td>\n",
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      ],
      "text/plain": [
       "      Area Abbreviation  Area Code         Area  Item Code  \\\n",
       "100                  AF          2  Afghanistan       2511   \n",
       "101                  AF          2  Afghanistan       2805   \n",
       "102                  AF          2  Afghanistan       2513   \n",
       "103                  AF          2  Afghanistan       2513   \n",
       "104                  AF          2  Afghanistan       2514   \n",
       "...                 ...        ...          ...        ...   \n",
       "21572                ZW        181     Zimbabwe       2948   \n",
       "21573                ZW        181     Zimbabwe       2960   \n",
       "21574                ZW        181     Zimbabwe       2960   \n",
       "21575                ZW        181     Zimbabwe       2961   \n",
       "21576                ZW        181     Zimbabwe       2928   \n",
       "\n",
       "                           Item  ...   Y2009   Y2010   Y2011  Y2012  Y2013  \n",
       "100          Wheat and products  ...  4538.0  4605.0  4711.0   4810   4895  \n",
       "101    Rice (Milled Equivalent)  ...   415.0   442.0   476.0    425    422  \n",
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       "104          Maize and products  ...   195.0   178.0   191.0    200    200  \n",
       "...                         ...  ...     ...     ...     ...    ...    ...  \n",
       "21572   Milk - Excluding Butter  ...   385.0   418.0   457.0    426    451  \n",
       "21573             Fish, Seafood  ...     5.0    15.0    15.0     15     15  \n",
       "21574             Fish, Seafood  ...    18.0    29.0    40.0     40     40  \n",
       "21575   Aquatic Products, Other  ...     0.0     0.0     0.0      0      0  \n",
       "21576             Miscellaneous  ...     0.0     0.0     0.0      0      0  \n",
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       "      Area Abbreviation  Area Code     New_Area  Item Code  \\\n",
       "100                  AF          2  Afghanistan       2511   \n",
       "101                  AF          2  Afghanistan       2805   \n",
       "102                  AF          2  Afghanistan       2513   \n",
       "103                  AF          2  Afghanistan       2513   \n",
       "104                  AF          2  Afghanistan       2514   \n",
       "...                 ...        ...          ...        ...   \n",
       "21572                ZW        181     Zimbabwe       2948   \n",
       "21573                ZW        181     Zimbabwe       2960   \n",
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       "\n",
       "                           Item  ...   Y2009   Y2010   Y2011  Y2012  Y2013  \n",
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       "...                         ...  ...     ...     ...     ...    ...    ...  \n",
       "21572   Milk - Excluding Butter  ...   385.0   418.0   457.0    426    451  \n",
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       "\n",
       "[21477 rows x 63 columns]"
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     },
     "execution_count": 71,
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   ],
   "source": [
    "display(df_rel)\n",
    "df_rel.rename(columns={'Area':'New_Area'}, inplace=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 72,
   "metadata": {
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     "start_time": "2021-03-15T06:56:24.338897Z"
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   "outputs": [
    {
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       "      Area Abbreviation  Area Code     New_Area  Item Code  \\\n",
       "100                  AF          2  Afghanistan       2511   \n",
       "101                  AF          2  Afghanistan       2805   \n",
       "102                  AF          2  Afghanistan       2513   \n",
       "103                  AF          2  Afghanistan       2513   \n",
       "104                  AF          2  Afghanistan       2514   \n",
       "...                 ...        ...          ...        ...   \n",
       "21572                ZW        181     Zimbabwe       2948   \n",
       "21573                ZW        181     Zimbabwe       2960   \n",
       "21574                ZW        181     Zimbabwe       2960   \n",
       "21575                ZW        181     Zimbabwe       2961   \n",
       "21576                ZW        181     Zimbabwe       2928   \n",
       "\n",
       "                           Item  ...   Y2009   Y2010   Y2011  Y2012  Year_2013  \n",
       "100          Wheat and products  ...  4538.0  4605.0  4711.0   4810       4895  \n",
       "101    Rice (Milled Equivalent)  ...   415.0   442.0   476.0    425        422  \n",
       "102         Barley and products  ...   379.0   315.0   203.0    367        360  \n",
       "103         Barley and products  ...    55.0    60.0    72.0     78         89  \n",
       "104          Maize and products  ...   195.0   178.0   191.0    200        200  \n",
       "...                         ...  ...     ...     ...     ...    ...        ...  \n",
       "21572   Milk - Excluding Butter  ...   385.0   418.0   457.0    426        451  \n",
       "21573             Fish, Seafood  ...     5.0    15.0    15.0     15         15  \n",
       "21574             Fish, Seafood  ...    18.0    29.0    40.0     40         40  \n",
       "21575   Aquatic Products, Other  ...     0.0     0.0     0.0      0          0  \n",
       "21576             Miscellaneous  ...     0.0     0.0     0.0      0          0  \n",
       "\n",
       "[21477 rows x 63 columns]"
      ]
     },
     "execution_count": 72,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_rel.rename(columns={'Area':'New_Area',\n",
    "                       'Y2013':'Year_2013'}, inplace=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 73,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-03-15T06:56:24.411699Z",
     "start_time": "2021-03-15T06:56:24.382776Z"
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   },
   "outputs": [
    {
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       "      <th>101</th>\n",
       "      <td>AF</td>\n",
       "      <td>2</td>\n",
       "      <td>Afghanistan</td>\n",
       "      <td>2805</td>\n",
       "      <td>Rice (Milled Equivalent)</td>\n",
       "      <td>...</td>\n",
       "      <td>415.0</td>\n",
       "      <td>442.0</td>\n",
       "      <td>476.0</td>\n",
       "      <td>425</td>\n",
       "      <td>422</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>102</th>\n",
       "      <td>AF</td>\n",
       "      <td>2</td>\n",
       "      <td>Afghanistan</td>\n",
       "      <td>2513</td>\n",
       "      <td>Barley and products</td>\n",
       "      <td>...</td>\n",
       "      <td>379.0</td>\n",
       "      <td>315.0</td>\n",
       "      <td>203.0</td>\n",
       "      <td>367</td>\n",
       "      <td>360</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>103</th>\n",
       "      <td>AF</td>\n",
       "      <td>2</td>\n",
       "      <td>Afghanistan</td>\n",
       "      <td>2513</td>\n",
       "      <td>Barley and products</td>\n",
       "      <td>...</td>\n",
       "      <td>55.0</td>\n",
       "      <td>60.0</td>\n",
       "      <td>72.0</td>\n",
       "      <td>78</td>\n",
       "      <td>89</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>104</th>\n",
       "      <td>AF</td>\n",
       "      <td>2</td>\n",
       "      <td>Afghanistan</td>\n",
       "      <td>2514</td>\n",
       "      <td>Maize and products</td>\n",
       "      <td>...</td>\n",
       "      <td>195.0</td>\n",
       "      <td>178.0</td>\n",
       "      <td>191.0</td>\n",
       "      <td>200</td>\n",
       "      <td>200</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21572</th>\n",
       "      <td>ZW</td>\n",
       "      <td>181</td>\n",
       "      <td>Zimbabwe</td>\n",
       "      <td>2948</td>\n",
       "      <td>Milk - Excluding Butter</td>\n",
       "      <td>...</td>\n",
       "      <td>385.0</td>\n",
       "      <td>418.0</td>\n",
       "      <td>457.0</td>\n",
       "      <td>426</td>\n",
       "      <td>451</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21573</th>\n",
       "      <td>ZW</td>\n",
       "      <td>181</td>\n",
       "      <td>Zimbabwe</td>\n",
       "      <td>2960</td>\n",
       "      <td>Fish, Seafood</td>\n",
       "      <td>...</td>\n",
       "      <td>5.0</td>\n",
       "      <td>15.0</td>\n",
       "      <td>15.0</td>\n",
       "      <td>15</td>\n",
       "      <td>15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21574</th>\n",
       "      <td>ZW</td>\n",
       "      <td>181</td>\n",
       "      <td>Zimbabwe</td>\n",
       "      <td>2960</td>\n",
       "      <td>Fish, Seafood</td>\n",
       "      <td>...</td>\n",
       "      <td>18.0</td>\n",
       "      <td>29.0</td>\n",
       "      <td>40.0</td>\n",
       "      <td>40</td>\n",
       "      <td>40</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21575</th>\n",
       "      <td>ZW</td>\n",
       "      <td>181</td>\n",
       "      <td>Zimbabwe</td>\n",
       "      <td>2961</td>\n",
       "      <td>Aquatic Products, Other</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21576</th>\n",
       "      <td>ZW</td>\n",
       "      <td>181</td>\n",
       "      <td>Zimbabwe</td>\n",
       "      <td>2928</td>\n",
       "      <td>Miscellaneous</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>21477 rows × 63 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      AREA_ABBREVIATION  AREA_CODE         AREA  ITEM_CODE  \\\n",
       "100                  AF          2  Afghanistan       2511   \n",
       "101                  AF          2  Afghanistan       2805   \n",
       "102                  AF          2  Afghanistan       2513   \n",
       "103                  AF          2  Afghanistan       2513   \n",
       "104                  AF          2  Afghanistan       2514   \n",
       "...                 ...        ...          ...        ...   \n",
       "21572                ZW        181     Zimbabwe       2948   \n",
       "21573                ZW        181     Zimbabwe       2960   \n",
       "21574                ZW        181     Zimbabwe       2960   \n",
       "21575                ZW        181     Zimbabwe       2961   \n",
       "21576                ZW        181     Zimbabwe       2928   \n",
       "\n",
       "                           ITEM  ...   Y2009   Y2010   Y2011  Y2012  Y2013  \n",
       "100          Wheat and products  ...  4538.0  4605.0  4711.0   4810   4895  \n",
       "101    Rice (Milled Equivalent)  ...   415.0   442.0   476.0    425    422  \n",
       "102         Barley and products  ...   379.0   315.0   203.0    367    360  \n",
       "103         Barley and products  ...    55.0    60.0    72.0     78     89  \n",
       "104          Maize and products  ...   195.0   178.0   191.0    200    200  \n",
       "...                         ...  ...     ...     ...     ...    ...    ...  \n",
       "21572   Milk - Excluding Butter  ...   385.0   418.0   457.0    426    451  \n",
       "21573             Fish, Seafood  ...     5.0    15.0    15.0     15     15  \n",
       "21574             Fish, Seafood  ...    18.0    29.0    40.0     40     40  \n",
       "21575   Aquatic Products, Other  ...     0.0     0.0     0.0      0      0  \n",
       "21576             Miscellaneous  ...     0.0     0.0     0.0      0      0  \n",
       "\n",
       "[21477 rows x 63 columns]"
      ]
     },
     "execution_count": 73,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_rel.rename(columns=lambda x: x.upper().replace(' ', '_'), inplace=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 데이터의 특성확인(Descriptive Statistics)\n",
    "\n",
    "> **DataFrame.describe() 함수는 적용되는 모든 변수 또는 그룹의 통계를 빠르게 표시하는 유용한 요약 도구**\n",
    "\n",
    "| Function | Description                         |\n",
    "|----------|-------------------------------------|\n",
    "| count    | Number of non-null observations     |\n",
    "| sum      | Sum of values                       |\n",
    "| mean     | Mean of values                      |\n",
    "| mad      | Mean absolute deviation             |\n",
    "| median   | Arithmetic median of values         |\n",
    "| min      | Minimum                             |\n",
    "| max      | Maximum                             |\n",
    "| mode     | Mode                                |\n",
    "| abs      | Absolute Value                      |\n",
    "| prod     | Product of values                   |\n",
    "| std      | Unbiased standard deviation         |\n",
    "| var      | Unbiased variance                   |\n",
    "| sem      | Unbiased standard error of the mean |\n",
    "| skew     | Unbiased skewness (3rd moment)      |\n",
    "| kurt     | Unbiased kurtosis (4th moment)      |\n",
    "| quantile | Sample quantile (value at %)        |\n",
    "| cumsum   | Cumulative sum                      |\n",
    "| cumprod  | Cumulative product                  |\n",
    "| cummax   | Cumulative maximum                  |\n",
    "| cummin   | Cumulative minimum                  |"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 74,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-03-15T06:56:24.426658Z",
     "start_time": "2021-03-15T06:56:24.414695Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(21477, 63)"
      ]
     },
     "execution_count": 74,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Examine data in a Pandas DataFrame\n",
    "df_rel.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 75,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-03-15T06:56:24.441618Z",
     "start_time": "2021-03-15T06:56:24.428655Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2"
      ]
     },
     "execution_count": 75,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_rel.ndim"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 76,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-03-15T06:56:24.471541Z",
     "start_time": "2021-03-15T06:56:24.443615Z"
    }
   },
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Area Abbreviation</th>\n",
       "      <th>Area Code</th>\n",
       "      <th>Area</th>\n",
       "      <th>Item Code</th>\n",
       "      <th>Item</th>\n",
       "      <th>...</th>\n",
       "      <th>Y2009</th>\n",
       "      <th>Y2010</th>\n",
       "      <th>Y2011</th>\n",
       "      <th>Y2012</th>\n",
       "      <th>Y2013</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>100</th>\n",
       "      <td>AF</td>\n",
       "      <td>2</td>\n",
       "      <td>Afghanistan</td>\n",
       "      <td>2511</td>\n",
       "      <td>Wheat and products</td>\n",
       "      <td>...</td>\n",
       "      <td>4538.0</td>\n",
       "      <td>4605.0</td>\n",
       "      <td>4711.0</td>\n",
       "      <td>4810</td>\n",
       "      <td>4895</td>\n",
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       "    <tr>\n",
       "      <th>101</th>\n",
       "      <td>AF</td>\n",
       "      <td>2</td>\n",
       "      <td>Afghanistan</td>\n",
       "      <td>2805</td>\n",
       "      <td>Rice (Milled Equivalent)</td>\n",
       "      <td>...</td>\n",
       "      <td>415.0</td>\n",
       "      <td>442.0</td>\n",
       "      <td>476.0</td>\n",
       "      <td>425</td>\n",
       "      <td>422</td>\n",
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       "    <tr>\n",
       "      <th>102</th>\n",
       "      <td>AF</td>\n",
       "      <td>2</td>\n",
       "      <td>Afghanistan</td>\n",
       "      <td>2513</td>\n",
       "      <td>Barley and products</td>\n",
       "      <td>...</td>\n",
       "      <td>379.0</td>\n",
       "      <td>315.0</td>\n",
       "      <td>203.0</td>\n",
       "      <td>367</td>\n",
       "      <td>360</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>103</th>\n",
       "      <td>AF</td>\n",
       "      <td>2</td>\n",
       "      <td>Afghanistan</td>\n",
       "      <td>2513</td>\n",
       "      <td>Barley and products</td>\n",
       "      <td>...</td>\n",
       "      <td>55.0</td>\n",
       "      <td>60.0</td>\n",
       "      <td>72.0</td>\n",
       "      <td>78</td>\n",
       "      <td>89</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>104</th>\n",
       "      <td>AF</td>\n",
       "      <td>2</td>\n",
       "      <td>Afghanistan</td>\n",
       "      <td>2514</td>\n",
       "      <td>Maize and products</td>\n",
       "      <td>...</td>\n",
       "      <td>195.0</td>\n",
       "      <td>178.0</td>\n",
       "      <td>191.0</td>\n",
       "      <td>200</td>\n",
       "      <td>200</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 63 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "    Area Abbreviation  Area Code         Area  Item Code  \\\n",
       "100                AF          2  Afghanistan       2511   \n",
       "101                AF          2  Afghanistan       2805   \n",
       "102                AF          2  Afghanistan       2513   \n",
       "103                AF          2  Afghanistan       2513   \n",
       "104                AF          2  Afghanistan       2514   \n",
       "\n",
       "                         Item  ...   Y2009   Y2010   Y2011  Y2012  Y2013  \n",
       "100        Wheat and products  ...  4538.0  4605.0  4711.0   4810   4895  \n",
       "101  Rice (Milled Equivalent)  ...   415.0   442.0   476.0    425    422  \n",
       "102       Barley and products  ...   379.0   315.0   203.0    367    360  \n",
       "103       Barley and products  ...    55.0    60.0    72.0     78     89  \n",
       "104        Maize and products  ...   195.0   178.0   191.0    200    200  \n",
       "\n",
       "[5 rows x 63 columns]"
      ]
     },
     "execution_count": 76,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_rel.head(5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 77,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-03-15T06:56:24.502455Z",
     "start_time": "2021-03-15T06:56:24.474532Z"
    }
   },
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Area Abbreviation</th>\n",
       "      <th>Area Code</th>\n",
       "      <th>Area</th>\n",
       "      <th>Item Code</th>\n",
       "      <th>Item</th>\n",
       "      <th>...</th>\n",
       "      <th>Y2009</th>\n",
       "      <th>Y2010</th>\n",
       "      <th>Y2011</th>\n",
       "      <th>Y2012</th>\n",
       "      <th>Y2013</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>21572</th>\n",
       "      <td>ZW</td>\n",
       "      <td>181</td>\n",
       "      <td>Zimbabwe</td>\n",
       "      <td>2948</td>\n",
       "      <td>Milk - Excluding Butter</td>\n",
       "      <td>...</td>\n",
       "      <td>385.0</td>\n",
       "      <td>418.0</td>\n",
       "      <td>457.0</td>\n",
       "      <td>426</td>\n",
       "      <td>451</td>\n",
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       "    <tr>\n",
       "      <th>21573</th>\n",
       "      <td>ZW</td>\n",
       "      <td>181</td>\n",
       "      <td>Zimbabwe</td>\n",
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       "      <td>Fish, Seafood</td>\n",
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       "      <td>5.0</td>\n",
       "      <td>15.0</td>\n",
       "      <td>15.0</td>\n",
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       "      <td>15</td>\n",
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       "    <tr>\n",
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       "      <td>18.0</td>\n",
       "      <td>29.0</td>\n",
       "      <td>40.0</td>\n",
       "      <td>40</td>\n",
       "      <td>40</td>\n",
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       "    <tr>\n",
       "      <th>21575</th>\n",
       "      <td>ZW</td>\n",
       "      <td>181</td>\n",
       "      <td>Zimbabwe</td>\n",
       "      <td>2961</td>\n",
       "      <td>Aquatic Products, Other</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
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       "      <td>0</td>\n",
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       "    <tr>\n",
       "      <th>21576</th>\n",
       "      <td>ZW</td>\n",
       "      <td>181</td>\n",
       "      <td>Zimbabwe</td>\n",
       "      <td>2928</td>\n",
       "      <td>Miscellaneous</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
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       "</table>\n",
       "<p>5 rows × 63 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      Area Abbreviation  Area Code      Area  Item Code  \\\n",
       "21572                ZW        181  Zimbabwe       2948   \n",
       "21573                ZW        181  Zimbabwe       2960   \n",
       "21574                ZW        181  Zimbabwe       2960   \n",
       "21575                ZW        181  Zimbabwe       2961   \n",
       "21576                ZW        181  Zimbabwe       2928   \n",
       "\n",
       "                          Item  ...  Y2009  Y2010  Y2011  Y2012  Y2013  \n",
       "21572  Milk - Excluding Butter  ...  385.0  418.0  457.0    426    451  \n",
       "21573            Fish, Seafood  ...    5.0   15.0   15.0     15     15  \n",
       "21574            Fish, Seafood  ...   18.0   29.0   40.0     40     40  \n",
       "21575  Aquatic Products, Other  ...    0.0    0.0    0.0      0      0  \n",
       "21576            Miscellaneous  ...    0.0    0.0    0.0      0      0  \n",
       "\n",
       "[5 rows x 63 columns]"
      ]
     },
     "execution_count": 77,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_rel.tail(5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 78,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-03-15T06:56:24.517418Z",
     "start_time": "2021-03-15T06:56:24.505451Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Area Abbreviation     object\n",
       "Area Code              int64\n",
       "Area                  object\n",
       "Item Code              int64\n",
       "Item                  object\n",
       "                      ...   \n",
       "Y2009                float64\n",
       "Y2010                float64\n",
       "Y2011                float64\n",
       "Y2012                  int64\n",
       "Y2013                  int64\n",
       "Length: 63, dtype: object"
      ]
     },
     "execution_count": 78,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_rel.dtypes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 79,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-03-15T06:56:24.547335Z",
     "start_time": "2021-03-15T06:56:24.520408Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Area Abbreviation     object\n",
       "Area Code              int64\n",
       "Area                  object\n",
       "Item Code             object\n",
       "Item                  object\n",
       "                      ...   \n",
       "Y2009                float64\n",
       "Y2010                float64\n",
       "Y2011                float64\n",
       "Y2012                  int64\n",
       "Y2013                  int64\n",
       "Length: 63, dtype: object"
      ]
     },
     "execution_count": 79,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_rel['Item Code'] = df_rel['Item Code'].astype(str)\n",
    "df_rel.dtypes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 80,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-03-15T06:56:24.711904Z",
     "start_time": "2021-03-15T06:56:24.549330Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "100      138171.65\n",
       "101       20527.65\n",
       "102       10814.65\n",
       "103       13774.65\n",
       "104       15075.65\n",
       "           ...    \n",
       "21572     23570.13\n",
       "21573      6319.13\n",
       "21574      6330.13\n",
       "21575      5333.13\n",
       "21576      5333.13\n",
       "Length: 21477, dtype: float64"
      ]
     },
     "execution_count": 80,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_rel.sum(axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 81,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-03-15T06:56:25.132847Z",
     "start_time": "2021-03-15T06:56:24.713900Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Area Code                                                 2694277\n",
       "Area            AfghanistanAfghanistanAfghanistanAfghanistanAf...\n",
       "Item Code       2511280525132513251425142517252025312536253725...\n",
       "Item            Wheat and productsRice (Milled Equivalent)Barl...\n",
       "Element Code                                            111931405\n",
       "                                      ...                        \n",
       "Y2009                                                 1.12119e+07\n",
       "Y2010                                                 1.14451e+07\n",
       "Y2011                                                 1.18278e+07\n",
       "Y2012                                                    12039345\n",
       "Y2013                                                    12361248\n",
       "Length: 62, dtype: object"
      ]
     },
     "execution_count": 81,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_rel.sum(axis=0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 82,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-03-15T06:56:25.162796Z",
     "start_time": "2021-03-15T06:56:25.133845Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Area Code       2.694277e+06\n",
       "Element Code    1.119314e+08\n",
       "latitude        4.392178e+05\n",
       "longitude       3.392173e+05\n",
       "Y1961           3.502611e+06\n",
       "                    ...     \n",
       "Y2009           1.121189e+07\n",
       "Y2010           1.144507e+07\n",
       "Y2011           1.182780e+07\n",
       "Y2012           1.203934e+07\n",
       "Y2013           1.236125e+07\n",
       "Length: 57, dtype: float64"
      ]
     },
     "execution_count": 82,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_rel[df_rel.columns[df_rel.dtypes != 'object']].sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 83,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-03-15T06:56:25.222637Z",
     "start_time": "2021-03-15T06:56:25.163776Z"
    }
   },
   "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>Area Code</th>\n",
       "      <th>Element Code</th>\n",
       "      <th>latitude</th>\n",
       "      <th>longitude</th>\n",
       "      <th>Y1961</th>\n",
       "      <th>...</th>\n",
       "      <th>Y2009</th>\n",
       "      <th>Y2010</th>\n",
       "      <th>Y2011</th>\n",
       "      <th>Y2012</th>\n",
       "      <th>Y2013</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>100</th>\n",
       "      <td>2</td>\n",
       "      <td>5142</td>\n",
       "      <td>33.94</td>\n",
       "      <td>67.71</td>\n",
       "      <td>1928.0</td>\n",
       "      <td>...</td>\n",
       "      <td>4538.0</td>\n",
       "      <td>4605.0</td>\n",
       "      <td>4711.0</td>\n",
       "      <td>4810</td>\n",
       "      <td>4895</td>\n",
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       "    <tr>\n",
       "      <th>101</th>\n",
       "      <td>4</td>\n",
       "      <td>10284</td>\n",
       "      <td>67.88</td>\n",
       "      <td>135.42</td>\n",
       "      <td>2111.0</td>\n",
       "      <td>...</td>\n",
       "      <td>4953.0</td>\n",
       "      <td>5047.0</td>\n",
       "      <td>5187.0</td>\n",
       "      <td>5235</td>\n",
       "      <td>5317</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>102</th>\n",
       "      <td>6</td>\n",
       "      <td>15805</td>\n",
       "      <td>101.82</td>\n",
       "      <td>203.13</td>\n",
       "      <td>2187.0</td>\n",
       "      <td>...</td>\n",
       "      <td>5332.0</td>\n",
       "      <td>5362.0</td>\n",
       "      <td>5390.0</td>\n",
       "      <td>5602</td>\n",
       "      <td>5677</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>103</th>\n",
       "      <td>8</td>\n",
       "      <td>20947</td>\n",
       "      <td>135.76</td>\n",
       "      <td>270.84</td>\n",
       "      <td>2424.0</td>\n",
       "      <td>...</td>\n",
       "      <td>5387.0</td>\n",
       "      <td>5422.0</td>\n",
       "      <td>5462.0</td>\n",
       "      <td>5680</td>\n",
       "      <td>5766</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>104</th>\n",
       "      <td>10</td>\n",
       "      <td>26468</td>\n",
       "      <td>169.70</td>\n",
       "      <td>338.55</td>\n",
       "      <td>2634.0</td>\n",
       "      <td>...</td>\n",
       "      <td>5582.0</td>\n",
       "      <td>5600.0</td>\n",
       "      <td>5653.0</td>\n",
       "      <td>5880</td>\n",
       "      <td>5966</td>\n",
       "    </tr>\n",
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       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
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       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21572</th>\n",
       "      <td>2693553</td>\n",
       "      <td>111910458</td>\n",
       "      <td>439293.89</td>\n",
       "      <td>339100.70</td>\n",
       "      <td>3502578.0</td>\n",
       "      <td>...</td>\n",
       "      <td>11211868.0</td>\n",
       "      <td>11445028.0</td>\n",
       "      <td>11827747.0</td>\n",
       "      <td>12039290</td>\n",
       "      <td>12361193</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21573</th>\n",
       "      <td>2693734</td>\n",
       "      <td>111915979</td>\n",
       "      <td>439274.87</td>\n",
       "      <td>339129.85</td>\n",
       "      <td>3502605.0</td>\n",
       "      <td>...</td>\n",
       "      <td>11211873.0</td>\n",
       "      <td>11445043.0</td>\n",
       "      <td>11827762.0</td>\n",
       "      <td>12039305</td>\n",
       "      <td>12361208</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21574</th>\n",
       "      <td>2693915</td>\n",
       "      <td>111921121</td>\n",
       "      <td>439255.85</td>\n",
       "      <td>339159.00</td>\n",
       "      <td>3502611.0</td>\n",
       "      <td>...</td>\n",
       "      <td>11211891.0</td>\n",
       "      <td>11445072.0</td>\n",
       "      <td>11827802.0</td>\n",
       "      <td>12039345</td>\n",
       "      <td>12361248</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21575</th>\n",
       "      <td>2694096</td>\n",
       "      <td>111926263</td>\n",
       "      <td>439236.83</td>\n",
       "      <td>339188.15</td>\n",
       "      <td>3502611.0</td>\n",
       "      <td>...</td>\n",
       "      <td>11211891.0</td>\n",
       "      <td>11445072.0</td>\n",
       "      <td>11827802.0</td>\n",
       "      <td>12039345</td>\n",
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       "      <th>21576</th>\n",
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       "      <td>111931405</td>\n",
       "      <td>439217.81</td>\n",
       "      <td>339217.30</td>\n",
       "      <td>3502611.0</td>\n",
       "      <td>...</td>\n",
       "      <td>11211891.0</td>\n",
       "      <td>11445072.0</td>\n",
       "      <td>11827802.0</td>\n",
       "      <td>12039345</td>\n",
       "      <td>12361248</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>21477 rows × 57 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       Area Code  Element Code   latitude  longitude      Y1961  ...  \\\n",
       "100            2          5142      33.94      67.71     1928.0  ...   \n",
       "101            4         10284      67.88     135.42     2111.0  ...   \n",
       "102            6         15805     101.82     203.13     2187.0  ...   \n",
       "103            8         20947     135.76     270.84     2424.0  ...   \n",
       "104           10         26468     169.70     338.55     2634.0  ...   \n",
       "...          ...           ...        ...        ...        ...  ...   \n",
       "21572    2693553     111910458  439293.89  339100.70  3502578.0  ...   \n",
       "21573    2693734     111915979  439274.87  339129.85  3502605.0  ...   \n",
       "21574    2693915     111921121  439255.85  339159.00  3502611.0  ...   \n",
       "21575    2694096     111926263  439236.83  339188.15  3502611.0  ...   \n",
       "21576    2694277     111931405  439217.81  339217.30  3502611.0  ...   \n",
       "\n",
       "            Y2009       Y2010       Y2011     Y2012     Y2013  \n",
       "100        4538.0      4605.0      4711.0      4810      4895  \n",
       "101        4953.0      5047.0      5187.0      5235      5317  \n",
       "102        5332.0      5362.0      5390.0      5602      5677  \n",
       "103        5387.0      5422.0      5462.0      5680      5766  \n",
       "104        5582.0      5600.0      5653.0      5880      5966  \n",
       "...           ...         ...         ...       ...       ...  \n",
       "21572  11211868.0  11445028.0  11827747.0  12039290  12361193  \n",
       "21573  11211873.0  11445043.0  11827762.0  12039305  12361208  \n",
       "21574  11211891.0  11445072.0  11827802.0  12039345  12361248  \n",
       "21575  11211891.0  11445072.0  11827802.0  12039345  12361248  \n",
       "21576  11211891.0  11445072.0  11827802.0  12039345  12361248  \n",
       "\n",
       "[21477 rows x 57 columns]"
      ]
     },
     "execution_count": 83,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_rel[df_rel.columns[df_rel.dtypes != 'object']].cumsum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 84,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-03-15T06:56:25.252557Z",
     "start_time": "2021-03-15T06:56:25.223634Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Area Code                         1\n",
       "Area                    Afghanistan\n",
       "Item Code                      2511\n",
       "Item            Alcoholic Beverages\n",
       "Element Code                   5142\n",
       "                       ...         \n",
       "Y2009                             0\n",
       "Y2010                             0\n",
       "Y2011                             0\n",
       "Y2012                          -169\n",
       "Y2013                          -246\n",
       "Length: 62, dtype: object"
      ]
     },
     "execution_count": 84,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_rel.min()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 85,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-03-15T06:56:25.643396Z",
     "start_time": "2021-03-15T06:56:25.254524Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Area Code        125.449411\n",
       "Item Code               inf\n",
       "Element Code    5211.687154\n",
       "latitude          20.450613\n",
       "longitude         15.794445\n",
       "                   ...     \n",
       "Y2009            524.581996\n",
       "Y2010            535.492069\n",
       "Y2011            553.399242\n",
       "Y2012            560.569214\n",
       "Y2013            575.557480\n",
       "Length: 58, dtype: float64"
      ]
     },
     "execution_count": 85,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_rel.mean()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 86,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-03-15T06:56:25.688283Z",
     "start_time": "2021-03-15T06:56:25.645362Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Area Code        120.00\n",
       "Item Code       2640.00\n",
       "Element Code    5142.00\n",
       "latitude          20.59\n",
       "longitude         19.15\n",
       "                 ...   \n",
       "Y2009              7.00\n",
       "Y2010              7.00\n",
       "Y2011              8.00\n",
       "Y2012              8.00\n",
       "Y2013              8.00\n",
       "Length: 58, dtype: float64"
      ]
     },
     "execution_count": 86,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_rel.median()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 87,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-03-15T06:56:25.718203Z",
     "start_time": "2021-03-15T06:56:25.690273Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Area Code       5.309767e+03\n",
       "Element Code    2.155614e+04\n",
       "latitude        6.065550e+02\n",
       "longitude       4.357598e+03\n",
       "Y1961           3.474960e+06\n",
       "                    ...     \n",
       "Y2009           3.075744e+07\n",
       "Y2010           3.273086e+07\n",
       "Y2011           3.461053e+07\n",
       "Y2012           3.657771e+07\n",
       "Y2013           3.866824e+07\n",
       "Length: 57, dtype: float64"
      ]
     },
     "execution_count": 87,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_rel.var()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 88,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-03-15T06:56:25.748127Z",
     "start_time": "2021-03-15T06:56:25.719202Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Area Code         72.868149\n",
       "Element Code     146.820079\n",
       "latitude          24.628336\n",
       "longitude         66.012104\n",
       "Y1961           1864.124336\n",
       "                   ...     \n",
       "Y2009           5545.939303\n",
       "Y2010           5721.089425\n",
       "Y2011           5883.071604\n",
       "Y2012           6047.950804\n",
       "Y2013           6218.379479\n",
       "Length: 57, dtype: float64"
      ]
     },
     "execution_count": 88,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_rel.std()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 89,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-03-15T06:56:25.763073Z",
     "start_time": "2021-03-15T06:56:25.750084Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "100        2\n",
      "101        2\n",
      "102        2\n",
      "103        2\n",
      "104        2\n",
      "        ... \n",
      "21572    181\n",
      "21573    181\n",
      "21574    181\n",
      "21575    181\n",
      "21576    181\n",
      "Name: Area Code, Length: 21477, dtype: int64\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "array([  2,   3,   4,   7,   8,   9,   1,  10,  11,  52,  12,  16,  14,\n",
       "        57, 255,  23,  53,  17,  19,  80,  20,  21,  26,  27, 233,  35,\n",
       "       115,  32,  33,  37,  39,  40,  96, 128,  41, 214,  44,  46,  48,\n",
       "       107,  98,  49,  50, 167, 116,  54,  72,  55,  56,  58,  59,  60,\n",
       "        63, 238,  66,  67,  68,  70,  74,  75,  73,  79,  81,  84,  86,\n",
       "        89,  90, 175,  91,  93,  95,  97,  99, 100, 101, 102, 103, 104,\n",
       "       105, 106, 109, 110, 112, 108, 114,  83, 118, 113, 120, 119, 121,\n",
       "       122, 123, 126, 256, 129, 130, 131, 132, 133, 134, 136, 137, 138,\n",
       "       141, 273, 143, 144,  28, 147, 149, 150, 153, 156, 157, 158, 159,\n",
       "       162, 221, 165, 166, 169, 170, 171, 173, 174, 117, 146, 183, 185,\n",
       "       184, 188, 189, 191, 244, 193, 194, 195, 272, 197, 199, 198,  25,\n",
       "       202, 203,  38, 276, 207, 209, 210, 211, 208, 216, 154, 176, 217,\n",
       "       220, 222, 223, 213, 226, 230, 225, 229, 215, 231, 234, 235, 155,\n",
       "       236, 237, 249, 251, 181], dtype=int64)"
      ]
     },
     "execution_count": 89,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "print(df_rel['Area Code'])\n",
    "df_rel['Area Code'].unique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 90,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-03-15T06:56:25.778037Z",
     "start_time": "2021-03-15T06:56:25.764069Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "100      False\n",
       "101      False\n",
       "102      False\n",
       "103      False\n",
       "104      False\n",
       "         ...  \n",
       "21572    False\n",
       "21573    False\n",
       "21574    False\n",
       "21575    False\n",
       "21576    False\n",
       "Name: Area Code, Length: 21477, dtype: bool"
      ]
     },
     "execution_count": 90,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_rel['Area Code'].isin([203])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 91,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-03-15T06:56:25.792968Z",
     "start_time": "2021-03-15T06:56:25.779004Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "150"
      ]
     },
     "execution_count": 91,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_rel['Area Code'].isin([203]).sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 92,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-03-15T06:56:25.807928Z",
     "start_time": "2021-03-15T06:56:25.794963Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "148"
      ]
     },
     "execution_count": 92,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_rel['Area Code'].isin([106]).sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 93,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-03-15T06:56:25.823886Z",
     "start_time": "2021-03-15T06:56:25.809923Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "203    150\n",
       "106    148\n",
       "79     147\n",
       "41     146\n",
       "110    143\n",
       "      ... \n",
       "175     91\n",
       "213     90\n",
       "176     86\n",
       "2       83\n",
       "122     75\n",
       "Name: Area Code, Length: 174, dtype: int64"
      ]
     },
     "execution_count": 93,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_rel['Area Code'].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 94,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-03-15T06:56:25.838872Z",
     "start_time": "2021-03-15T06:56:25.824914Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(10867788.0,\n",
       " 508.48210358863986,\n",
       " 7.0,\n",
       " 1994,\n",
       " 21373,\n",
       " 402975.0,\n",
       " 0.0,\n",
       " 104,\n",
       " 100      4164.0\n",
       " 101       455.0\n",
       " 102       263.0\n",
       " 103        48.0\n",
       " 104       249.0\n",
       "           ...  \n",
       " 21572     356.0\n",
       " 21573       6.0\n",
       " 21574      14.0\n",
       " 21575       0.0\n",
       " 21576       0.0\n",
       " Name: Y2007, Length: 21477, dtype: float64)"
      ]
     },
     "execution_count": 94,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_rel['Y2007'].sum(), df_rel['Y2007'].mean(), df_rel['Y2007'].median(), \\\n",
    "df_rel['Y2007'].nunique(), df_rel['Y2007'].count(), df_rel['Y2007'].max(), df_rel['Y2007'].min(), \\\n",
    "df_rel['Y2007'].isna().sum(), df_rel['Y2007'].fillna(0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 95,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-03-15T06:56:25.853805Z",
     "start_time": "2021-03-15T06:56:25.839842Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "count     21373.000000\n",
       "mean        508.482104\n",
       "std        5298.939807\n",
       "min           0.000000\n",
       "25%           0.000000\n",
       "50%           7.000000\n",
       "75%          80.000000\n",
       "max      402975.000000\n",
       "Name: Y2007, dtype: float64"
      ]
     },
     "execution_count": 95,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_rel['Y2007'].describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 96,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-03-15T06:56:25.868766Z",
     "start_time": "2021-03-15T06:56:25.854827Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "count     21477\n",
       "unique      174\n",
       "top       Spain\n",
       "freq        150\n",
       "Name: Area, dtype: object"
      ]
     },
     "execution_count": 96,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_rel['Area'].describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 97,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-03-15T06:56:26.003408Z",
     "start_time": "2021-03-15T06:56:25.870791Z"
    },
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Area Code</th>\n",
       "      <th>Element Code</th>\n",
       "      <th>latitude</th>\n",
       "      <th>longitude</th>\n",
       "      <th>Y1961</th>\n",
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       "      <td>21477.000000</td>\n",
       "      <td>21477.000000</td>\n",
       "      <td>21477.000000</td>\n",
       "      <td>17938.000000</td>\n",
       "      <td>...</td>\n",
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       "      <td>21373.000000</td>\n",
       "      <td>21477.000000</td>\n",
       "      <td>21477.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
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       "      <td>125.449411</td>\n",
       "      <td>5211.687154</td>\n",
       "      <td>20.450613</td>\n",
       "      <td>15.794445</td>\n",
       "      <td>195.262069</td>\n",
       "      <td>...</td>\n",
       "      <td>524.581996</td>\n",
       "      <td>535.492069</td>\n",
       "      <td>553.399242</td>\n",
       "      <td>560.569214</td>\n",
       "      <td>575.557480</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>72.868149</td>\n",
       "      <td>146.820079</td>\n",
       "      <td>24.628336</td>\n",
       "      <td>66.012104</td>\n",
       "      <td>1864.124336</td>\n",
       "      <td>...</td>\n",
       "      <td>5545.939303</td>\n",
       "      <td>5721.089425</td>\n",
       "      <td>5883.071604</td>\n",
       "      <td>6047.950804</td>\n",
       "      <td>6218.379479</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>5142.000000</td>\n",
       "      <td>-40.900000</td>\n",
       "      <td>-172.100000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>-169.000000</td>\n",
       "      <td>-246.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>63.000000</td>\n",
       "      <td>5142.000000</td>\n",
       "      <td>6.430000</td>\n",
       "      <td>-11.780000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>120.000000</td>\n",
       "      <td>5142.000000</td>\n",
       "      <td>20.590000</td>\n",
       "      <td>19.150000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>7.000000</td>\n",
       "      <td>7.000000</td>\n",
       "      <td>8.000000</td>\n",
       "      <td>8.000000</td>\n",
       "      <td>8.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>188.000000</td>\n",
       "      <td>5142.000000</td>\n",
       "      <td>41.150000</td>\n",
       "      <td>46.870000</td>\n",
       "      <td>21.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>83.000000</td>\n",
       "      <td>83.000000</td>\n",
       "      <td>86.000000</td>\n",
       "      <td>88.000000</td>\n",
       "      <td>90.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>276.000000</td>\n",
       "      <td>5521.000000</td>\n",
       "      <td>64.960000</td>\n",
       "      <td>179.410000</td>\n",
       "      <td>112227.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>434724.000000</td>\n",
       "      <td>451838.000000</td>\n",
       "      <td>462696.000000</td>\n",
       "      <td>479028.000000</td>\n",
       "      <td>489299.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>8 rows × 57 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "          Area Code  Element Code      latitude     longitude          Y1961  \\\n",
       "count  21477.000000  21477.000000  21477.000000  21477.000000   17938.000000   \n",
       "mean     125.449411   5211.687154     20.450613     15.794445     195.262069   \n",
       "std       72.868149    146.820079     24.628336     66.012104    1864.124336   \n",
       "min        1.000000   5142.000000    -40.900000   -172.100000       0.000000   \n",
       "25%       63.000000   5142.000000      6.430000    -11.780000       0.000000   \n",
       "50%      120.000000   5142.000000     20.590000     19.150000       1.000000   \n",
       "75%      188.000000   5142.000000     41.150000     46.870000      21.000000   \n",
       "max      276.000000   5521.000000     64.960000    179.410000  112227.000000   \n",
       "\n",
       "       ...          Y2009          Y2010          Y2011          Y2012  \\\n",
       "count  ...   21373.000000   21373.000000   21373.000000   21477.000000   \n",
       "mean   ...     524.581996     535.492069     553.399242     560.569214   \n",
       "std    ...    5545.939303    5721.089425    5883.071604    6047.950804   \n",
       "min    ...       0.000000       0.000000       0.000000    -169.000000   \n",
       "25%    ...       0.000000       0.000000       0.000000       0.000000   \n",
       "50%    ...       7.000000       7.000000       8.000000       8.000000   \n",
       "75%    ...      83.000000      83.000000      86.000000      88.000000   \n",
       "max    ...  434724.000000  451838.000000  462696.000000  479028.000000   \n",
       "\n",
       "               Y2013  \n",
       "count   21477.000000  \n",
       "mean      575.557480  \n",
       "std      6218.379479  \n",
       "min      -246.000000  \n",
       "25%         0.000000  \n",
       "50%         8.000000  \n",
       "75%        90.000000  \n",
       "max    489299.000000  \n",
       "\n",
       "[8 rows x 57 columns]"
      ]
     },
     "execution_count": 97,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_rel.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 98,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-03-15T06:56:26.139042Z",
     "start_time": "2021-03-15T06:56:26.006398Z"
    }
   },
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>count</th>\n",
       "      <th>mean</th>\n",
       "      <th>std</th>\n",
       "      <th>min</th>\n",
       "      <th>25%</th>\n",
       "      <th>50%</th>\n",
       "      <th>75%</th>\n",
       "      <th>max</th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Area Code</th>\n",
       "      <td>21477.0</td>\n",
       "      <td>125.449411</td>\n",
       "      <td>72.868149</td>\n",
       "      <td>1.0</td>\n",
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       "      <td>188.00</td>\n",
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       "    <tr>\n",
       "      <th>Element Code</th>\n",
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       "      <td>5142.0</td>\n",
       "      <td>5142.00</td>\n",
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       "      <td>5142.00</td>\n",
       "      <td>5521.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>latitude</th>\n",
       "      <td>21477.0</td>\n",
       "      <td>20.450613</td>\n",
       "      <td>24.628336</td>\n",
       "      <td>-40.9</td>\n",
       "      <td>6.43</td>\n",
       "      <td>20.59</td>\n",
       "      <td>41.15</td>\n",
       "      <td>64.96</td>\n",
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       "    <tr>\n",
       "      <th>longitude</th>\n",
       "      <td>21477.0</td>\n",
       "      <td>15.794445</td>\n",
       "      <td>66.012104</td>\n",
       "      <td>-172.1</td>\n",
       "      <td>-11.78</td>\n",
       "      <td>19.15</td>\n",
       "      <td>46.87</td>\n",
       "      <td>179.41</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Y1961</th>\n",
       "      <td>17938.0</td>\n",
       "      <td>195.262069</td>\n",
       "      <td>1864.124336</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>1.00</td>\n",
       "      <td>21.00</td>\n",
       "      <td>112227.00</td>\n",
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       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
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       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Y2009</th>\n",
       "      <td>21373.0</td>\n",
       "      <td>524.581996</td>\n",
       "      <td>5545.939303</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>7.00</td>\n",
       "      <td>83.00</td>\n",
       "      <td>434724.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Y2010</th>\n",
       "      <td>21373.0</td>\n",
       "      <td>535.492069</td>\n",
       "      <td>5721.089425</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>7.00</td>\n",
       "      <td>83.00</td>\n",
       "      <td>451838.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Y2011</th>\n",
       "      <td>21373.0</td>\n",
       "      <td>553.399242</td>\n",
       "      <td>5883.071604</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>8.00</td>\n",
       "      <td>86.00</td>\n",
       "      <td>462696.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Y2012</th>\n",
       "      <td>21477.0</td>\n",
       "      <td>560.569214</td>\n",
       "      <td>6047.950804</td>\n",
       "      <td>-169.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>8.00</td>\n",
       "      <td>88.00</td>\n",
       "      <td>479028.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Y2013</th>\n",
       "      <td>21477.0</td>\n",
       "      <td>575.557480</td>\n",
       "      <td>6218.379479</td>\n",
       "      <td>-246.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>8.00</td>\n",
       "      <td>90.00</td>\n",
       "      <td>489299.00</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>57 rows × 8 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                count         mean          std     min      25%      50%  \\\n",
       "Area Code     21477.0   125.449411    72.868149     1.0    63.00   120.00   \n",
       "Element Code  21477.0  5211.687154   146.820079  5142.0  5142.00  5142.00   \n",
       "latitude      21477.0    20.450613    24.628336   -40.9     6.43    20.59   \n",
       "longitude     21477.0    15.794445    66.012104  -172.1   -11.78    19.15   \n",
       "Y1961         17938.0   195.262069  1864.124336     0.0     0.00     1.00   \n",
       "...               ...          ...          ...     ...      ...      ...   \n",
       "Y2009         21373.0   524.581996  5545.939303     0.0     0.00     7.00   \n",
       "Y2010         21373.0   535.492069  5721.089425     0.0     0.00     7.00   \n",
       "Y2011         21373.0   553.399242  5883.071604     0.0     0.00     8.00   \n",
       "Y2012         21477.0   560.569214  6047.950804  -169.0     0.00     8.00   \n",
       "Y2013         21477.0   575.557480  6218.379479  -246.0     0.00     8.00   \n",
       "\n",
       "                  75%        max  \n",
       "Area Code      188.00     276.00  \n",
       "Element Code  5142.00    5521.00  \n",
       "latitude        41.15      64.96  \n",
       "longitude       46.87     179.41  \n",
       "Y1961           21.00  112227.00  \n",
       "...               ...        ...  \n",
       "Y2009           83.00  434724.00  \n",
       "Y2010           83.00  451838.00  \n",
       "Y2011           86.00  462696.00  \n",
       "Y2012           88.00  479028.00  \n",
       "Y2013           90.00  489299.00  \n",
       "\n",
       "[57 rows x 8 columns]"
      ]
     },
     "execution_count": 98,
     "metadata": {},
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    }
   ],
   "source": [
    "df_rel.describe().T"
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   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 결과 출력(Exporting and Saving)\n",
    "\n",
    "- **목적:** 데이터 전처리 또는 정리가 끝난 결과를 \"파일\"로 저장해 두는 것이 필요\n",
    "> - to_csv는 DataFrame을 CSV 파일에 기록\n",
    "> - to_excel은 DataFrame 정보를 Excel 파일에 기록"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 99,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-03-15T06:56:26.962868Z",
     "start_time": "2021-03-15T06:56:26.140039Z"
    }
   },
   "outputs": [],
   "source": [
    "# Output data to a CSV file\n",
    "# index=False: don't want row numbers\n",
    "# utf8: to avoid character issues\n",
    "df_rel.to_csv(\"Tutorial_Pandas_Output.csv\", index=False, encoding='utf8')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 100,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-03-15T06:56:42.419622Z",
     "start_time": "2021-03-15T06:56:26.963866Z"
    }
   },
   "outputs": [],
   "source": [
    "# Output data to an Excel file.\n",
    "df_rel.to_excel(\"Tutorial_Pandas_Output.xlsx\", sheet_name=\"Sheet 1\", index=False)"
   ]
  }
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