Visualization_Seaborn_Regression_Plot.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Importing the libraries"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 218,
   "metadata": {},
   "outputs": [],
   "source": [
    "from __future__ import print_function    #adds compatibility to Python2\n",
    "import pandas as pd\n",
    "import numpy as np"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 219,
   "metadata": {},
   "outputs": [],
   "source": [
    "#using the inline backend\n",
    "%matplotlib inline\n",
    "import matplotlib as mpl\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 220,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Matplotlib version: 3.1.3\n"
     ]
    }
   ],
   "source": [
    "print(\"Matplotlib version:\", mpl.__version__)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 221,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['bmh', 'classic', 'dark_background', 'fast', 'fivethirtyeight', 'ggplot', 'grayscale', 'seaborn-bright', 'seaborn-colorblind', 'seaborn-dark-palette', 'seaborn-dark', 'seaborn-darkgrid', 'seaborn-deep', 'seaborn-muted', 'seaborn-notebook', 'seaborn-paper', 'seaborn-pastel', 'seaborn-poster', 'seaborn-talk', 'seaborn-ticks', 'seaborn-white', 'seaborn-whitegrid', 'seaborn', 'Solarize_Light2', 'tableau-colorblind10', '_classic_test']\n"
     ]
    }
   ],
   "source": [
    "print(plt.style.available)\n",
    "mpl.style.use(['ggplot'])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Importing the dataset"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 222,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_can = pd.read_excel(\"Canada.xlsx\", sheet_name= \"Canada by Citizenship\", skiprows= range(20), skipfooter=2)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Basic Operations and cleaning"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 223,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Type</th>\n",
       "      <th>Coverage</th>\n",
       "      <th>OdName</th>\n",
       "      <th>AREA</th>\n",
       "      <th>AreaName</th>\n",
       "      <th>REG</th>\n",
       "      <th>RegName</th>\n",
       "      <th>DEV</th>\n",
       "      <th>DevName</th>\n",
       "      <th>1980</th>\n",
       "      <th>...</th>\n",
       "      <th>2004</th>\n",
       "      <th>2005</th>\n",
       "      <th>2006</th>\n",
       "      <th>2007</th>\n",
       "      <th>2008</th>\n",
       "      <th>2009</th>\n",
       "      <th>2010</th>\n",
       "      <th>2011</th>\n",
       "      <th>2012</th>\n",
       "      <th>2013</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Immigrants</td>\n",
       "      <td>Foreigners</td>\n",
       "      <td>Afghanistan</td>\n",
       "      <td>935</td>\n",
       "      <td>Asia</td>\n",
       "      <td>5501</td>\n",
       "      <td>Southern Asia</td>\n",
       "      <td>902</td>\n",
       "      <td>Developing regions</td>\n",
       "      <td>16</td>\n",
       "      <td>...</td>\n",
       "      <td>2978</td>\n",
       "      <td>3436</td>\n",
       "      <td>3009</td>\n",
       "      <td>2652</td>\n",
       "      <td>2111</td>\n",
       "      <td>1746</td>\n",
       "      <td>1758</td>\n",
       "      <td>2203</td>\n",
       "      <td>2635</td>\n",
       "      <td>2004</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Immigrants</td>\n",
       "      <td>Foreigners</td>\n",
       "      <td>Albania</td>\n",
       "      <td>908</td>\n",
       "      <td>Europe</td>\n",
       "      <td>925</td>\n",
       "      <td>Southern Europe</td>\n",
       "      <td>901</td>\n",
       "      <td>Developed regions</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>1450</td>\n",
       "      <td>1223</td>\n",
       "      <td>856</td>\n",
       "      <td>702</td>\n",
       "      <td>560</td>\n",
       "      <td>716</td>\n",
       "      <td>561</td>\n",
       "      <td>539</td>\n",
       "      <td>620</td>\n",
       "      <td>603</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Immigrants</td>\n",
       "      <td>Foreigners</td>\n",
       "      <td>Algeria</td>\n",
       "      <td>903</td>\n",
       "      <td>Africa</td>\n",
       "      <td>912</td>\n",
       "      <td>Northern Africa</td>\n",
       "      <td>902</td>\n",
       "      <td>Developing regions</td>\n",
       "      <td>80</td>\n",
       "      <td>...</td>\n",
       "      <td>3616</td>\n",
       "      <td>3626</td>\n",
       "      <td>4807</td>\n",
       "      <td>3623</td>\n",
       "      <td>4005</td>\n",
       "      <td>5393</td>\n",
       "      <td>4752</td>\n",
       "      <td>4325</td>\n",
       "      <td>3774</td>\n",
       "      <td>4331</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Immigrants</td>\n",
       "      <td>Foreigners</td>\n",
       "      <td>American Samoa</td>\n",
       "      <td>909</td>\n",
       "      <td>Oceania</td>\n",
       "      <td>957</td>\n",
       "      <td>Polynesia</td>\n",
       "      <td>902</td>\n",
       "      <td>Developing regions</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Immigrants</td>\n",
       "      <td>Foreigners</td>\n",
       "      <td>Andorra</td>\n",
       "      <td>908</td>\n",
       "      <td>Europe</td>\n",
       "      <td>925</td>\n",
       "      <td>Southern Europe</td>\n",
       "      <td>901</td>\n",
       "      <td>Developed regions</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 43 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "         Type    Coverage          OdName  AREA AreaName   REG  \\\n",
       "0  Immigrants  Foreigners     Afghanistan   935     Asia  5501   \n",
       "1  Immigrants  Foreigners         Albania   908   Europe   925   \n",
       "2  Immigrants  Foreigners         Algeria   903   Africa   912   \n",
       "3  Immigrants  Foreigners  American Samoa   909  Oceania   957   \n",
       "4  Immigrants  Foreigners         Andorra   908   Europe   925   \n",
       "\n",
       "           RegName  DEV             DevName  1980  ...  2004  2005  2006  \\\n",
       "0    Southern Asia  902  Developing regions    16  ...  2978  3436  3009   \n",
       "1  Southern Europe  901   Developed regions     1  ...  1450  1223   856   \n",
       "2  Northern Africa  902  Developing regions    80  ...  3616  3626  4807   \n",
       "3        Polynesia  902  Developing regions     0  ...     0     0     1   \n",
       "4  Southern Europe  901   Developed regions     0  ...     0     0     1   \n",
       "\n",
       "   2007  2008  2009  2010  2011  2012  2013  \n",
       "0  2652  2111  1746  1758  2203  2635  2004  \n",
       "1   702   560   716   561   539   620   603  \n",
       "2  3623  4005  5393  4752  4325  3774  4331  \n",
       "3     0     0     0     0     0     0     0  \n",
       "4     1     0     0     0     0     1     1  \n",
       "\n",
       "[5 rows x 43 columns]"
      ]
     },
     "execution_count": 223,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_can.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 224,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 195 entries, 0 to 194\n",
      "Data columns (total 43 columns):\n",
      " #   Column    Non-Null Count  Dtype \n",
      "---  ------    --------------  ----- \n",
      " 0   Type      195 non-null    object\n",
      " 1   Coverage  195 non-null    object\n",
      " 2   OdName    195 non-null    object\n",
      " 3   AREA      195 non-null    int64 \n",
      " 4   AreaName  195 non-null    object\n",
      " 5   REG       195 non-null    int64 \n",
      " 6   RegName   195 non-null    object\n",
      " 7   DEV       195 non-null    int64 \n",
      " 8   DevName   195 non-null    object\n",
      " 9   1980      195 non-null    int64 \n",
      " 10  1981      195 non-null    int64 \n",
      " 11  1982      195 non-null    int64 \n",
      " 12  1983      195 non-null    int64 \n",
      " 13  1984      195 non-null    int64 \n",
      " 14  1985      195 non-null    int64 \n",
      " 15  1986      195 non-null    int64 \n",
      " 16  1987      195 non-null    int64 \n",
      " 17  1988      195 non-null    int64 \n",
      " 18  1989      195 non-null    int64 \n",
      " 19  1990      195 non-null    int64 \n",
      " 20  1991      195 non-null    int64 \n",
      " 21  1992      195 non-null    int64 \n",
      " 22  1993      195 non-null    int64 \n",
      " 23  1994      195 non-null    int64 \n",
      " 24  1995      195 non-null    int64 \n",
      " 25  1996      195 non-null    int64 \n",
      " 26  1997      195 non-null    int64 \n",
      " 27  1998      195 non-null    int64 \n",
      " 28  1999      195 non-null    int64 \n",
      " 29  2000      195 non-null    int64 \n",
      " 30  2001      195 non-null    int64 \n",
      " 31  2002      195 non-null    int64 \n",
      " 32  2003      195 non-null    int64 \n",
      " 33  2004      195 non-null    int64 \n",
      " 34  2005      195 non-null    int64 \n",
      " 35  2006      195 non-null    int64 \n",
      " 36  2007      195 non-null    int64 \n",
      " 37  2008      195 non-null    int64 \n",
      " 38  2009      195 non-null    int64 \n",
      " 39  2010      195 non-null    int64 \n",
      " 40  2011      195 non-null    int64 \n",
      " 41  2012      195 non-null    int64 \n",
      " 42  2013      195 non-null    int64 \n",
      "dtypes: int64(37), object(6)\n",
      "memory usage: 65.6+ KB\n"
     ]
    }
   ],
   "source": [
    "df_can.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 225,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['Type', 'Coverage', 'OdName', 'AREA', 'AreaName', 'REG', 'RegName',\n",
       "       'DEV', 'DevName', 1980, 1981, 1982, 1983, 1984, 1985, 1986, 1987,\n",
       "       1988, 1989, 1990, 1991, 1992, 1993, 1994, 1995, 1996, 1997, 1998,\n",
       "       1999, 2000, 2001, 2002, 2003, 2004, 2005, 2006, 2007, 2008, 2009,\n",
       "       2010, 2011, 2012, 2013], dtype=object)"
      ]
     },
     "execution_count": 225,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_can.columns.values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 226,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(195, 43)"
      ]
     },
     "execution_count": 226,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_can.shape"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Clean the dataset to remove some columns which are not required"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 227,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_can.drop(['Type','Coverage','REG','AREA','DEV'], axis=1, inplace=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Rename some columns "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 228,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_can.rename(columns= {\"OdName\":\"Country\", \"AreaName\":\"Continent\", \"RegName\":\"Region\"}, inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 229,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "    }\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>Country</th>\n",
       "      <th>Continent</th>\n",
       "      <th>Region</th>\n",
       "      <th>DevName</th>\n",
       "      <th>1980</th>\n",
       "      <th>1981</th>\n",
       "      <th>1982</th>\n",
       "      <th>1983</th>\n",
       "      <th>1984</th>\n",
       "      <th>1985</th>\n",
       "      <th>...</th>\n",
       "      <th>2004</th>\n",
       "      <th>2005</th>\n",
       "      <th>2006</th>\n",
       "      <th>2007</th>\n",
       "      <th>2008</th>\n",
       "      <th>2009</th>\n",
       "      <th>2010</th>\n",
       "      <th>2011</th>\n",
       "      <th>2012</th>\n",
       "      <th>2013</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Afghanistan</td>\n",
       "      <td>Asia</td>\n",
       "      <td>Southern Asia</td>\n",
       "      <td>Developing regions</td>\n",
       "      <td>16</td>\n",
       "      <td>39</td>\n",
       "      <td>39</td>\n",
       "      <td>47</td>\n",
       "      <td>71</td>\n",
       "      <td>340</td>\n",
       "      <td>...</td>\n",
       "      <td>2978</td>\n",
       "      <td>3436</td>\n",
       "      <td>3009</td>\n",
       "      <td>2652</td>\n",
       "      <td>2111</td>\n",
       "      <td>1746</td>\n",
       "      <td>1758</td>\n",
       "      <td>2203</td>\n",
       "      <td>2635</td>\n",
       "      <td>2004</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Albania</td>\n",
       "      <td>Europe</td>\n",
       "      <td>Southern Europe</td>\n",
       "      <td>Developed regions</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>1450</td>\n",
       "      <td>1223</td>\n",
       "      <td>856</td>\n",
       "      <td>702</td>\n",
       "      <td>560</td>\n",
       "      <td>716</td>\n",
       "      <td>561</td>\n",
       "      <td>539</td>\n",
       "      <td>620</td>\n",
       "      <td>603</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Algeria</td>\n",
       "      <td>Africa</td>\n",
       "      <td>Northern Africa</td>\n",
       "      <td>Developing regions</td>\n",
       "      <td>80</td>\n",
       "      <td>67</td>\n",
       "      <td>71</td>\n",
       "      <td>69</td>\n",
       "      <td>63</td>\n",
       "      <td>44</td>\n",
       "      <td>...</td>\n",
       "      <td>3616</td>\n",
       "      <td>3626</td>\n",
       "      <td>4807</td>\n",
       "      <td>3623</td>\n",
       "      <td>4005</td>\n",
       "      <td>5393</td>\n",
       "      <td>4752</td>\n",
       "      <td>4325</td>\n",
       "      <td>3774</td>\n",
       "      <td>4331</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>American Samoa</td>\n",
       "      <td>Oceania</td>\n",
       "      <td>Polynesia</td>\n",
       "      <td>Developing regions</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Andorra</td>\n",
       "      <td>Europe</td>\n",
       "      <td>Southern Europe</td>\n",
       "      <td>Developed regions</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 38 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "          Country Continent           Region             DevName  1980  1981  \\\n",
       "0     Afghanistan      Asia    Southern Asia  Developing regions    16    39   \n",
       "1         Albania    Europe  Southern Europe   Developed regions     1     0   \n",
       "2         Algeria    Africa  Northern Africa  Developing regions    80    67   \n",
       "3  American Samoa   Oceania        Polynesia  Developing regions     0     1   \n",
       "4         Andorra    Europe  Southern Europe   Developed regions     0     0   \n",
       "\n",
       "   1982  1983  1984  1985  ...  2004  2005  2006  2007  2008  2009  2010  \\\n",
       "0    39    47    71   340  ...  2978  3436  3009  2652  2111  1746  1758   \n",
       "1     0     0     0     0  ...  1450  1223   856   702   560   716   561   \n",
       "2    71    69    63    44  ...  3616  3626  4807  3623  4005  5393  4752   \n",
       "3     0     0     0     0  ...     0     0     1     0     0     0     0   \n",
       "4     0     0     0     0  ...     0     0     1     1     0     0     0   \n",
       "\n",
       "   2011  2012  2013  \n",
       "0  2203  2635  2004  \n",
       "1   539   620   603  \n",
       "2  4325  3774  4331  \n",
       "3     0     0     0  \n",
       "4     0     1     1  \n",
       "\n",
       "[5 rows x 38 columns]"
      ]
     },
     "execution_count": 229,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_can.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Adding the Total column"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 230,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_can[\"Total\"]=df_can.sum(axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 231,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Country      0\n",
       "Continent    0\n",
       "Region       0\n",
       "DevName      0\n",
       "1980         0\n",
       "1981         0\n",
       "1982         0\n",
       "1983         0\n",
       "1984         0\n",
       "1985         0\n",
       "1986         0\n",
       "1987         0\n",
       "1988         0\n",
       "1989         0\n",
       "1990         0\n",
       "1991         0\n",
       "1992         0\n",
       "1993         0\n",
       "1994         0\n",
       "1995         0\n",
       "1996         0\n",
       "1997         0\n",
       "1998         0\n",
       "1999         0\n",
       "2000         0\n",
       "2001         0\n",
       "2002         0\n",
       "2003         0\n",
       "2004         0\n",
       "2005         0\n",
       "2006         0\n",
       "2007         0\n",
       "2008         0\n",
       "2009         0\n",
       "2010         0\n",
       "2011         0\n",
       "2012         0\n",
       "2013         0\n",
       "Total        0\n",
       "dtype: int64"
      ]
     },
     "execution_count": 231,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_can.isnull().sum()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Indexing the dataset"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 232,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_can.set_index(\"Country\", inplace=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Opposite of the set_index() function is reset_index() function."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 233,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Continent</th>\n",
       "      <th>Region</th>\n",
       "      <th>DevName</th>\n",
       "      <th>1980</th>\n",
       "      <th>1981</th>\n",
       "      <th>1982</th>\n",
       "      <th>1983</th>\n",
       "      <th>1984</th>\n",
       "      <th>1985</th>\n",
       "      <th>1986</th>\n",
       "      <th>...</th>\n",
       "      <th>2005</th>\n",
       "      <th>2006</th>\n",
       "      <th>2007</th>\n",
       "      <th>2008</th>\n",
       "      <th>2009</th>\n",
       "      <th>2010</th>\n",
       "      <th>2011</th>\n",
       "      <th>2012</th>\n",
       "      <th>2013</th>\n",
       "      <th>Total</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Country</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",
       "      <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>Afghanistan</th>\n",
       "      <td>Asia</td>\n",
       "      <td>Southern Asia</td>\n",
       "      <td>Developing regions</td>\n",
       "      <td>16</td>\n",
       "      <td>39</td>\n",
       "      <td>39</td>\n",
       "      <td>47</td>\n",
       "      <td>71</td>\n",
       "      <td>340</td>\n",
       "      <td>496</td>\n",
       "      <td>...</td>\n",
       "      <td>3436</td>\n",
       "      <td>3009</td>\n",
       "      <td>2652</td>\n",
       "      <td>2111</td>\n",
       "      <td>1746</td>\n",
       "      <td>1758</td>\n",
       "      <td>2203</td>\n",
       "      <td>2635</td>\n",
       "      <td>2004</td>\n",
       "      <td>58639</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Albania</th>\n",
       "      <td>Europe</td>\n",
       "      <td>Southern Europe</td>\n",
       "      <td>Developed regions</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>1223</td>\n",
       "      <td>856</td>\n",
       "      <td>702</td>\n",
       "      <td>560</td>\n",
       "      <td>716</td>\n",
       "      <td>561</td>\n",
       "      <td>539</td>\n",
       "      <td>620</td>\n",
       "      <td>603</td>\n",
       "      <td>15699</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Algeria</th>\n",
       "      <td>Africa</td>\n",
       "      <td>Northern Africa</td>\n",
       "      <td>Developing regions</td>\n",
       "      <td>80</td>\n",
       "      <td>67</td>\n",
       "      <td>71</td>\n",
       "      <td>69</td>\n",
       "      <td>63</td>\n",
       "      <td>44</td>\n",
       "      <td>69</td>\n",
       "      <td>...</td>\n",
       "      <td>3626</td>\n",
       "      <td>4807</td>\n",
       "      <td>3623</td>\n",
       "      <td>4005</td>\n",
       "      <td>5393</td>\n",
       "      <td>4752</td>\n",
       "      <td>4325</td>\n",
       "      <td>3774</td>\n",
       "      <td>4331</td>\n",
       "      <td>69439</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>American Samoa</th>\n",
       "      <td>Oceania</td>\n",
       "      <td>Polynesia</td>\n",
       "      <td>Developing regions</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Andorra</th>\n",
       "      <td>Europe</td>\n",
       "      <td>Southern Europe</td>\n",
       "      <td>Developed regions</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>15</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 38 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "               Continent           Region             DevName  1980  1981  \\\n",
       "Country                                                                     \n",
       "Afghanistan         Asia    Southern Asia  Developing regions    16    39   \n",
       "Albania           Europe  Southern Europe   Developed regions     1     0   \n",
       "Algeria           Africa  Northern Africa  Developing regions    80    67   \n",
       "American Samoa   Oceania        Polynesia  Developing regions     0     1   \n",
       "Andorra           Europe  Southern Europe   Developed regions     0     0   \n",
       "\n",
       "                1982  1983  1984  1985  1986  ...  2005  2006  2007  2008  \\\n",
       "Country                                       ...                           \n",
       "Afghanistan       39    47    71   340   496  ...  3436  3009  2652  2111   \n",
       "Albania            0     0     0     0     1  ...  1223   856   702   560   \n",
       "Algeria           71    69    63    44    69  ...  3626  4807  3623  4005   \n",
       "American Samoa     0     0     0     0     0  ...     0     1     0     0   \n",
       "Andorra            0     0     0     0     2  ...     0     1     1     0   \n",
       "\n",
       "                2009  2010  2011  2012  2013  Total  \n",
       "Country                                              \n",
       "Afghanistan     1746  1758  2203  2635  2004  58639  \n",
       "Albania          716   561   539   620   603  15699  \n",
       "Algeria         5393  4752  4325  3774  4331  69439  \n",
       "American Samoa     0     0     0     0     0      6  \n",
       "Andorra            0     0     0     1     1     15  \n",
       "\n",
       "[5 rows x 38 columns]"
      ]
     },
     "execution_count": 233,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_can.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 234,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_can.index.name=None"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 235,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Continent</th>\n",
       "      <th>Region</th>\n",
       "      <th>DevName</th>\n",
       "      <th>1980</th>\n",
       "      <th>1981</th>\n",
       "      <th>1982</th>\n",
       "      <th>1983</th>\n",
       "      <th>1984</th>\n",
       "      <th>1985</th>\n",
       "      <th>1986</th>\n",
       "      <th>...</th>\n",
       "      <th>2005</th>\n",
       "      <th>2006</th>\n",
       "      <th>2007</th>\n",
       "      <th>2008</th>\n",
       "      <th>2009</th>\n",
       "      <th>2010</th>\n",
       "      <th>2011</th>\n",
       "      <th>2012</th>\n",
       "      <th>2013</th>\n",
       "      <th>Total</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Afghanistan</th>\n",
       "      <td>Asia</td>\n",
       "      <td>Southern Asia</td>\n",
       "      <td>Developing regions</td>\n",
       "      <td>16</td>\n",
       "      <td>39</td>\n",
       "      <td>39</td>\n",
       "      <td>47</td>\n",
       "      <td>71</td>\n",
       "      <td>340</td>\n",
       "      <td>496</td>\n",
       "      <td>...</td>\n",
       "      <td>3436</td>\n",
       "      <td>3009</td>\n",
       "      <td>2652</td>\n",
       "      <td>2111</td>\n",
       "      <td>1746</td>\n",
       "      <td>1758</td>\n",
       "      <td>2203</td>\n",
       "      <td>2635</td>\n",
       "      <td>2004</td>\n",
       "      <td>58639</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Albania</th>\n",
       "      <td>Europe</td>\n",
       "      <td>Southern Europe</td>\n",
       "      <td>Developed regions</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>1223</td>\n",
       "      <td>856</td>\n",
       "      <td>702</td>\n",
       "      <td>560</td>\n",
       "      <td>716</td>\n",
       "      <td>561</td>\n",
       "      <td>539</td>\n",
       "      <td>620</td>\n",
       "      <td>603</td>\n",
       "      <td>15699</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Algeria</th>\n",
       "      <td>Africa</td>\n",
       "      <td>Northern Africa</td>\n",
       "      <td>Developing regions</td>\n",
       "      <td>80</td>\n",
       "      <td>67</td>\n",
       "      <td>71</td>\n",
       "      <td>69</td>\n",
       "      <td>63</td>\n",
       "      <td>44</td>\n",
       "      <td>69</td>\n",
       "      <td>...</td>\n",
       "      <td>3626</td>\n",
       "      <td>4807</td>\n",
       "      <td>3623</td>\n",
       "      <td>4005</td>\n",
       "      <td>5393</td>\n",
       "      <td>4752</td>\n",
       "      <td>4325</td>\n",
       "      <td>3774</td>\n",
       "      <td>4331</td>\n",
       "      <td>69439</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>American Samoa</th>\n",
       "      <td>Oceania</td>\n",
       "      <td>Polynesia</td>\n",
       "      <td>Developing regions</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Andorra</th>\n",
       "      <td>Europe</td>\n",
       "      <td>Southern Europe</td>\n",
       "      <td>Developed regions</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>15</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 38 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "               Continent           Region             DevName  1980  1981  \\\n",
       "Afghanistan         Asia    Southern Asia  Developing regions    16    39   \n",
       "Albania           Europe  Southern Europe   Developed regions     1     0   \n",
       "Algeria           Africa  Northern Africa  Developing regions    80    67   \n",
       "American Samoa   Oceania        Polynesia  Developing regions     0     1   \n",
       "Andorra           Europe  Southern Europe   Developed regions     0     0   \n",
       "\n",
       "                1982  1983  1984  1985  1986  ...  2005  2006  2007  2008  \\\n",
       "Afghanistan       39    47    71   340   496  ...  3436  3009  2652  2111   \n",
       "Albania            0     0     0     0     1  ...  1223   856   702   560   \n",
       "Algeria           71    69    63    44    69  ...  3626  4807  3623  4005   \n",
       "American Samoa     0     0     0     0     0  ...     0     1     0     0   \n",
       "Andorra            0     0     0     0     2  ...     0     1     1     0   \n",
       "\n",
       "                2009  2010  2011  2012  2013  Total  \n",
       "Afghanistan     1746  1758  2203  2635  2004  58639  \n",
       "Albania          716   561   539   620   603  15699  \n",
       "Algeria         5393  4752  4325  3774  4331  69439  \n",
       "American Samoa     0     0     0     0     0      6  \n",
       "Andorra            0     0     0     1     1     15  \n",
       "\n",
       "[5 rows x 38 columns]"
      ]
     },
     "execution_count": 235,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_can.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 236,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['Afghanistan', 'Albania', 'Algeria', 'American Samoa', 'Andorra',\n",
       "       'Angola', 'Antigua and Barbuda', 'Argentina', 'Armenia', 'Australia',\n",
       "       ...\n",
       "       'United States of America', 'Uruguay', 'Uzbekistan', 'Vanuatu',\n",
       "       'Venezuela (Bolivarian Republic of)', 'Viet Nam', 'Western Sahara',\n",
       "       'Yemen', 'Zambia', 'Zimbabwe'],\n",
       "      dtype='object', length=195)"
      ]
     },
     "execution_count": 236,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_can.index"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## For consistency, ensure that all column labels of type string."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 237,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "False"
      ]
     },
     "execution_count": 237,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "all(isinstance(column, str) for column in df_can.columns)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Converting Integer Column names into Strings"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 238,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_can.columns= list(map(str, df_can.columns))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 239,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['Continent', 'Region', 'DevName', '1980', '1981', '1982', '1983',\n",
       "       '1984', '1985', '1986', '1987', '1988', '1989', '1990', '1991', '1992',\n",
       "       '1993', '1994', '1995', '1996', '1997', '1998', '1999', '2000', '2001',\n",
       "       '2002', '2003', '2004', '2005', '2006', '2007', '2008', '2009', '2010',\n",
       "       '2011', '2012', '2013', 'Total'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 239,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_can.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 240,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['1980', '1981', '1982', '1983', '1984', '1985', '1986', '1987', '1988', '1989', '1990', '1991', '1992', '1993', '1994', '1995', '1996', '1997', '1998', '1999', '2000', '2001', '2002', '2003', '2004', '2005', '2006', '2007', '2008', '2009', '2010', '2011', '2012', '2013']\n"
     ]
    }
   ],
   "source": [
    "years= list(map(str, range(1980,2014)))\n",
    "print(years)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 241,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "True"
      ]
     },
     "execution_count": 241,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# let's check the column labels types now\n",
    "all(isinstance(column, str) for column in df_can.columns)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Visualization using `seaborn` library `regplot()` function"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 242,
   "metadata": {},
   "outputs": [],
   "source": [
    "import seaborn as sns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 243,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Continent</th>\n",
       "      <th>Region</th>\n",
       "      <th>DevName</th>\n",
       "      <th>1980</th>\n",
       "      <th>1981</th>\n",
       "      <th>1982</th>\n",
       "      <th>1983</th>\n",
       "      <th>1984</th>\n",
       "      <th>1985</th>\n",
       "      <th>1986</th>\n",
       "      <th>...</th>\n",
       "      <th>2005</th>\n",
       "      <th>2006</th>\n",
       "      <th>2007</th>\n",
       "      <th>2008</th>\n",
       "      <th>2009</th>\n",
       "      <th>2010</th>\n",
       "      <th>2011</th>\n",
       "      <th>2012</th>\n",
       "      <th>2013</th>\n",
       "      <th>Total</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Afghanistan</th>\n",
       "      <td>Asia</td>\n",
       "      <td>Southern Asia</td>\n",
       "      <td>Developing regions</td>\n",
       "      <td>16</td>\n",
       "      <td>39</td>\n",
       "      <td>39</td>\n",
       "      <td>47</td>\n",
       "      <td>71</td>\n",
       "      <td>340</td>\n",
       "      <td>496</td>\n",
       "      <td>...</td>\n",
       "      <td>3436</td>\n",
       "      <td>3009</td>\n",
       "      <td>2652</td>\n",
       "      <td>2111</td>\n",
       "      <td>1746</td>\n",
       "      <td>1758</td>\n",
       "      <td>2203</td>\n",
       "      <td>2635</td>\n",
       "      <td>2004</td>\n",
       "      <td>58639</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Albania</th>\n",
       "      <td>Europe</td>\n",
       "      <td>Southern Europe</td>\n",
       "      <td>Developed regions</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>1223</td>\n",
       "      <td>856</td>\n",
       "      <td>702</td>\n",
       "      <td>560</td>\n",
       "      <td>716</td>\n",
       "      <td>561</td>\n",
       "      <td>539</td>\n",
       "      <td>620</td>\n",
       "      <td>603</td>\n",
       "      <td>15699</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Algeria</th>\n",
       "      <td>Africa</td>\n",
       "      <td>Northern Africa</td>\n",
       "      <td>Developing regions</td>\n",
       "      <td>80</td>\n",
       "      <td>67</td>\n",
       "      <td>71</td>\n",
       "      <td>69</td>\n",
       "      <td>63</td>\n",
       "      <td>44</td>\n",
       "      <td>69</td>\n",
       "      <td>...</td>\n",
       "      <td>3626</td>\n",
       "      <td>4807</td>\n",
       "      <td>3623</td>\n",
       "      <td>4005</td>\n",
       "      <td>5393</td>\n",
       "      <td>4752</td>\n",
       "      <td>4325</td>\n",
       "      <td>3774</td>\n",
       "      <td>4331</td>\n",
       "      <td>69439</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>American Samoa</th>\n",
       "      <td>Oceania</td>\n",
       "      <td>Polynesia</td>\n",
       "      <td>Developing regions</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Andorra</th>\n",
       "      <td>Europe</td>\n",
       "      <td>Southern Europe</td>\n",
       "      <td>Developed regions</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>15</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 38 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "               Continent           Region             DevName  1980  1981  \\\n",
       "Afghanistan         Asia    Southern Asia  Developing regions    16    39   \n",
       "Albania           Europe  Southern Europe   Developed regions     1     0   \n",
       "Algeria           Africa  Northern Africa  Developing regions    80    67   \n",
       "American Samoa   Oceania        Polynesia  Developing regions     0     1   \n",
       "Andorra           Europe  Southern Europe   Developed regions     0     0   \n",
       "\n",
       "                1982  1983  1984  1985  1986  ...  2005  2006  2007  2008  \\\n",
       "Afghanistan       39    47    71   340   496  ...  3436  3009  2652  2111   \n",
       "Albania            0     0     0     0     1  ...  1223   856   702   560   \n",
       "Algeria           71    69    63    44    69  ...  3626  4807  3623  4005   \n",
       "American Samoa     0     0     0     0     0  ...     0     1     0     0   \n",
       "Andorra            0     0     0     0     2  ...     0     1     1     0   \n",
       "\n",
       "                2009  2010  2011  2012  2013  Total  \n",
       "Afghanistan     1746  1758  2203  2635  2004  58639  \n",
       "Albania          716   561   539   620   603  15699  \n",
       "Algeria         5393  4752  4325  3774  4331  69439  \n",
       "American Samoa     0     0     0     0     0      6  \n",
       "Andorra            0     0     0     1     1     15  \n",
       "\n",
       "[5 rows x 38 columns]"
      ]
     },
     "execution_count": 243,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_can.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 244,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>0</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1980</th>\n",
       "      <td>99137</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1981</th>\n",
       "      <td>110563</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1982</th>\n",
       "      <td>104271</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1983</th>\n",
       "      <td>75550</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1984</th>\n",
       "      <td>73417</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "           0\n",
       "1980   99137\n",
       "1981  110563\n",
       "1982  104271\n",
       "1983   75550\n",
       "1984   73417"
      ]
     },
     "execution_count": 244,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_tot= pd.DataFrame(df_can[years].sum())\n",
    "df_tot.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 245,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_tot.reset_index(inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 246,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Year</th>\n",
       "      <th>Total</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1980</td>\n",
       "      <td>99137</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1981</td>\n",
       "      <td>110563</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1982</td>\n",
       "      <td>104271</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1983</td>\n",
       "      <td>75550</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1984</td>\n",
       "      <td>73417</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Year   Total\n",
       "0  1980   99137\n",
       "1  1981  110563\n",
       "2  1982  104271\n",
       "3  1983   75550\n",
       "4  1984   73417"
      ]
     },
     "execution_count": 246,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_tot.columns=['Year','Total']\n",
    "df_tot.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 247,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_tot['Year']=df_tot['Year'].map(int)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 248,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ax= sns.regplot(x='Year', y='Total', data=df_tot)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 249,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ax= sns.regplot(x='Year', y='Total', data=df_tot, color='green')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 250,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ax= sns.regplot(x='Year', y='Total', data=df_tot, color='green', marker='+')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 251,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x576 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(12,8))\n",
    "ax= sns.regplot(x='Year', y='Total', data=df_tot, color='green', marker='+')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 252,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x576 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(12,8))\n",
    "ax= sns.regplot(x='Year', y='Total', data=df_tot, color='green', marker='+', scatter_kws={'s':100}) #set size of markers\n",
    "\n",
    "ax.set(xlabel=\"Year\", ylabel=\"Total Immigration\", title=\"Total Immigration to Canada from 1980-2013\")\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 253,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x576 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(12,8))\n",
    "\n",
    "sns.set(font_scale=1.25)        #set font size of the labels of ticks\n",
    "\n",
    "ax= sns.regplot(x='Year', y='Total', data=df_tot, color='green', marker='+', scatter_kws={'s':100})\n",
    "\n",
    "ax.set(xlabel=\"Year\", ylabel=\"Total Immigration\")\n",
    "ax.set_title(\"Total Immigration to Canada from 1980-2013\")\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 254,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x576 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(12,8))\n",
    "\n",
    "sns.set(font_scale=1.25)        #set font size of the labels of ticks\n",
    "\n",
    "sns.set_style(\"white\")          #set the background to white\n",
    "\n",
    "ax= sns.regplot(x='Year', y='Total', data=df_tot, color='green', marker='+', scatter_kws={'s':100})\n",
    "\n",
    "ax.set(xlabel=\"Year\", ylabel=\"Total Immigration\")\n",
    "ax.set_title(\"Total Immigration to Canada from 1980-2013\")\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 255,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x576 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(12,8))\n",
    "\n",
    "sns.set(font_scale=1.25)        #set font size of the labels of ticks\n",
    "\n",
    "sns.set_style(\"whitegrid\")      #a white background with grid\n",
    "\n",
    "ax= sns.regplot(x='Year', y='Total', data=df_tot, color='green', marker='+', scatter_kws={'s':100})\n",
    "\n",
    "ax.set(xlabel=\"Year\", ylabel=\"Total Immigration\")\n",
    "ax.set_title(\"Total Immigration to Canada from 1980-2013\")\n",
    "\n",
    "plt.show()"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.7"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}