ML_Experiment4_J024_Pranav_Kotak.ipynb

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  "metadata": {
    "colab": {
      "name": "ML_Experiment4_J024_Pranav_Kotak.ipynb",
      "provenance": [],
      "collapsed_sections": [],
      "authorship_tag": "ABX9TyNdBAE2X4ttNASLo6qjbhI4",
      "include_colab_link": true
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    }
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/pranavkotak8/ML/blob/master/ML_Experiment4_J024_Pranav_Kotak.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "FejsqgGcmHCb",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 35
        },
        "outputId": "3e9c87a7-11e2-4563-d4d3-1eab47b58d56"
      },
      "source": [
        "# useful for many scientific computing in Python\n",
        "import numpy as np \n",
        "import pandas as pd \n",
        " \n",
        "df_can = pd.read_excel('https://s3-api.us-geo.objectstorage.softlayer.net/cf-courses-data/CognitiveClass/DV0101EN/labs/Data_Files/Canada.xlsx',\n",
        " sheet_name='Canada by Citizenship',\n",
        " skiprows=range(20),\n",
        " skipfooter=2\n",
        " )\n",
        " \n",
        "print('Data downloaded and read into a dataframe!')"
      ],
      "execution_count": 1,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Data downloaded and read into a dataframe!\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "B4JohrznycCR",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 298
        },
        "outputId": "dcdd39b3-651f-41ed-bdbc-e078191b1e07"
      },
      "source": [
        "# dataset has immigration from each country to canada from 1980-2013\n",
        "df_can.head()"
      ],
      "execution_count": 2,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
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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>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>1981</th>\n",
              "      <th>1982</th>\n",
              "      <th>1983</th>\n",
              "      <th>1984</th>\n",
              "      <th>1985</th>\n",
              "      <th>1986</th>\n",
              "      <th>1987</th>\n",
              "      <th>1988</th>\n",
              "      <th>1989</th>\n",
              "      <th>1990</th>\n",
              "      <th>1991</th>\n",
              "      <th>1992</th>\n",
              "      <th>1993</th>\n",
              "      <th>1994</th>\n",
              "      <th>1995</th>\n",
              "      <th>1996</th>\n",
              "      <th>1997</th>\n",
              "      <th>1998</th>\n",
              "      <th>1999</th>\n",
              "      <th>2000</th>\n",
              "      <th>2001</th>\n",
              "      <th>2002</th>\n",
              "      <th>2003</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>39</td>\n",
              "      <td>39</td>\n",
              "      <td>47</td>\n",
              "      <td>71</td>\n",
              "      <td>340</td>\n",
              "      <td>496</td>\n",
              "      <td>741</td>\n",
              "      <td>828</td>\n",
              "      <td>1076</td>\n",
              "      <td>1028</td>\n",
              "      <td>1378</td>\n",
              "      <td>1170</td>\n",
              "      <td>713</td>\n",
              "      <td>858</td>\n",
              "      <td>1537</td>\n",
              "      <td>2212</td>\n",
              "      <td>2555</td>\n",
              "      <td>1999</td>\n",
              "      <td>2395</td>\n",
              "      <td>3326</td>\n",
              "      <td>4067</td>\n",
              "      <td>3697</td>\n",
              "      <td>3479</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>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
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              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>3</td>\n",
              "      <td>3</td>\n",
              "      <td>21</td>\n",
              "      <td>56</td>\n",
              "      <td>96</td>\n",
              "      <td>71</td>\n",
              "      <td>63</td>\n",
              "      <td>113</td>\n",
              "      <td>307</td>\n",
              "      <td>574</td>\n",
              "      <td>1264</td>\n",
              "      <td>1816</td>\n",
              "      <td>1602</td>\n",
              "      <td>1021</td>\n",
              "      <td>853</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>67</td>\n",
              "      <td>71</td>\n",
              "      <td>69</td>\n",
              "      <td>63</td>\n",
              "      <td>44</td>\n",
              "      <td>69</td>\n",
              "      <td>132</td>\n",
              "      <td>242</td>\n",
              "      <td>434</td>\n",
              "      <td>491</td>\n",
              "      <td>872</td>\n",
              "      <td>795</td>\n",
              "      <td>717</td>\n",
              "      <td>595</td>\n",
              "      <td>1106</td>\n",
              "      <td>2054</td>\n",
              "      <td>1842</td>\n",
              "      <td>2292</td>\n",
              "      <td>2389</td>\n",
              "      <td>2867</td>\n",
              "      <td>3418</td>\n",
              "      <td>3406</td>\n",
              "      <td>3072</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>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>0</td>\n",
              "      <td>1</td>\n",
              "      <td>2</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>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>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>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>2</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>3</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>2</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>2</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",
              "</div>"
            ],
            "text/plain": [
              "         Type    Coverage          OdName  AREA  ...  2010  2011  2012  2013\n",
              "0  Immigrants  Foreigners     Afghanistan   935  ...  1758  2203  2635  2004\n",
              "1  Immigrants  Foreigners         Albania   908  ...   561   539   620   603\n",
              "2  Immigrants  Foreigners         Algeria   903  ...  4752  4325  3774  4331\n",
              "3  Immigrants  Foreigners  American Samoa   909  ...     0     0     0     0\n",
              "4  Immigrants  Foreigners         Andorra   908  ...     0     0     1     1\n",
              "\n",
              "[5 rows x 43 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 2
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "4NwdcbuXycF1",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 35
        },
        "outputId": "be9e97fa-ffbb-4f8b-b27e-60f2261096da"
      },
      "source": [
        "#dimensions of the dataset \n",
        "df_can.shape"
      ],
      "execution_count": 3,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(195, 43)"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 3
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Xh1EsQS_ycID",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "# Dropping the columns not needed, resetting the index and renaming the columns\n",
        "df_can.drop(columns={'AREA','REG','Coverage','Type'},axis='columns',inplace=True)\n",
        "df_can.rename(columns={'OdName':'Country','AreaName':'Continent','RegName':'Continent-region','DevName':'Development-status'},inplace=True)\n",
        "df_can.set_index('Country',inplace=True)\n",
        "df_can['Total_count']=df_can.sum(axis='columns')\n",
        "years=range(1980,2014)"
      ],
      "execution_count": 4,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "CXKSbevA5Dea",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 35
        },
        "outputId": "e857b06b-59ad-469b-cb6b-18a2aa30c128"
      },
      "source": [
        "df_can.columns.dtype"
      ],
      "execution_count": 5,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "dtype('O')"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 5
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "47C6OsA_ycKW",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "# Importing the Libraries needed for Visualization\n",
        "import matplotlib.pyplot as plt\n",
        "import matplotlib as mpl"
      ],
      "execution_count": 6,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "BOiiwdnf5bGP",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "# Performing groupby - continents\n",
        "df_continents=df_can.groupby('Continent',axis='index').sum()"
      ],
      "execution_count": 7,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "DlerOoJbycMR",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 575
        },
        "outputId": "37bcb89a-2414-42d9-9999-614090df961b"
      },
      "source": [
        "#create pie charts\n",
        "#baseline pie chart\n",
        "df_continents['Total_count'].plot(kind='pie',figsize=(10,10))\n",
        "plt.show()"
      ],
      "execution_count": 8,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 720x720 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "R5x3zb-36X1G",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 591
        },
        "outputId": "9e310dfc-4c75-4e7e-aad4-166634fa1af1"
      },
      "source": [
        "df_continents['Total_count'].plot(kind='pie',figsize=(10,10),startangle=90,autopct='%1.1f%%',shadow=True)\n",
        "\n",
        "plt.title('Immigration from 1980-2013 by continents')\n",
        "plt.axis('equal') #looks like a circle\n",
        "plt.show()"
      ],
      "execution_count": 9,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 720x720 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "JkHEjkpMycOJ",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        ""
      ],
      "execution_count": 9,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab_type": "code",
        "id": "GCyt4WDa7Enh",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 591
        },
        "outputId": "456f6b41-6763-485f-83d2-eaa7c2dfe2b1"
      },
      "source": [
        "explodelist=[0,0.2,0,0,0,0.1]   # This is for having a part of pie chart detached from the circle\n",
        "df_continents['Total_count'].plot(kind='pie',\n",
        "                                  figsize=(10,10),\n",
        "                                  startangle=270,\n",
        "                                  autopct='%1.1f%%',\n",
        "                                  shadow=True,\n",
        "                                  labels=None,\n",
        "                                  explode=explodelist)\n",
        "plt.title('Immigration from 1980-2013 by continents')\n",
        "plt.axis('equal') #looks like a circle\n",
        "plt.legend(labels=df_continents.index,loc='upper left')\n",
        "plt.show()"
      ],
      "execution_count": 12,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 720x720 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "prKImpDP8iwy",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "#plot pie chart of dev status\n",
        "df_devstatus=df_can.groupby('Development-status',axis='index').sum()"
      ],
      "execution_count": 13,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "3eaqqcs39EBs",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 591
        },
        "outputId": "5a143361-d265-4621-c871-4a44d9608899"
      },
      "source": [
        "colorlist=['gold','lightgreen']\n",
        "explodelist=[0,0.1]\n",
        "df_devstatus['Total_count'].plot(kind='pie',\n",
        "                                  figsize=(10,10),\n",
        "                                  startangle=90,\n",
        "                                  autopct='%1.1f%%',\n",
        "                                  shadow=True,\n",
        "                                  labels=None,\n",
        "                                  colors=colorlist,\n",
        "                                  explode=explodelist)\n",
        "\n",
        "plt.title('Immigration from 1980-2013 by developing status')\n",
        "plt.axis('equal') #looks like a circle\n",
        "plt.legend(labels=df_continents.index,loc='upper left')\n",
        "plt.show()"
      ],
      "execution_count": 14,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 720x720 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "WeWVXHYI9EEE",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "##1. By Continent-region------pie chart \n",
        "##use colorlist explode pct figsize title add axes add legend remove labels and use shadows"
      ],
      "execution_count": 15,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "UdYqGAFo9EHd",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "df_continentregion=df_can.groupby('Continent-region',axis='index').sum()"
      ],
      "execution_count": 16,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ho68yziW9EKZ",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 592
        },
        "outputId": "8a3161c8-6ee3-491f-b6a3-00e56f107c38"
      },
      "source": [
        "colorlist=['blue','yellow','green','red','black','orange']\n",
        "df_continentregion['Total_count'].plot(kind='pie',\n",
        "                                  figsize=(10,10),\n",
        "                                  startangle=90,\n",
        "                                  autopct='%1.1f%%',\n",
        "                                  shadow=True,\n",
        "                                  labels=None,\n",
        "                                  colors=colorlist\n",
        "                                  )\n",
        "\n",
        "plt.title('Immigration from 1980-2013 by continent region')\n",
        "plt.axis('equal') #looks like a circle\n",
        "plt.legend(labels=df_continents.index,loc='upper right')\n",
        "plt.show()"
      ],
      "execution_count": 54,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 720x720 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "KR8poi5c6Kg9",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "dfIndia=df_can.loc['India',years]"
      ],
      "execution_count": 19,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "IrKojMt16UeS",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "outputId": "a37caae3-924c-4702-f41e-51d9bedbf402"
      },
      "source": [
        "dfIndiapak"
      ],
      "execution_count": 74,
      "outputs": [
        {
          "output_type": "execute_result",
          "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>Country</th>\n",
              "      <th>India</th>\n",
              "      <th>Pakistan</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>1980</th>\n",
              "      <td>8880</td>\n",
              "      <td>978</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1981</th>\n",
              "      <td>8670</td>\n",
              "      <td>972</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1982</th>\n",
              "      <td>8147</td>\n",
              "      <td>1201</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1983</th>\n",
              "      <td>7338</td>\n",
              "      <td>900</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1984</th>\n",
              "      <td>5704</td>\n",
              "      <td>668</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1985</th>\n",
              "      <td>4211</td>\n",
              "      <td>514</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1986</th>\n",
              "      <td>7150</td>\n",
              "      <td>691</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1987</th>\n",
              "      <td>10189</td>\n",
              "      <td>1072</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1988</th>\n",
              "      <td>11522</td>\n",
              "      <td>1334</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1989</th>\n",
              "      <td>10343</td>\n",
              "      <td>2261</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1990</th>\n",
              "      <td>12041</td>\n",
              "      <td>2470</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1991</th>\n",
              "      <td>13734</td>\n",
              "      <td>3079</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1992</th>\n",
              "      <td>13673</td>\n",
              "      <td>4071</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1993</th>\n",
              "      <td>21496</td>\n",
              "      <td>4777</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1994</th>\n",
              "      <td>18620</td>\n",
              "      <td>4666</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1995</th>\n",
              "      <td>18489</td>\n",
              "      <td>4994</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1996</th>\n",
              "      <td>23859</td>\n",
              "      <td>9125</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1997</th>\n",
              "      <td>22268</td>\n",
              "      <td>13073</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1998</th>\n",
              "      <td>17241</td>\n",
              "      <td>9068</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1999</th>\n",
              "      <td>18974</td>\n",
              "      <td>9979</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2000</th>\n",
              "      <td>28572</td>\n",
              "      <td>15400</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2001</th>\n",
              "      <td>31223</td>\n",
              "      <td>16708</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2002</th>\n",
              "      <td>31889</td>\n",
              "      <td>15110</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2003</th>\n",
              "      <td>27155</td>\n",
              "      <td>13205</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2004</th>\n",
              "      <td>28235</td>\n",
              "      <td>13399</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2005</th>\n",
              "      <td>36210</td>\n",
              "      <td>14314</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2006</th>\n",
              "      <td>33848</td>\n",
              "      <td>13127</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2007</th>\n",
              "      <td>28742</td>\n",
              "      <td>10124</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2008</th>\n",
              "      <td>28261</td>\n",
              "      <td>8994</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2009</th>\n",
              "      <td>29456</td>\n",
              "      <td>7217</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2010</th>\n",
              "      <td>34235</td>\n",
              "      <td>6811</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2011</th>\n",
              "      <td>27509</td>\n",
              "      <td>7468</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2012</th>\n",
              "      <td>30933</td>\n",
              "      <td>11227</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2013</th>\n",
              "      <td>33087</td>\n",
              "      <td>12603</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "Country  India  Pakistan\n",
              "1980      8880       978\n",
              "1981      8670       972\n",
              "1982      8147      1201\n",
              "1983      7338       900\n",
              "1984      5704       668\n",
              "1985      4211       514\n",
              "1986      7150       691\n",
              "1987     10189      1072\n",
              "1988     11522      1334\n",
              "1989     10343      2261\n",
              "1990     12041      2470\n",
              "1991     13734      3079\n",
              "1992     13673      4071\n",
              "1993     21496      4777\n",
              "1994     18620      4666\n",
              "1995     18489      4994\n",
              "1996     23859      9125\n",
              "1997     22268     13073\n",
              "1998     17241      9068\n",
              "1999     18974      9979\n",
              "2000     28572     15400\n",
              "2001     31223     16708\n",
              "2002     31889     15110\n",
              "2003     27155     13205\n",
              "2004     28235     13399\n",
              "2005     36210     14314\n",
              "2006     33848     13127\n",
              "2007     28742     10124\n",
              "2008     28261      8994\n",
              "2009     29456      7217\n",
              "2010     34235      6811\n",
              "2011     27509      7468\n",
              "2012     30933     11227\n",
              "2013     33087     12603"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 74
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "TKPDIC5B6Vhv",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 390
        },
        "outputId": "824779e7-09eb-4fc9-cb9c-544e5c89677c"
      },
      "source": [
        "dfIndia.plot(\n",
        "    kind='box',\n",
        "    figsize=(10,6)\n",
        ")\n",
        "plt.title('Box plot of india from 1980-2013')\n",
        "plt.ylabel('Number of Immigrants')\n",
        "plt.show()"
      ],
      "execution_count": 21,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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V7YEdgYuAi4Ed26zW9ekmOiwe1/lIkiQ9Uqw7fZc1thVwcpst+hjgtKo6M8nVwKlJ3gtcCpzY+p8IfCLJUmAFXSCjqq5KchpwNXA/cERVPQCQ5PXA2cA6wElVddUYz0eSJOkRYWwBrqouB3abpP16uvvhVm3/CfDSIfs6Fjh2kvazgLMedrGSJEk94psYJEmSesYAJ0mS1DMGOEmSpJ4xwEmSJPWMAU6SJKlnDHCSJEk9M87nwEnSw7bLu7/CnT/+2WyXMZIFR31xtkuY1qYbrse3j95ntsuQ9DAZ4CQ9ot35459xw3EHzHYZc0YfQqak6XkJVZIkqWcMcJIkST1jgJMkSeoZA5wkSVLPGOAkSZJ6xgAnSZLUMwY4SZKknjHASZIk9YwBTpIkqWcMcJIkST1jgJMkSeoZA5wkSVLPGOAkSZJ6xgAnSZLUMwY4SZKknjHASZIk9YwBTpIkqWcMcJIkST1jgJMkSeoZA5wkSVLPGOAkSZJ6xgAnSZLUM9MGuCQ7JHlsW94ryRuTzBt/aZIkSZrMKCNw/w48kOQpwAnAtsCnxlqVJEmShholwP28qu4H/gD4cFX9BbDVeMuSJEnSMKMEuJ8lORhYBJzZ2tYbX0mSJEmayigB7lDgWcCxVfW9JNsDnxhvWZIkSRpm3RH6PK+q3jjxpYW4n4yxJkmSJE1hlBG4RZO0vWot1yFJkqQRDQ1wSQ5O8gVg+ySLBz7nAium23GSbZOcm+TqJFcleVNrf1eSm5Nc1j77D2zz1iRLk3wnyb4D7fu1tqVJjhpo3z7Jha39M0nWX9NfhCRJUl9MdQn1v4BbgC2ADw603wVcPsK+7wfeUlXfSrIxcEmSc9q6D1XV3w52TrIT8HLgacATga8m+bW2+p+A5wHLgIuTLK6qq4H3t32dmuSfgcOAj45QmyRJUm8NDXBVdSNwI90EhtVWVbfQBUCq6q4k1wBbT7HJQcCpVXUf8L0kS4Hd27qlVXU9QJJTgYPa/vYGXtH6nAy8CwOcJEma40Z5E8OLklyX5M4kK5PclWTl6hwkyQJgN+DC1vT6JJcnOSnJZq1ta+Cmgc2WtbZh7Y8D7mjPqBtsn+z4hydZkmTJ8uXLV6d0SZKkR5xRJjH8DXBgVW1aVZtU1cZVtcmoB0iyEd3bHP60qlbSjZDtAOxKN0L3wSk2Xyuq6oSqWlhVC+fPnz/uw0mSJI3VKI8RubWqrlmTnSdZjy68fbKqPgdQVbcOrP8YDz4c+Ga613RN2Ka1MaT9R8C8JOu2UbjB/pIkSXPWKCNwS9oMz4Pb5dQXJXnRdBslCXAicE1V/d1A++BruP4AuLItLwZenuSx7WHBOwIXARcDO7YZp+vTTXRYXFUFnAu8pG2/CDhjhPORJEnqtVFG4DYB7gX2GWgr4HPTbPds4JXAFUkua21vAw5Osmvbxw3AawGq6qokpwFX081gPaKqHgBI8nrgbGAd4KSquqrt70jg1CTvBS6lC4ySJElz2rQBrqoOXZMdV9X5QCZZddYU2xwLHDtJ+1mTbddmpu6+arskSdJcNm2AS7IB3fPVngZsMNFeVa8eY12SJEkaYpR74D4BPAHYF/g63WSBu8ZZlCRJkoYbJcA9pareAdxTVScDBwB7jLcsSZIkDTNKgPtZ+3lHkp2BTYHHj68kSZIkTWWUWagntLclvJ3uUR8bAe8Ya1WSJEkaasoAl+QxwMqquh34BvDkGalKkiRJQ015CbWqfg785QzVIkmSpBGMcg/cV5P8eZJtk2w+8Rl7ZZIkSZrUKPfA/WH7ecRAW+HlVEmSpFkxypsYtp+JQiRJkjSaUd7EMNmL6+8Erqiq29Z+SZIkSZrKKJdQDwOeBZzbvu8FXAJsn+Q9VfWJMdUmSZKkSYwS4NYFnlpVtwIk2RI4he5tDN+ge9WWJEmSZsgos1C3nQhvzW2tbQUPvqVBkiRJM2SUEbjzkpwJfLZ9f3Fr+1XgjrFVJkmSpEmNEuCOoAttz27fTwH+vaoK+L1xFSZJkqTJjfIYkQJObx9JkiTNsqEBLsn5VfWcJHfRPbj3F6voct0mY69OkiRJv2RogKuq57SfG89cOZIkSZrOKPfAkWQzYNvB/lX1rXEVJUmSpOFGeRPDMcCrgOuBn7fmAvYeX1mSJEkaZpQRuJcBO1TVT8ddjCRJkqY3yoN8rwTmjbsQSZIkjWaUEbj3AZcmuRK4b6Kxqg4cW1WSJEkaapQAdzLwfuAKHrwHTpIkSbNklAB3b1UdP/ZKJEmSNJJRAtw3k7wPWMxDL6H6GBFJkqRZMEqA26393HOgzceISJIkzZJR3oXqC+slSZIeQUZ5kO884BBgAQ99E8Mbx1eWJEmShhnlEupZwAU4C1WSJOkRYZQAt0FVvXnslUiSJGkko7yJ4RNJXpNkqySbT3zGXpkkSZImNcoI3E+BDwB/RTf7lPbzyeMqSpIkScONEuDeAjylqn447mIkSZI0vVEuoS4F7h13IZIkSRrNKCNw9wCXJTmXh76JwceISJIkzYJRRuA+DxwL/BdwycBnSkm2TXJukquTXJXkTa198yTnJLmu/dystSfJ8UmWJrk8yTMG9rWo9b8uyaKB9mcmuaJtc3ySrN7pS5Ik9U+qavpea7LjZCtgq6r6VpKN6ULfC4FXASuq6rgkRwGbVdWRSfYH3gDsD+wB/ENV7dFmvC4BFtJNnrgEeGZV3Z7kIuCNwIV0z6s7vqq+NFVdCxcurCVLlozjlCWNwdNPfvpslzDnXLHoitkuQdKIklxSVQtXbR96CTXJFTw46/SXVNVvTnXAqroFuKUt35XkGmBr4CBgr9btZOA84MjWfkp1ifKCJPNaCNwLOKeqVrS6zgH2S3IesElVXdDaT6ELiFMGOEn9ctc1x3HDcQfMdhlzxoKjvjjbJUhaC6a6B+5/rq2DJFkA7EY3UrZlC3cAPwC2bMtbAzcNbLastU3VvmySdkmSpDltaICrqhvXxgGSbAT8O/CnVbVy8Da1qqok47mG+9AaDgcOB9huu+3GfThJkqSxGmUSwxpLsh5dePtkVX2uNd/aLo1O3Cd3W2u/Gdh2YPNtWttU7dtM0v5LquqEqlpYVQvnz5//8E5KkiRplo0twLUZoScC11TV3w2sWgxMzCRdBJwx0H5Im426J3Bnu9R6NrBPks3ajNV9gLPbupVJ9mzHOmRgX5IkSXPW0ACX5Gvt5/vXcN/PBl4J7J3ksvbZHzgOeF6S64Dfb9+hm0V6Pd2Dgz8GvA6gTV44Bri4fd4zMaGh9fnXts13cQKDJEl6FJhqEsNWSX4bODDJqcBDnrFWVd+aasdVdf6q2wx47iT9CzhiyL5OAk6apH0JsPNUdUiSJM01UwW4dwLvoLu37O9WWVfA3uMqSpIkScNNNQv1dOD0JO+oqmNmsCZJkiRNYdp3oVbVMUkOBH6nNZ1XVWeOtyxJkiQNM+0s1CTvA94EXN0+b0ry1+MuTJIkSZObdgQOOADYtap+DpDkZOBS4G3jLEySJEmTG/U5cPMGljcdRyGSJEkazSgjcO8DLk1yLt1jQX4HOGqsVUmSJGmoUSYxfDrJecBvtaYjq+oHY61KkiRJQ40yAkd7bdXiMdciSZKkEYz1ZfaSJEla+wxwkiRJPTNlgEuyTpJrZ6oYSZIkTW/KAFdVDwDfSbLdDNUjSZKkaYwyiWEz4KokFwH3TDRW1YFjq0qSJElDjRLg3jH2KiRJkjSyUZ4D9/UkTwJ2rKqvJvkVYJ3xlyZJkqTJjPIy+9cApwP/0pq2Bj4/zqIkSZI03CiPETkCeDawEqCqrgMeP86iJEmSNNwoAe6+qvrpxJck6wI1vpIkSZI0lVEC3NeTvA3YMMnzgM8CXxhvWZIkSRpmlAB3FLAcuAJ4LXAW8PZxFiVJkqThRpmF+vMkJwMX0l06/U5VeQlVkiRplkwb4JIcAPwz8F0gwPZJXltVXxp3cZIkSfplozzI94PA71XVUoAkOwBfBAxwkiRJs2CUe+DumghvzfXAXWOqR5IkSdMYOgKX5EVtcUmSs4DT6O6Beylw8QzUJkmSpElMdQn1BQPLtwK/25aXAxuOrSJJkiRNaWiAq6pDZ7IQSZIkjWaUWajbA28AFgz2r6oDx1eWJEmShhllFurngRPp3r7w8/GWI0mSpOmMEuB+UlXHj70SSZIkjWSUAPcPSY4GvgLcN9FYVd8aW1WSJEkaapQA93TglcDePHgJtdp3SZIkzbBRAtxLgSdX1U/HXYwkSZKmN8qbGK4E5o27EEmSJI1mlBG4ecC1SS7moffA+RgRSZKkWTBKgDt67FVIkiRpZNMGuKr6+kwUIkmSpNFMew9ckruSrGyfnyR5IMnKEbY7KcltSa4caHtXkpuTXNY++w+se2uSpUm+k2Tfgfb9WtvSJEcNtG+f5MLW/pkk66/eqUuSJPXTtAGuqjauqk2qahO6l9i/GPjICPv+OLDfJO0fqqpd2+csgCQ7AS8Hnta2+UiSdZKsA/wT8HxgJ+Dg1hfg/W1fTwFuBw4boSZJkqTeG2UW6i9U5/PAviP0/QawYsRdHwScWlX3VdX3gKXA7u2ztKqub48xORU4KEnonkN3etv+ZOCFq3MukiRJfTXKy+xfNPD1McBC4CcP45ivT3IIsAR4S1XdDmwNXDDQZ1lrA7hplfY9gMcBd1TV/ZP0n+wcDgcOB9huu+0eRumSJEmzb5QRuBcMfPYF7qIbMVsTHwV2AHYFbgE+uIb7WS1VdUJVLayqhfPnz5+JQ0qSJI3NKLNQD11bB6uqWyeWk3wMOLN9vRnYdqDrNq2NIe0/AuYlWbeNwg32lyRJmtOGBrgk75xiu6qqY1b3YEm2qqpb2tc/oHvLA8Bi4FNJ/g54IrAjcBEQYMck29MFtJcDr6iqSnIu8BK6++IWAWesbj2SJEl9NNUI3D2TtP0q3WzPxwFTBrgknwb2ArZIsozugcB7JdkVKOAG4LUAVXVVktOAq4H7gSOq6oG2n9cDZwPrACdV1VXtEEcCpyZ5L3ApcOJ0JytJkjQXDA1wVfWL+9OSbAy8CTiUbsRr2nvXqurgSZqHhqyqOhY4dpL2s4CzJmm/nm6WqiRJ0qPKlPfAJdkceDPwR3SP6nhGmzUqSZKkWTLVPXAfAF4EnAA8varunrGqJEmSNNRUjxF5C92EgrcD3x94ndZdo7xKS5IkSeMx1T1wq/WWBkmSJM0MQ5okSVLPGOAkSZJ6xgAnSZLUMwY4SZKknjHASZIk9YwBTpIkqWcMcJIkST1jgJMkSeoZA5wkSVLPGOAkSZJ6xgAnSZLUMwY4SZKknjHASZIk9YwBTpIkqWcMcJIkST1jgJMkSeoZA5wkSVLPGOAkSZJ6xgAnSZLUMwY4SZKknjHASZIk9YwBTpIkqWcMcJIkST1jgJMkSeoZA5wkSVLPGOAkSZJ6xgAnSZLUMwY4SZKknjHASZIk9YwBTpIkqWfWne0CJGk6C4764myXMGdsuuF6s12CpLXAACfpEe2G4w6Y7RJGsuCoL/amVkn95yVUSZKknhlbgEtyUpLbklw50LZ5knOSXNd+btbak+T4JEuTXJ7kGQPbLGr9r0uyaKD9mUmuaNscnyTjOhdJkqRHknGOwH0c2G+VtqOAr1XVjsDX2neA5wM7ts/hwEehC3zA0cAewO7A0ROhr/V5zcB2qx5LkiRpThpbgKuqbwArVmk+CDi5LZ8MvHCg/ZTqXADMS7IVsC9wTlWtqKrbgXOA/dq6Tarqgqoq4JSBfUmSJM1pM30P3JZVdUtb/gGwZVveGrhpoN+y1jZV+7JJ2ieV5PAkS5IsWb58+cM7A0mSpFk2a5MY2shZzdCxTqiqhVW1cP78+TNxSEmSpLGZ6QB3a7v8Sft5W2u/Gdh2oN82rW2q9m0maZckSZrzZjrALQYmZpIuAs4YaD+kzUbdE7izXWo9G9gnyWZt8sI+wNlt3coke7bZp4cM7EuSJGlOG9uDfJN8GtgL2CLJMrrZpMcBpyU5DLgReFnrfhawP7AUuBc4FKCqViQ5Bri49XtPVU1MjHgd3UzXDYEvtY8kSdKcN7YAV1UHD1n13En6FnDEkP2cBJw0SfsSYOeHU6MkSVIf+SYGSZKknjHASZIk9YwBTvfgcfIAAASpSURBVJIkqWcMcJIkST1jgJMkSeoZA5wkSVLPGOAkSZJ6xgAnSZLUMwY4SZKknjHASZIk9YwBTpIkqWcMcJIkST1jgJMkSeoZA5wkSVLPGOAkSZJ6xgAnSZLUMwY4SZKknjHASZIk9YwBTpIkqWcMcJIkST1jgJMkSeoZA5wkSVLPGOAkSZJ6xgAnSZLUMwY4SZKknjHASZIk9YwBTpIkqWcMcJIkST1jgJMkSeoZA5wkSVLPGOAkSZJ6xgAnSZLUMwY4SZKknjHASZIk9YwBTpIkqWcMcJIkST1jgJMkSeqZWQlwSW5IckWSy5IsaW2bJzknyXXt52atPUmOT7I0yeVJnjGwn0Wt/3VJFs3GuUiSJM202RyB+72q2rWqFrbvRwFfq6odga+17wDPB3Zsn8OBj0IX+ICjgT2A3YGjJ0KfJEnSXPZIuoR6EHByWz4ZeOFA+ynVuQCYl2QrYF/gnKpaUVW3A+cA+8100ZIkSTNttgJcAV9JckmSw1vbllV1S1v+AbBlW94auGlg22WtbVi7JEnSnLbuLB33OVV1c5LHA+ckuXZwZVVVklpbB2sh8XCA7bbbbm3tVpIkaVbMyghcVd3cft4G/AfdPWy3tkujtJ+3te43A9sObL5NaxvWPtnxTqiqhVW1cP78+WvzVCRJkmbcjAe4JL+aZOOJZWAf4EpgMTAxk3QRcEZbXgwc0maj7gnc2S61ng3sk2SzNnlhn9YmSZI0p83GJdQtgf9IMnH8T1XVl5NcDJyW5DDgRuBlrf9ZwP7AUuBe4FCAqlqR5Bjg4tbvPVW1YuZOQ5IkaXbMeICrquuBXSZp/xHw3EnaCzhiyL5OAk5a2zVKkiQ9kj2SHiMiSZKkERjgJEmSema2HiMiSbOm3YO79vf7/rW/z+4uEkl6KAOcpEcdQ5GkvvMSqiRJUs8Y4CRJknrGACdJktQzBjhJkqSeMcBJkiT1jAFOkiSpZwxwkiRJPWOAkyRJ6hkDnCRJUs8Y4CRJknrGACdJktQzBjhJkqSeMcBJkiT1TKpqtmuYUUmWAzfOdh2S5pwtgB/OdhGS5pwnVdX8VRsfdQFOksYhyZKqWjjbdUh6dPASqiRJUs8Y4CRJknrGACdJa8cJs12ApEcP74GTJEnqGUfgJEmSesYAJ0mTSHL3avbfK8mZbfnAJEeNpzJJgnVnuwBJmmuqajGweLbrkDR3OQInSVNoI2vnJTk9ybVJPpkkbd1+re1bwIsGtnlVkn9syy9IcmGSS5N8NcmWs3QqkuYQA5wkTW834E+BnYAnA89OsgHwMeAFwDOBJwzZ9nxgz6raDTgV+MvxlytprvMSqiRN76KqWgaQ5DJgAXA38L2quq61/xtw+CTbbgN8JslWwPrA92akYklzmiNwkjS9+waWH2D1/uf3w8A/VtXTgdcCG6zNwiQ9OhngJGnNXAssSLJD+37wkH6bAje35UVjr0rSo4IBTpLWQFX9hO6S6RfbJIbbhnR9F/DZJJcAP5yh8iTNcb6JQZIkqWccgZMkSeoZA5wkSVLPGOAkSZJ6xgAnSZLUMwY4SZKknjHASZIk9YwBTpIkqWcMcJIkST3z/wH9kLCLYpTouQAAAABJRU5ErkJggg==\n",
            "text/plain": [
              "<Figure size 720x432 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "GTdiN1ZH6ZMd",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 390
        },
        "outputId": "2a07f9b6-4c1e-4fb2-de07-826f62554de1"
      },
      "source": [
        "dfIndiapak=df_can.loc[['India','Pakistan'],years].transpose()\n",
        "dfIndiapak.plot(\n",
        "    kind='box',\n",
        "    figsize=(10,6)\n",
        ")\n",
        "plt.title('Box plot of india from 1980-2013')\n",
        "plt.ylabel('Number of Immigrants')\n",
        "plt.show()"
      ],
      "execution_count": 22,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 720x432 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "rnsI3-3uxEGf",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 651
        },
        "outputId": "dc27a68f-bc09-4e1c-e85c-5c8497cd9533"
      },
      "source": [
        "df_can"
      ],
      "execution_count": 64,
      "outputs": [
        {
          "output_type": "execute_result",
          "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>Continent-region</th>\n",
              "      <th>DEV</th>\n",
              "      <th>Development-status</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>1987</th>\n",
              "      <th>1988</th>\n",
              "      <th>1989</th>\n",
              "      <th>1990</th>\n",
              "      <th>1991</th>\n",
              "      <th>1992</th>\n",
              "      <th>1993</th>\n",
              "      <th>1994</th>\n",
              "      <th>1995</th>\n",
              "      <th>1996</th>\n",
              "      <th>1997</th>\n",
              "      <th>1998</th>\n",
              "      <th>1999</th>\n",
              "      <th>2000</th>\n",
              "      <th>2001</th>\n",
              "      <th>2002</th>\n",
              "      <th>2003</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",
              "      <th>Total_count</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",
              "      <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>902</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>741</td>\n",
              "      <td>828</td>\n",
              "      <td>1076</td>\n",
              "      <td>1028</td>\n",
              "      <td>1378</td>\n",
              "      <td>1170</td>\n",
              "      <td>713</td>\n",
              "      <td>858</td>\n",
              "      <td>1537</td>\n",
              "      <td>2212</td>\n",
              "      <td>2555</td>\n",
              "      <td>1999</td>\n",
              "      <td>2395</td>\n",
              "      <td>3326</td>\n",
              "      <td>4067</td>\n",
              "      <td>3697</td>\n",
              "      <td>3479</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",
              "      <td>59541</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Albania</th>\n",
              "      <td>Europe</td>\n",
              "      <td>Southern Europe</td>\n",
              "      <td>901</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>2</td>\n",
              "      <td>2</td>\n",
              "      <td>3</td>\n",
              "      <td>3</td>\n",
              "      <td>21</td>\n",
              "      <td>56</td>\n",
              "      <td>96</td>\n",
              "      <td>71</td>\n",
              "      <td>63</td>\n",
              "      <td>113</td>\n",
              "      <td>307</td>\n",
              "      <td>574</td>\n",
              "      <td>1264</td>\n",
              "      <td>1816</td>\n",
              "      <td>1602</td>\n",
              "      <td>1021</td>\n",
              "      <td>853</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",
              "      <td>16600</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Algeria</th>\n",
              "      <td>Africa</td>\n",
              "      <td>Northern Africa</td>\n",
              "      <td>902</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>132</td>\n",
              "      <td>242</td>\n",
              "      <td>434</td>\n",
              "      <td>491</td>\n",
              "      <td>872</td>\n",
              "      <td>795</td>\n",
              "      <td>717</td>\n",
              "      <td>595</td>\n",
              "      <td>1106</td>\n",
              "      <td>2054</td>\n",
              "      <td>1842</td>\n",
              "      <td>2292</td>\n",
              "      <td>2389</td>\n",
              "      <td>2867</td>\n",
              "      <td>3418</td>\n",
              "      <td>3406</td>\n",
              "      <td>3072</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",
              "      <td>70341</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>American Samoa</th>\n",
              "      <td>Oceania</td>\n",
              "      <td>Polynesia</td>\n",
              "      <td>902</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>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>2</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>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>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>908</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Andorra</th>\n",
              "      <td>Europe</td>\n",
              "      <td>Southern Europe</td>\n",
              "      <td>901</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>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>3</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>2</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>2</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",
              "      <td>916</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",
              "      <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",
              "      <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",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Viet Nam</th>\n",
              "      <td>Asia</td>\n",
              "      <td>South-Eastern Asia</td>\n",
              "      <td>902</td>\n",
              "      <td>Developing regions</td>\n",
              "      <td>1191</td>\n",
              "      <td>1829</td>\n",
              "      <td>2162</td>\n",
              "      <td>3404</td>\n",
              "      <td>7583</td>\n",
              "      <td>5907</td>\n",
              "      <td>2741</td>\n",
              "      <td>1406</td>\n",
              "      <td>1411</td>\n",
              "      <td>3004</td>\n",
              "      <td>3801</td>\n",
              "      <td>5870</td>\n",
              "      <td>5416</td>\n",
              "      <td>6547</td>\n",
              "      <td>5105</td>\n",
              "      <td>3723</td>\n",
              "      <td>2462</td>\n",
              "      <td>1752</td>\n",
              "      <td>1631</td>\n",
              "      <td>1419</td>\n",
              "      <td>1803</td>\n",
              "      <td>2117</td>\n",
              "      <td>2291</td>\n",
              "      <td>1713</td>\n",
              "      <td>1816</td>\n",
              "      <td>1852</td>\n",
              "      <td>3153</td>\n",
              "      <td>2574</td>\n",
              "      <td>1784</td>\n",
              "      <td>2171</td>\n",
              "      <td>1942</td>\n",
              "      <td>1723</td>\n",
              "      <td>1731</td>\n",
              "      <td>2112</td>\n",
              "      <td>98048</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Western Sahara</th>\n",
              "      <td>Africa</td>\n",
              "      <td>Northern Africa</td>\n",
              "      <td>902</td>\n",
              "      <td>Developing 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>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</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",
              "      <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>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>904</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Yemen</th>\n",
              "      <td>Asia</td>\n",
              "      <td>Western Asia</td>\n",
              "      <td>902</td>\n",
              "      <td>Developing regions</td>\n",
              "      <td>1</td>\n",
              "      <td>2</td>\n",
              "      <td>1</td>\n",
              "      <td>6</td>\n",
              "      <td>0</td>\n",
              "      <td>18</td>\n",
              "      <td>7</td>\n",
              "      <td>12</td>\n",
              "      <td>7</td>\n",
              "      <td>18</td>\n",
              "      <td>4</td>\n",
              "      <td>18</td>\n",
              "      <td>41</td>\n",
              "      <td>41</td>\n",
              "      <td>39</td>\n",
              "      <td>73</td>\n",
              "      <td>144</td>\n",
              "      <td>121</td>\n",
              "      <td>141</td>\n",
              "      <td>134</td>\n",
              "      <td>122</td>\n",
              "      <td>181</td>\n",
              "      <td>171</td>\n",
              "      <td>113</td>\n",
              "      <td>124</td>\n",
              "      <td>161</td>\n",
              "      <td>140</td>\n",
              "      <td>122</td>\n",
              "      <td>133</td>\n",
              "      <td>128</td>\n",
              "      <td>211</td>\n",
              "      <td>160</td>\n",
              "      <td>174</td>\n",
              "      <td>217</td>\n",
              "      <td>3887</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Zambia</th>\n",
              "      <td>Africa</td>\n",
              "      <td>Eastern Africa</td>\n",
              "      <td>902</td>\n",
              "      <td>Developing regions</td>\n",
              "      <td>11</td>\n",
              "      <td>17</td>\n",
              "      <td>11</td>\n",
              "      <td>7</td>\n",
              "      <td>16</td>\n",
              "      <td>9</td>\n",
              "      <td>15</td>\n",
              "      <td>23</td>\n",
              "      <td>44</td>\n",
              "      <td>68</td>\n",
              "      <td>77</td>\n",
              "      <td>69</td>\n",
              "      <td>73</td>\n",
              "      <td>46</td>\n",
              "      <td>51</td>\n",
              "      <td>41</td>\n",
              "      <td>34</td>\n",
              "      <td>72</td>\n",
              "      <td>34</td>\n",
              "      <td>51</td>\n",
              "      <td>39</td>\n",
              "      <td>78</td>\n",
              "      <td>50</td>\n",
              "      <td>46</td>\n",
              "      <td>56</td>\n",
              "      <td>91</td>\n",
              "      <td>77</td>\n",
              "      <td>71</td>\n",
              "      <td>64</td>\n",
              "      <td>60</td>\n",
              "      <td>102</td>\n",
              "      <td>69</td>\n",
              "      <td>46</td>\n",
              "      <td>59</td>\n",
              "      <td>2579</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Zimbabwe</th>\n",
              "      <td>Africa</td>\n",
              "      <td>Eastern Africa</td>\n",
              "      <td>902</td>\n",
              "      <td>Developing regions</td>\n",
              "      <td>72</td>\n",
              "      <td>114</td>\n",
              "      <td>102</td>\n",
              "      <td>44</td>\n",
              "      <td>32</td>\n",
              "      <td>29</td>\n",
              "      <td>43</td>\n",
              "      <td>68</td>\n",
              "      <td>99</td>\n",
              "      <td>187</td>\n",
              "      <td>129</td>\n",
              "      <td>94</td>\n",
              "      <td>61</td>\n",
              "      <td>72</td>\n",
              "      <td>78</td>\n",
              "      <td>58</td>\n",
              "      <td>39</td>\n",
              "      <td>44</td>\n",
              "      <td>43</td>\n",
              "      <td>49</td>\n",
              "      <td>98</td>\n",
              "      <td>110</td>\n",
              "      <td>191</td>\n",
              "      <td>669</td>\n",
              "      <td>1450</td>\n",
              "      <td>615</td>\n",
              "      <td>454</td>\n",
              "      <td>663</td>\n",
              "      <td>611</td>\n",
              "      <td>508</td>\n",
              "      <td>494</td>\n",
              "      <td>434</td>\n",
              "      <td>437</td>\n",
              "      <td>407</td>\n",
              "      <td>9500</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>195 rows × 39 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "               Continent    Continent-region  DEV  ...  2012  2013  Total_count\n",
              "Country                                            ...                         \n",
              "Afghanistan         Asia       Southern Asia  902  ...  2635  2004        59541\n",
              "Albania           Europe     Southern Europe  901  ...   620   603        16600\n",
              "Algeria           Africa     Northern Africa  902  ...  3774  4331        70341\n",
              "American Samoa   Oceania           Polynesia  902  ...     0     0          908\n",
              "Andorra           Europe     Southern Europe  901  ...     1     1          916\n",
              "...                  ...                 ...  ...  ...   ...   ...          ...\n",
              "Viet Nam            Asia  South-Eastern Asia  902  ...  1731  2112        98048\n",
              "Western Sahara    Africa     Northern Africa  902  ...     0     0          904\n",
              "Yemen               Asia        Western Asia  902  ...   174   217         3887\n",
              "Zambia            Africa      Eastern Africa  902  ...    46    59         2579\n",
              "Zimbabwe          Africa      Eastern Africa  902  ...   437   407         9500\n",
              "\n",
              "[195 rows x 39 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 64
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "kdphtJyfvJVZ",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "asia = df_can[(df_can['Continent']=='Asia')].sort_values('Total_count', ascending=False).head()\n",
        "eur = df_can[(df_can['Continent']=='Europe')].sort_values('Total_count', ascending=False).head()\n",
        "afr = df_can[(df_can['Continent']=='Africa')].sort_values('Total_count', ascending=False).head()\n",
        "ocn = df_can[(df_can['Continent']=='Oceania')].sort_values('Total_count', ascending=False).head()\n",
        "asia = asia[years].transpose()\n",
        "eur = eur[years].transpose()\n",
        "afr = afr[years].transpose()\n",
        "ocn = ocn[years].transpose()"
      ],
      "execution_count": 65,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "X3uZ0VfDwz8W",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 531
        },
        "outputId": "e5dd01fb-d206-47fa-f0e9-38d6a8e9c657"
      },
      "source": [
        " # making subplots\n",
        "fig = plt.figure()\n",
        "ax1 = fig.add_subplot(1,2,1)\n",
        "ax2 = fig.add_subplot(1,2,2)\n",
        "fig2 = plt.figure()\n",
        "ax3 = fig2.add_subplot(1,2,1)\n",
        "ax4 = fig2.add_subplot(1,2,2)\n",
        "eur.plot(kind='box', color='blue', vert=False, ax=ax1)\n",
        "asia.plot(kind='box', color='blue', vert=False, ax=ax2)\n",
        "afr.plot(kind='box', color='blue', vert=False, ax=ax3)\n",
        "ocn.plot(kind='box', color='blue', vert=False, ax=ax4)"
      ],
      "execution_count": 66,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.axes._subplots.AxesSubplot at 0x7f6ef980d128>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 66
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 2 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 2 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "_WXXg22mxWaO",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 141
        },
        "outputId": "d223ce4e-1fee-4836-ad45-e8592cd3839c"
      },
      "source": [
        "# Outlier Detection\n",
        "temp = asia.describe()\n",
        "Q1 = temp.loc['25%', 'Philippines']\n",
        "Q3 = temp.loc['75%', 'Philippines']\n",
        "IQR = Q3-Q1\n",
        "\n",
        "Outlier1 = Q3 + 1.5*IQR\n",
        "Outlier2 = Q1 - 1.5*IQR\n",
        "print(Outlier1)\n",
        "print(Outlier2)\n",
        "\n",
        "asia[asia['Philippines']>Outlier1]"
      ],
      "execution_count": 67,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "35128.0\n",
            "-7216.0\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "execute_result",
          "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>Country</th>\n",
              "      <th>India</th>\n",
              "      <th>China</th>\n",
              "      <th>Philippines</th>\n",
              "      <th>Pakistan</th>\n",
              "      <th>Iran (Islamic Republic of)</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>2010</th>\n",
              "      <td>34235</td>\n",
              "      <td>30391</td>\n",
              "      <td>38617</td>\n",
              "      <td>6811</td>\n",
              "      <td>7477</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2011</th>\n",
              "      <td>27509</td>\n",
              "      <td>28502</td>\n",
              "      <td>36765</td>\n",
              "      <td>7468</td>\n",
              "      <td>7479</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "Country  India  China  Philippines  Pakistan  Iran (Islamic Republic of)\n",
              "2010     34235  30391        38617      6811                        7477\n",
              "2011     27509  28502        36765      7468                        7479"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 67
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "oJcZKD3R1-y7",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "outputId": "0bf15a7b-ce3d-4ec9-bfe0-bf06f91b4ce5"
      },
      "source": [
        "dfIndiapak"
      ],
      "execution_count": 114,
      "outputs": [
        {
          "output_type": "execute_result",
          "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>Country</th>\n",
              "      <th>India</th>\n",
              "      <th>Pakistan</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>1980</th>\n",
              "      <td>8880</td>\n",
              "      <td>978</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1981</th>\n",
              "      <td>8670</td>\n",
              "      <td>972</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1982</th>\n",
              "      <td>8147</td>\n",
              "      <td>1201</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1983</th>\n",
              "      <td>7338</td>\n",
              "      <td>900</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1984</th>\n",
              "      <td>5704</td>\n",
              "      <td>668</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1985</th>\n",
              "      <td>4211</td>\n",
              "      <td>514</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1986</th>\n",
              "      <td>7150</td>\n",
              "      <td>691</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1987</th>\n",
              "      <td>10189</td>\n",
              "      <td>1072</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1988</th>\n",
              "      <td>11522</td>\n",
              "      <td>1334</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1989</th>\n",
              "      <td>10343</td>\n",
              "      <td>2261</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1990</th>\n",
              "      <td>12041</td>\n",
              "      <td>2470</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1991</th>\n",
              "      <td>13734</td>\n",
              "      <td>3079</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1992</th>\n",
              "      <td>13673</td>\n",
              "      <td>4071</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1993</th>\n",
              "      <td>21496</td>\n",
              "      <td>4777</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1994</th>\n",
              "      <td>18620</td>\n",
              "      <td>4666</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1995</th>\n",
              "      <td>18489</td>\n",
              "      <td>4994</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1996</th>\n",
              "      <td>23859</td>\n",
              "      <td>9125</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1997</th>\n",
              "      <td>22268</td>\n",
              "      <td>13073</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1998</th>\n",
              "      <td>17241</td>\n",
              "      <td>9068</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1999</th>\n",
              "      <td>18974</td>\n",
              "      <td>9979</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2000</th>\n",
              "      <td>28572</td>\n",
              "      <td>15400</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2001</th>\n",
              "      <td>31223</td>\n",
              "      <td>16708</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2002</th>\n",
              "      <td>31889</td>\n",
              "      <td>15110</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2003</th>\n",
              "      <td>27155</td>\n",
              "      <td>13205</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2004</th>\n",
              "      <td>28235</td>\n",
              "      <td>13399</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2005</th>\n",
              "      <td>36210</td>\n",
              "      <td>14314</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2006</th>\n",
              "      <td>33848</td>\n",
              "      <td>13127</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2007</th>\n",
              "      <td>28742</td>\n",
              "      <td>10124</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2008</th>\n",
              "      <td>28261</td>\n",
              "      <td>8994</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2009</th>\n",
              "      <td>29456</td>\n",
              "      <td>7217</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2010</th>\n",
              "      <td>34235</td>\n",
              "      <td>6811</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2011</th>\n",
              "      <td>27509</td>\n",
              "      <td>7468</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2012</th>\n",
              "      <td>30933</td>\n",
              "      <td>11227</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2013</th>\n",
              "      <td>33087</td>\n",
              "      <td>12603</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "Country  India  Pakistan\n",
              "1980      8880       978\n",
              "1981      8670       972\n",
              "1982      8147      1201\n",
              "1983      7338       900\n",
              "1984      5704       668\n",
              "1985      4211       514\n",
              "1986      7150       691\n",
              "1987     10189      1072\n",
              "1988     11522      1334\n",
              "1989     10343      2261\n",
              "1990     12041      2470\n",
              "1991     13734      3079\n",
              "1992     13673      4071\n",
              "1993     21496      4777\n",
              "1994     18620      4666\n",
              "1995     18489      4994\n",
              "1996     23859      9125\n",
              "1997     22268     13073\n",
              "1998     17241      9068\n",
              "1999     18974      9979\n",
              "2000     28572     15400\n",
              "2001     31223     16708\n",
              "2002     31889     15110\n",
              "2003     27155     13205\n",
              "2004     28235     13399\n",
              "2005     36210     14314\n",
              "2006     33848     13127\n",
              "2007     28742     10124\n",
              "2008     28261      8994\n",
              "2009     29456      7217\n",
              "2010     34235      6811\n",
              "2011     27509      7468\n",
              "2012     30933     11227\n",
              "2013     33087     12603"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 114
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "MlNn6wW72qsP",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 194
        },
        "outputId": "78c445ca-e299-4130-85dc-1a15ed85485d"
      },
      "source": [
        "dfIndiapak.reset_index(inplace=True)\n",
        "dfIndiapak.rename(columns={'Country':'index','index':'Year'}, inplace=True)\n",
        "dfIndiapak.head()"
      ],
      "execution_count": 125,
      "outputs": [
        {
          "output_type": "execute_result",
          "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>Country</th>\n",
              "      <th>Year</th>\n",
              "      <th>India</th>\n",
              "      <th>Pakistan</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>1980</td>\n",
              "      <td>8880</td>\n",
              "      <td>978</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>1981</td>\n",
              "      <td>8670</td>\n",
              "      <td>972</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>1982</td>\n",
              "      <td>8147</td>\n",
              "      <td>1201</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>1983</td>\n",
              "      <td>7338</td>\n",
              "      <td>900</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>1984</td>\n",
              "      <td>5704</td>\n",
              "      <td>668</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "Country  Year  India  Pakistan\n",
              "0        1980   8880       978\n",
              "1        1981   8670       972\n",
              "2        1982   8147      1201\n",
              "3        1983   7338       900\n",
              "4        1984   5704       668"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 125
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "aiAoHpIWxhmP",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 408
        },
        "outputId": "1030db77-7da9-4236-ac92-be3521677b93"
      },
      "source": [
        "# Scatter and Bubble Plots\n",
        "x=dfIndiapak['Year'].astype('int64')\n",
        "y=dfIndiapak['India']\n",
        "dfIndiapak.plot(\n",
        "    kind='scatter',\n",
        "    x='Year',\n",
        "    y='India',\n",
        "    color='red',\n",
        "    figsize=(10,6)\n",
        ")\n",
        "plt.title('Scatter plot of india from 1980-2013')\n",
        "plt.ylabel('Number of Immigrants')\n",
        "plt.show()"
      ],
      "execution_count": 129,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 720x432 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "f0lt-PJb5TjV",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 408
        },
        "outputId": "b20ee616-8f67-4807-8cc4-11c44f556a94"
      },
      "source": [
        "# Bubble Plot\n",
        "norm_india = (dfIndiapak['India'] - dfIndiapak['India'].min()) / (dfIndiapak['India'].max() - dfIndiapak['India'].min())\n",
        "norm_pak = (dfIndiapak['Pakistan'] - dfIndiapak['Pakistan'].min()) / (dfIndiapak['Pakistan'].max() - dfIndiapak['Pakistan'].min())\n",
        "ax0 = dfIndiapak.plot(kind='scatter', x='Year', y='India', color='yellow', s=norm_india*200, figsize=(10,6))\n",
        "dfIndiapak.plot(kind='scatter', x='Year', y='Pakistan', color='purple', s=norm_india*200, figsize=(10,6), ax=ax0)\n",
        "plt.title('Total immigrants from India and Pakistan 1980-2013')\n",
        "plt.xlabel(\"years\")\n",
        "plt.ylabel(\"Number of immigrants\")\n",
        "ax0.legend(['India','Pakistan'], loc='upper left')\n",
        "plt.show()"
      ],
      "execution_count": 134,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 720x432 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "v6tW8UfV7fks",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 390
        },
        "outputId": "82e2b802-de11-476c-ec92-5a16065c4b97"
      },
      "source": [
        "# Boxplots\n",
        "dfIndiapak=df_can.loc[['India','Pakistan'],years].transpose()\n",
        "dfIndiapak.plot(\n",
        "    kind='box',\n",
        "    figsize=(10,6),\n",
        "    color='red'\n",
        ")\n",
        "plt.title('Box plot of india from 1980-2013')\n",
        "plt.ylabel('Number of Immigrants')\n",
        "plt.show()"
      ],
      "execution_count": 23,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 720x432 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "k5S38uy3F8Db",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 35
        },
        "outputId": "b5929cfd-bc88-4652-ed35-0488014db779"
      },
      "source": [
        "%matplotlib inline\n",
        "import matplotlib as mpl\n",
        "import matplotlib.pyplot as plt\n",
        "import matplotlib.patches as mpatches # needed for waffle Charts\n",
        "mpl.style.use('ggplot') # optional: for ggplot-like style\n",
        "# check for latest version of Matplotlib\n",
        "print ('Matplotlib version: ', mpl.__version__) # >= 2.0.0"
      ],
      "execution_count": 25,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Matplotlib version:  3.2.2\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "R3iNGNmn1Wfn",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "# WAFFLE CHARTS"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ObpZFSJrGAg8",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "def create_waffle_chart(categories, values, height, width, colormap, value_sign=''):\n",
        "\n",
        "    # compute the proportion of each category with respect to the total\n",
        "    total_values = sum(values)\n",
        "    category_proportions = [(float(value) / total_values) for value in values]\n",
        "\n",
        "    # compute the total number of tiles\n",
        "    total_num_tiles = width * height # total number of tiles\n",
        "    print ('Total number of tiles is', total_num_tiles)\n",
        "    \n",
        "    # compute the number of tiles for each catagory\n",
        "    tiles_per_category = [round(proportion * total_num_tiles) for proportion in category_proportions]\n",
        "\n",
        "    # print out number of tiles per category\n",
        "    for i, tiles in enumerate(tiles_per_category):\n",
        "        print (df_dsn.index.values[i] + ': ' + str(tiles))\n",
        "    \n",
        "    # initialize the waffle chart as an empty matrix\n",
        "    waffle_chart = np.zeros((height, width))\n",
        "\n",
        "    # define indices to loop through waffle chart\n",
        "    category_index = 0\n",
        "    tile_index = 0\n",
        "\n",
        "    # populate the waffle chart\n",
        "    for col in range(width):\n",
        "        for row in range(height):\n",
        "            tile_index += 1\n",
        "\n",
        "            # if the number of tiles populated for the current category \n",
        "            # is equal to its corresponding allocated tiles...\n",
        "            if tile_index > sum(tiles_per_category[0:category_index]):\n",
        "                # ...proceed to the next category\n",
        "                category_index += 1       \n",
        "            \n",
        "            # set the class value to an integer, which increases with class\n",
        "            waffle_chart[row, col] = category_index\n",
        "    \n",
        "    # instantiate a new figure object\n",
        "    fig = plt.figure()\n",
        "\n",
        "    # use matshow to display the waffle chart\n",
        "    colormap = plt.cm.coolwarm\n",
        "    plt.matshow(waffle_chart, cmap=colormap)\n",
        "    plt.colorbar()\n",
        "\n",
        "    # get the axis\n",
        "    ax = plt.gca()\n",
        "\n",
        "    # set minor ticks\n",
        "    ax.set_xticks(np.arange(-.5, (width), 1), minor=True)\n",
        "    ax.set_yticks(np.arange(-.5, (height), 1), minor=True)\n",
        "    \n",
        "    # add dridlines based on minor ticks\n",
        "    ax.grid(which='minor', color='w', linestyle='-', linewidth=2)\n",
        "\n",
        "    plt.xticks([])\n",
        "    plt.yticks([])\n",
        "\n",
        "    # compute cumulative sum of individual categories to match color schemes between chart and legend\n",
        "    values_cumsum = np.cumsum(values)\n",
        "    total_values = values_cumsum[len(values_cumsum) - 1]\n",
        "\n",
        "    # create legend\n",
        "    legend_handles = []\n",
        "    for i, category in enumerate(categories):\n",
        "        if value_sign == '%':\n",
        "            label_str = category + ' (' + str(values[i]) + value_sign + ')'\n",
        "        else:\n",
        "            label_str = category + ' (' + value_sign + str(values[i]) + ')'\n",
        "            \n",
        "        color_val = colormap(float(values_cumsum[i])/total_values)\n",
        "        legend_handles.append(mpatches.Patch(color=color_val, label=label_str))\n",
        "\n",
        "    # add legend to chart\n",
        "    plt.legend(\n",
        "        handles=legend_handles,\n",
        "        loc='lower center', \n",
        "        ncol=len(categories),\n",
        "        bbox_to_anchor=(0., -0.2, 0.95, .1)\n",
        "    )"
      ],
      "execution_count": 26,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "bsTPWjDBGQeT",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 252
        },
        "outputId": "3aa76150-6f18-41ec-95b3-d7e49d576627"
      },
      "source": [
        "# let's create a new dataframe for these three countries \n",
        "df_dsn = df_can.loc[['Denmark', 'Norway', 'Sweden'], :]\n",
        "# let's take a look at our dataframe\n",
        "df_dsn"
      ],
      "execution_count": 27,
      "outputs": [
        {
          "output_type": "execute_result",
          "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>Continent-region</th>\n",
              "      <th>DEV</th>\n",
              "      <th>Development-status</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>1987</th>\n",
              "      <th>1988</th>\n",
              "      <th>1989</th>\n",
              "      <th>1990</th>\n",
              "      <th>1991</th>\n",
              "      <th>1992</th>\n",
              "      <th>1993</th>\n",
              "      <th>1994</th>\n",
              "      <th>1995</th>\n",
              "      <th>1996</th>\n",
              "      <th>1997</th>\n",
              "      <th>1998</th>\n",
              "      <th>1999</th>\n",
              "      <th>2000</th>\n",
              "      <th>2001</th>\n",
              "      <th>2002</th>\n",
              "      <th>2003</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",
              "      <th>Total_count</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",
              "      <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>Denmark</th>\n",
              "      <td>Europe</td>\n",
              "      <td>Northern Europe</td>\n",
              "      <td>901</td>\n",
              "      <td>Developed regions</td>\n",
              "      <td>272</td>\n",
              "      <td>293</td>\n",
              "      <td>299</td>\n",
              "      <td>106</td>\n",
              "      <td>93</td>\n",
              "      <td>73</td>\n",
              "      <td>93</td>\n",
              "      <td>109</td>\n",
              "      <td>129</td>\n",
              "      <td>129</td>\n",
              "      <td>118</td>\n",
              "      <td>111</td>\n",
              "      <td>158</td>\n",
              "      <td>186</td>\n",
              "      <td>93</td>\n",
              "      <td>111</td>\n",
              "      <td>70</td>\n",
              "      <td>83</td>\n",
              "      <td>63</td>\n",
              "      <td>81</td>\n",
              "      <td>93</td>\n",
              "      <td>81</td>\n",
              "      <td>70</td>\n",
              "      <td>89</td>\n",
              "      <td>89</td>\n",
              "      <td>62</td>\n",
              "      <td>101</td>\n",
              "      <td>97</td>\n",
              "      <td>108</td>\n",
              "      <td>81</td>\n",
              "      <td>92</td>\n",
              "      <td>93</td>\n",
              "      <td>94</td>\n",
              "      <td>81</td>\n",
              "      <td>4802</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Norway</th>\n",
              "      <td>Europe</td>\n",
              "      <td>Northern Europe</td>\n",
              "      <td>901</td>\n",
              "      <td>Developed regions</td>\n",
              "      <td>116</td>\n",
              "      <td>77</td>\n",
              "      <td>106</td>\n",
              "      <td>51</td>\n",
              "      <td>31</td>\n",
              "      <td>54</td>\n",
              "      <td>56</td>\n",
              "      <td>80</td>\n",
              "      <td>73</td>\n",
              "      <td>76</td>\n",
              "      <td>83</td>\n",
              "      <td>103</td>\n",
              "      <td>74</td>\n",
              "      <td>92</td>\n",
              "      <td>60</td>\n",
              "      <td>65</td>\n",
              "      <td>70</td>\n",
              "      <td>104</td>\n",
              "      <td>31</td>\n",
              "      <td>36</td>\n",
              "      <td>56</td>\n",
              "      <td>78</td>\n",
              "      <td>74</td>\n",
              "      <td>77</td>\n",
              "      <td>73</td>\n",
              "      <td>57</td>\n",
              "      <td>53</td>\n",
              "      <td>73</td>\n",
              "      <td>66</td>\n",
              "      <td>75</td>\n",
              "      <td>46</td>\n",
              "      <td>49</td>\n",
              "      <td>53</td>\n",
              "      <td>59</td>\n",
              "      <td>3228</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Sweden</th>\n",
              "      <td>Europe</td>\n",
              "      <td>Northern Europe</td>\n",
              "      <td>901</td>\n",
              "      <td>Developed regions</td>\n",
              "      <td>281</td>\n",
              "      <td>308</td>\n",
              "      <td>222</td>\n",
              "      <td>176</td>\n",
              "      <td>128</td>\n",
              "      <td>158</td>\n",
              "      <td>187</td>\n",
              "      <td>198</td>\n",
              "      <td>171</td>\n",
              "      <td>182</td>\n",
              "      <td>130</td>\n",
              "      <td>167</td>\n",
              "      <td>179</td>\n",
              "      <td>203</td>\n",
              "      <td>192</td>\n",
              "      <td>176</td>\n",
              "      <td>161</td>\n",
              "      <td>151</td>\n",
              "      <td>123</td>\n",
              "      <td>170</td>\n",
              "      <td>138</td>\n",
              "      <td>184</td>\n",
              "      <td>149</td>\n",
              "      <td>161</td>\n",
              "      <td>129</td>\n",
              "      <td>205</td>\n",
              "      <td>139</td>\n",
              "      <td>193</td>\n",
              "      <td>165</td>\n",
              "      <td>167</td>\n",
              "      <td>159</td>\n",
              "      <td>134</td>\n",
              "      <td>140</td>\n",
              "      <td>140</td>\n",
              "      <td>6767</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "        Continent Continent-region  DEV  ... 2012  2013  Total_count\n",
              "Country                                  ...                        \n",
              "Denmark    Europe  Northern Europe  901  ...   94    81         4802\n",
              "Norway     Europe  Northern Europe  901  ...   53    59         3228\n",
              "Sweden     Europe  Northern Europe  901  ...  140   140         6767\n",
              "\n",
              "[3 rows x 39 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 27
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "T-sPjhIIGUEp",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "width = 40 # width of chart\n",
        "height = 10 # height of chart\n",
        "categories = df_dsn.index.values # categories\n",
        "values = df_dsn['Total_count'] # correponding values of categories\n",
        "colormap = plt.cm.coolwarm # color map class"
      ],
      "execution_count": 32,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ISpawhk7GXRH",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 355
        },
        "outputId": "8014c4cf-9cfe-4dea-c4ba-0dacbc1c59b6"
      },
      "source": [
        "create_waffle_chart(categories, values, height, width, colormap)"
      ],
      "execution_count": 33,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Total number of tiles is 400\n",
            "Denmark: 130\n",
            "Norway: 87\n",
            "Sweden: 183\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x288 with 0 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 1152x288 with 2 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "PIJ1wA941TZg",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "# Word Clouds"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "I7uEiozMHG-4",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 70
        },
        "outputId": "831e044b-157c-4de5-bd7e-4001a6f08152"
      },
      "source": [
        "# install wordcloud\n",
        "!conda install -c conda-forge wordcloud==1.4.1 --yes\n",
        "\n",
        "# import package and its set of stopwords\n",
        "from wordcloud import WordCloud, STOPWORDS\n",
        "\n",
        "print ('Wordcloud is installed and imported!')\n",
        "\n",
        "# download file and save as alice_novel.txt\n",
        "!wget --quiet https://s3-api.us-geo.objectstorage.softlayer.net/cf-courses-data/CognitiveClass/DV0101EN/labs/Data_Files/alice_novel.txt\n",
        "\n",
        "# open the file and read it into a variable alice_novel\n",
        "alice_novel = open('alice_novel.txt', 'r').read()\n",
        "    \n",
        "print ('File downloaded and saved!')"
      ],
      "execution_count": 39,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "/bin/bash: conda: command not found\n",
            "Wordcloud is installed and imported!\n",
            "File downloaded and saved!\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "CGcLgX0hHG6c",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 236
        },
        "outputId": "295be98b-2576-469d-d5a3-9f1ef46a7d42"
      },
      "source": [
        "#Step 1: stopwords removals - \n",
        "stopwordsremove = set(STOPWORDS)\n",
        "#Step2: create an object of class WordCloud\n",
        "alice_wc = WordCloud(\n",
        "    max_words=2000,\n",
        "    stopwords=stopwordsremove\n",
        ")\n",
        "#step3 : use object to call function\n",
        "alice_wc.generate(alice_novel)\n",
        "plt.imshow(alice_wc)\n",
        "fig = plt.figure()\n",
        "fig.set_figheight(20)\n",
        "fig.set_figwidth(20)\n",
        "plt.show()"
      ],
      "execution_count": 94,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1440x1440 with 0 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "IUGrw2zkHGyO",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 968
        },
        "outputId": "6e74485c-c226-43ee-bd19-d483fde27397"
      },
      "source": [
        "# Maps\n",
        "import folium\n",
        "worldmap = folium.Map(location=[56.130, -106.35], zoom_start=10)\n",
        "worldmap"
      ],
      "execution_count": 95,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div style=\"width:100%;\"><div style=\"position:relative;width:100%;height:0;padding-bottom:60%;\"><span style=\"color:#565656\">Make this Notebook Trusted to load map: File -> Trust Notebook</span><iframe src=\"about:blank\" style=\"position:absolute;width:100%;height:100%;left:0;top:0;border:none !important;\" data-html=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 onload=\"this.contentDocument.open();this.contentDocument.write(atob(this.getAttribute('data-html')));this.contentDocument.close();\" allowfullscreen webkitallowfullscreen mozallowfullscreen></iframe></div></div>"
            ],
            "text/plain": [
              "<folium.folium.Map at 0x7f6ef9874a58>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 95
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "XfrulWfp0N_l",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 195
        },
        "outputId": "ca07932c-d8ef-4a18-acb4-8c5349846884"
      },
      "source": [
        "# Getting the Dataset\n",
        "incidents = pd.read_csv('https://s3-api.us-geo.objectstorage.softlayer.net/cf-courses-data/CognitiveClass/DV0101EN/labs/Data_Files/Police_Department_Incidents_-_Previous_Year__2016_.csv')\n",
        "print('Dataset downloaded and read into a pandas dataframe!')\n",
        "print(incidents.head())\n",
        "print(incidents.shape)"
      ],
      "execution_count": 96,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Dataset downloaded and read into a pandas dataframe!\n",
            "   IncidntNum  ...            PdId\n",
            "0   120058272  ...  12005827212120\n",
            "1   120058272  ...  12005827212168\n",
            "2   141059263  ...  14105926363010\n",
            "3   160013662  ...  16001366271000\n",
            "4   160002740  ...  16000274071000\n",
            "\n",
            "[5 rows x 13 columns]\n",
            "(150500, 13)\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "aWPkgOxD0jn4",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "limit = 100\n",
        "inc = incidents.iloc[0:limit,:]"
      ],
      "execution_count": 97,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "cfW9OVbo0noo",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 968
        },
        "outputId": "6ce29a90-790f-49e6-df24-4960d6adfee3"
      },
      "source": [
        "latitude = 37.77\n",
        "longitude = -122.42\n",
        "map1 = folium.Map(location = [latitude, longitude], zoom_start=12)\n",
        "map1"
      ],
      "execution_count": 98,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div style=\"width:100%;\"><div style=\"position:relative;width:100%;height:0;padding-bottom:60%;\"><span style=\"color:#565656\">Make this Notebook Trusted to load map: File -> Trust Notebook</span><iframe src=\"about:blank\" style=\"position:absolute;width:100%;height:100%;left:0;top:0;border:none !important;\" data-html=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 onload=\"this.contentDocument.open();this.contentDocument.write(atob(this.getAttribute('data-html')));this.contentDocument.close();\" allowfullscreen webkitallowfullscreen mozallowfullscreen></iframe></div></div>"
            ],
            "text/plain": [
              "<folium.folium.Map at 0x7f6ef1a07940>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 98
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "_M4hNqrG0pUI",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 968
        },
        "outputId": "52f33aa0-d0b7-4949-e59e-c2ba995515d1"
      },
      "source": [
        "#given information about city coordinates\n",
        "latitude= 37.77\n",
        "longitude = -122.42\n",
        "\n",
        "#create map using folium library and Map class\n",
        "map1 = folium.Map(location = [latitude, longitude], zoom_start=12)\n",
        "map1\n",
        "\n",
        "#incident we will impose on the map\n",
        "incident = folium.map.FeatureGroup()\n",
        "\n",
        "#reduce size of dataset\n",
        "df1 = incidents.iloc[0:limit,:]\n",
        "\n",
        "#loop through the crimes by their lat Y and long X and create markers\n",
        "lats = list(df1.Y)\n",
        "longs = list(df1.X)\n",
        "labels = list(df1.Category)\n",
        "\n",
        "for lat, long, labs in zip(lats, longs, labels):\n",
        "        folium.CircleMarker([lat, long], popup=labs, radius=5, color='yellow', fill=True, \n",
        "                            fill_color='blue').add_to(map1)\n",
        "\n",
        "#add incidents/crimes to the map\n",
        "map1"
      ],
      "execution_count": 100,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div style=\"width:100%;\"><div style=\"position:relative;width:100%;height:0;padding-bottom:60%;\"><span style=\"color:#565656\">Make this Notebook Trusted to load map: File -> Trust Notebook</span><iframe src=\"about:blank\" style=\"position:absolute;width:100%;height:100%;left:0;top:0;border:none !important;\" data-html=<!DOCTYPE html>
<head>    
    <meta http-equiv="content-type" content="text/html; charset=UTF-8" />
    <script>L_PREFER_CANVAS=false; L_NO_TOUCH=false; L_DISABLE_3D=false;</script>
    <script src="https://cdn.jsdelivr.net/npm/leaflet@1.4.0/dist/leaflet.js"></script>
    <script src="https://code.jquery.com/jquery-1.12.4.min.js"></script>
    <script src="https://maxcdn.bootstrapcdn.com/bootstrap/3.2.0/js/bootstrap.min.js"></script>
    <script src="https://cdnjs.cloudflare.com/ajax/libs/Leaflet.awesome-markers/2.0.2/leaflet.awesome-markers.js"></script>
    <link rel="stylesheet" href="https://cdn.jsdelivr.net/npm/leaflet@1.4.0/dist/leaflet.css"/>
    <link rel="stylesheet" href="https://maxcdn.bootstrapcdn.com/bootstrap/3.2.0/css/bootstrap.min.css"/>
    <link rel="stylesheet" href="https://maxcdn.bootstrapcdn.com/bootstrap/3.2.0/css/bootstrap-theme.min.css"/>
    <link rel="stylesheet" href="https://maxcdn.bootstrapcdn.com/font-awesome/4.6.3/css/font-awesome.min.css"/>
    <link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/Leaflet.awesome-markers/2.0.2/leaflet.awesome-markers.css"/>
    <link rel="stylesheet" href="https://rawcdn.githack.com/python-visualization/folium/master/folium/templates/leaflet.awesome.rotate.css"/>
    <style>html, body {width: 100%;height: 100%;margin: 0;padding: 0;}</style>
    <style>#map {position:absolute;top:0;bottom:0;right:0;left:0;}</style>
    
    <meta name="viewport" content="width=device-width,
        initial-scale=1.0, maximum-scale=1.0, user-scalable=no" />
    <style>#map_56f7cd0eb11c45cfa51c1e6f0e899779 {
        position: relative;
        width: 100.0%;
        height: 100.0%;
        left: 0.0%;
        top: 0.0%;
        }
    </style>
</head>
<body>    
    
    <div class="folium-map" id="map_56f7cd0eb11c45cfa51c1e6f0e899779" ></div>
</body>
<script>    
    
    
        var bounds = null;
    

    var map_56f7cd0eb11c45cfa51c1e6f0e899779 = L.map(
        'map_56f7cd0eb11c45cfa51c1e6f0e899779', {
        center: [37.77, -122.42],
        zoom: 12,
        maxBounds: bounds,
        layers: [],
        worldCopyJump: false,
        crs: L.CRS.EPSG3857,
        zoomControl: true,
        });


    
    var tile_layer_a2f9512423fe4279991302f5d802dd4d = L.tileLayer(
        'https://{s}.tile.openstreetmap.org/{z}/{x}/{y}.png',
        {
        "attribution": null,
        "detectRetina": false,
        "maxNativeZoom": 18,
        "maxZoom": 18,
        "minZoom": 0,
        "noWrap": false,
        "opacity": 1,
        "subdomains": "abc",
        "tms": false
}).addTo(map_56f7cd0eb11c45cfa51c1e6f0e899779);
    
            var circle_marker_9226e730fa624c1195276fa904fbbc3e = L.circleMarker(
                [37.775420706711, -122.40340479147899],
                {
  "bubblingMouseEvents": true,
  "color": "yellow",
  "dashArray": null,
  "dashOffset": null,
  "fill": true,
  "fillColor": "blue",
  "fillOpacity": 0.2,
  "fillRule": "evenodd",
  "lineCap": "round",
  "lineJoin": "round",
  "opacity": 1.0,
  "radius": 5,
  "stroke": true,
  "weight": 3
}
                )
                .addTo(map_56f7cd0eb11c45cfa51c1e6f0e899779);
            
    
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            var popup_4f321dc896a8445197217a11b95ddbea = L.popup({maxWidth: '100%'
            
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            var popup_e71c55ffcf034e62ae5bf16d73bd8501 = L.popup({maxWidth: '100%'
            
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            var popup_e5d3af62ce094ae49d5f4e95d9dab75a = L.popup({maxWidth: '100%'
            
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                var html_fd31cfca10ad4da19c6963048fe9d373 = $(`<div id="html_fd31cfca10ad4da19c6963048fe9d373" style="width: 100.0%; height: 100.0%;">OTHER OFFENSES</div>`)[0];
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            circle_marker_8a2674da893f4f35ae64a45c85f4da25.bindPopup(popup_4c8b38f5f5ea43f99ae0fad1fcc4b903)
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            var popup_93fb9403fa6341839966f728c917378a = L.popup({maxWidth: '100%'
            
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                var html_274d457de57745fa9aaabda475e02f40 = $(`<div id="html_274d457de57745fa9aaabda475e02f40" style="width: 100.0%; height: 100.0%;">NON-CRIMINAL</div>`)[0];
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            circle_marker_2d1a27d046d4407c9da8d3cee89e2e95.bindPopup(popup_93fb9403fa6341839966f728c917378a)
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}
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            var popup_8a91efcc42004d398102d00d3e0deab2 = L.popup({maxWidth: '100%'
            
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            circle_marker_4fe42995caf04a9c95849df4144d13d0.bindPopup(popup_8a91efcc42004d398102d00d3e0deab2)
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            var circle_marker_291750501014400aa5c337cc350752ec = L.circleMarker(
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}
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            var popup_d56ff240b86742958d83259c156e81e1 = L.popup({maxWidth: '100%'
            
            });

            
                var html_4b8f5478ceb74dc7950e35716bf7b2b2 = $(`<div id="html_4b8f5478ceb74dc7950e35716bf7b2b2" style="width: 100.0%; height: 100.0%;">ROBBERY</div>`)[0];
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            circle_marker_291750501014400aa5c337cc350752ec.bindPopup(popup_d56ff240b86742958d83259c156e81e1)
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            var circle_marker_b82d039c3f0f4a95a2d592e4f29bec32 = L.circleMarker(
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}
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            var popup_5bd95938eabe4775bca0254d0e349cb6 = L.popup({maxWidth: '100%'
            
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                var html_19b6616bd78b42f382e95988cda9bbe3 = $(`<div id="html_19b6616bd78b42f382e95988cda9bbe3" style="width: 100.0%; height: 100.0%;">OTHER OFFENSES</div>`)[0];
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            circle_marker_b82d039c3f0f4a95a2d592e4f29bec32.bindPopup(popup_5bd95938eabe4775bca0254d0e349cb6)
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            var circle_marker_ea351065ba4d459683497b65a4078071 = L.circleMarker(
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}
                )
                .addTo(map_56f7cd0eb11c45cfa51c1e6f0e899779);
            
    
            var popup_93faad6aa20348e49f717e3a1cad240c = L.popup({maxWidth: '100%'
            
            });

            
                var html_67a8b485701a443b84d4fd0cd0574abc = $(`<div id="html_67a8b485701a443b84d4fd0cd0574abc" style="width: 100.0%; height: 100.0%;">NON-CRIMINAL</div>`)[0];
                popup_93faad6aa20348e49f717e3a1cad240c.setContent(html_67a8b485701a443b84d4fd0cd0574abc);
            

            circle_marker_ea351065ba4d459683497b65a4078071.bindPopup(popup_93faad6aa20348e49f717e3a1cad240c)
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            var circle_marker_6289804bfc30473e9124423046e9e510 = L.circleMarker(
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                .addTo(map_56f7cd0eb11c45cfa51c1e6f0e899779);
            
    
            var popup_55b6c76ab12f451ab6835bba40e5e60b = L.popup({maxWidth: '100%'
            
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                var html_bbdd0461f5e1478cb631bfbfc17cdbe5 = $(`<div id="html_bbdd0461f5e1478cb631bfbfc17cdbe5" style="width: 100.0%; height: 100.0%;">BURGLARY</div>`)[0];
                popup_55b6c76ab12f451ab6835bba40e5e60b.setContent(html_bbdd0461f5e1478cb631bfbfc17cdbe5);
            

            circle_marker_6289804bfc30473e9124423046e9e510.bindPopup(popup_55b6c76ab12f451ab6835bba40e5e60b)
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            var circle_marker_792f21f1abbd40549be95bc616f77704 = L.circleMarker(
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            var popup_fb9e778831904abc8a0c8520a824056f = L.popup({maxWidth: '100%'
            
            });

            
                var html_c3f8bebd674e4abfafd26c1207f0f611 = $(`<div id="html_c3f8bebd674e4abfafd26c1207f0f611" style="width: 100.0%; height: 100.0%;">LARCENY/THEFT</div>`)[0];
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            circle_marker_792f21f1abbd40549be95bc616f77704.bindPopup(popup_fb9e778831904abc8a0c8520a824056f)
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            var circle_marker_d829bee27b1c477789dfedc96c0abc75 = L.circleMarker(
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                .addTo(map_56f7cd0eb11c45cfa51c1e6f0e899779);
            
    
            var popup_3c84a4ad77a74da0b7b418917ca7597f = L.popup({maxWidth: '100%'
            
            });

            
                var html_d58aecbc0fdb458d93fd50fe431dc89e = $(`<div id="html_d58aecbc0fdb458d93fd50fe431dc89e" style="width: 100.0%; height: 100.0%;">LARCENY/THEFT</div>`)[0];
                popup_3c84a4ad77a74da0b7b418917ca7597f.setContent(html_d58aecbc0fdb458d93fd50fe431dc89e);
            

            circle_marker_d829bee27b1c477789dfedc96c0abc75.bindPopup(popup_3c84a4ad77a74da0b7b418917ca7597f)
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            ],
            "text/plain": [
              "<folium.folium.Map at 0x7f6ef1a0a940>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 100
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "9Eo6IuMR1B_X",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        ""
      ],
      "execution_count": null,
      "outputs": []
    }
  ]
}