Prepare georeferenced data for artificial disease outbreak in Europe
====================================================================

In this notebook geospatial data from a shapefile is loaded, relevant
attributes extracte and

.. code:: ipython3

    %matplotlib inline
    import geopandas as gp
    import pandas as pd

The geospatial vector dataset shapefile was downloaded from open access
NaturalEarthData, which provides free vector and raster map data.

Download:
http://www.naturalearthdata.com/http//www.naturalearthdata.com/download/110m/cultural/ne_110m_admin_0_countries.zip

.. code:: ipython3

    shp = 'Shapefile/ne_110m_admin_0_countries.shp'
    geo_df = gp.GeoDataFrame.from_file(shp)
    geo_df.head(1)




.. raw:: html

    <div>
    <style scoped>
        .dataframe tbody tr th:only-of-type {
            vertical-align: middle;
        }
    
        .dataframe tbody tr th {
            vertical-align: top;
        }
    
        .dataframe thead th {
            text-align: right;
        }
    </style>
    <table border="1" class="dataframe">
      <thead>
        <tr style="text-align: right;">
          <th></th>
          <th>featurecla</th>
          <th>scalerank</th>
          <th>LABELRANK</th>
          <th>SOVEREIGNT</th>
          <th>SOV_A3</th>
          <th>ADM0_DIF</th>
          <th>LEVEL</th>
          <th>TYPE</th>
          <th>TLC</th>
          <th>ADMIN</th>
          <th>...</th>
          <th>FCLASS_TR</th>
          <th>FCLASS_ID</th>
          <th>FCLASS_PL</th>
          <th>FCLASS_GR</th>
          <th>FCLASS_IT</th>
          <th>FCLASS_NL</th>
          <th>FCLASS_SE</th>
          <th>FCLASS_BD</th>
          <th>FCLASS_UA</th>
          <th>geometry</th>
        </tr>
      </thead>
      <tbody>
        <tr>
          <th>0</th>
          <td>Admin-0 country</td>
          <td>1</td>
          <td>6</td>
          <td>Fiji</td>
          <td>FJI</td>
          <td>0</td>
          <td>2</td>
          <td>Sovereign country</td>
          <td>1</td>
          <td>Fiji</td>
          <td>...</td>
          <td>None</td>
          <td>None</td>
          <td>None</td>
          <td>None</td>
          <td>None</td>
          <td>None</td>
          <td>None</td>
          <td>None</td>
          <td>None</td>
          <td>MULTIPOLYGON (((180.00000 -16.06713, 180.00000...</td>
        </tr>
      </tbody>
    </table>
    <p>1 rows × 169 columns</p>
    </div>



Attributes in shapefile
'''''''''''''''''''''''

.. code:: ipython3

    geo_df.columns




.. parsed-literal::

    Index(['featurecla', 'scalerank', 'LABELRANK', 'SOVEREIGNT', 'SOV_A3',
           'ADM0_DIF', 'LEVEL', 'TYPE', 'TLC', 'ADMIN',
           ...
           'FCLASS_TR', 'FCLASS_ID', 'FCLASS_PL', 'FCLASS_GR', 'FCLASS_IT',
           'FCLASS_NL', 'FCLASS_SE', 'FCLASS_BD', 'FCLASS_UA', 'geometry'],
          dtype='object', length=169)



Take only European countries and exclude Russia
'''''''''''''''''''''''''''''''''''''''''''''''

.. code:: ipython3

    geo_df_EU = geo_df[geo_df["REGION_UN"] == "Europe"]
    
    geo_df_EU.set_index("ADMIN", inplace=True)
    geo_df_EU.drop('Russia', axis=0, inplace=True)
    geo_df_EU.reset_index(inplace=True)


.. parsed-literal::

    /home/eneko/.miniconda3/envs/cook/lib/python3.7/site-packages/pandas/core/frame.py:4913: SettingWithCopyWarning: 
    A value is trying to be set on a copy of a slice from a DataFrame
    
    See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
      errors=errors,


Retrieve relevant data
^^^^^^^^^^^^^^^^^^^^^^

.. code:: ipython3

    geo_df_EU = geo_df_EU[['geometry', 'POP_EST', 'ADMIN']]
    geo_df_EU.head()




.. raw:: html

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            text-align: right;
        }
    </style>
    <table border="1" class="dataframe">
      <thead>
        <tr style="text-align: right;">
          <th></th>
          <th>geometry</th>
          <th>POP_EST</th>
          <th>ADMIN</th>
        </tr>
      </thead>
      <tbody>
        <tr>
          <th>0</th>
          <td>MULTIPOLYGON (((15.14282 79.67431, 15.52255 80...</td>
          <td>5347896.0</td>
          <td>Norway</td>
        </tr>
        <tr>
          <th>1</th>
          <td>MULTIPOLYGON (((-51.65780 4.15623, -52.24934 3...</td>
          <td>67059887.0</td>
          <td>France</td>
        </tr>
        <tr>
          <th>2</th>
          <td>POLYGON ((11.02737 58.85615, 11.46827 59.43239...</td>
          <td>10285453.0</td>
          <td>Sweden</td>
        </tr>
        <tr>
          <th>3</th>
          <td>POLYGON ((28.17671 56.16913, 29.22951 55.91834...</td>
          <td>9466856.0</td>
          <td>Belarus</td>
        </tr>
        <tr>
          <th>4</th>
          <td>POLYGON ((31.78599 52.10168, 32.15944 52.06125...</td>
          <td>44385155.0</td>
          <td>Ukraine</td>
        </tr>
      </tbody>
    </table>
    </div>



Compute population density based on Population density the number of
people per unit of area,

.. code:: ipython3

    geo_df_EU['POP_DENSITY'] = geo_df_EU['POP_EST']/(geo_df_EU['geometry'].area)


.. parsed-literal::

    /home/eneko/.miniconda3/envs/cook/lib/python3.7/site-packages/ipykernel_launcher.py:1: UserWarning: Geometry is in a geographic CRS. Results from 'area' are likely incorrect. Use 'GeoSeries.to_crs()' to re-project geometries to a projected CRS before this operation.
    
      """Entry point for launching an IPython kernel.


Normalization of pop density into a contact rate between 10 and 100

.. code:: ipython3

    from sklearn import preprocessing
    min_max_scaler = preprocessing.MinMaxScaler(feature_range=(0, 1))
    x_scaled = min_max_scaler.fit_transform(geo_df_EU['POP_DENSITY'].values.reshape(-1, 1))[:,0]
    geo_df_EU['inf_rate'] = pd.Series(x_scaled)

.. code:: ipython3

    geo_df_EU.head()




.. raw:: html

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    </style>
    <table border="1" class="dataframe">
      <thead>
        <tr style="text-align: right;">
          <th></th>
          <th>geometry</th>
          <th>POP_EST</th>
          <th>ADMIN</th>
          <th>POP_DENSITY</th>
          <th>inf_rate</th>
        </tr>
      </thead>
      <tbody>
        <tr>
          <th>0</th>
          <td>MULTIPOLYGON (((15.14282 79.67431, 15.52255 80...</td>
          <td>5347896.0</td>
          <td>Norway</td>
          <td>59095.218795</td>
          <td>0.012681</td>
        </tr>
        <tr>
          <th>1</th>
          <td>MULTIPOLYGON (((-51.65780 4.15623, -52.24934 3...</td>
          <td>67059887.0</td>
          <td>France</td>
          <td>923490.631806</td>
          <td>0.276615</td>
        </tr>
        <tr>
          <th>2</th>
          <td>POLYGON ((11.02737 58.85615, 11.46827 59.43239...</td>
          <td>10285453.0</td>
          <td>Sweden</td>
          <td>129464.357267</td>
          <td>0.034167</td>
        </tr>
        <tr>
          <th>3</th>
          <td>POLYGON ((28.17671 56.16913, 29.22951 55.91834...</td>
          <td>9466856.0</td>
          <td>Belarus</td>
          <td>334504.027829</td>
          <td>0.096774</td>
        </tr>
        <tr>
          <th>4</th>
          <td>POLYGON ((31.78599 52.10168, 32.15944 52.06125...</td>
          <td>44385155.0</td>
          <td>Ukraine</td>
          <td>628756.876391</td>
          <td>0.186621</td>
        </tr>
      </tbody>
    </table>
    </div>



.. code:: ipython3

    geo_df_EU.plot('inf_rate');



.. image:: Prepare_Data_files/Prepare_Data_15_0.png


Give columns easy understandable names and remove unncessary columns

.. code:: ipython3

    geo_df_EU.rename(columns={'ADMIN': 'country', 'POP_EST': 'population'},inplace=True )
    geo_df_EU.drop(['POP_DENSITY'], axis=1, inplace=True)

Save results into new shapefle

.. code:: ipython3

    geo_df_EU.to_file('geo_df_EU.shp', driver="ESRI Shapefile")

.. code:: ipython3

    geo_df_EU




.. raw:: html

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    <style scoped>
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        }
    
        .dataframe tbody tr th {
            vertical-align: top;
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            text-align: right;
        }
    </style>
    <table border="1" class="dataframe">
      <thead>
        <tr style="text-align: right;">
          <th></th>
          <th>geometry</th>
          <th>population</th>
          <th>country</th>
          <th>inf_rate</th>
        </tr>
      </thead>
      <tbody>
        <tr>
          <th>0</th>
          <td>MULTIPOLYGON (((15.14282 79.67431, 15.52255 80...</td>
          <td>5347896.0</td>
          <td>Norway</td>
          <td>0.012681</td>
        </tr>
        <tr>
          <th>1</th>
          <td>MULTIPOLYGON (((-51.65780 4.15623, -52.24934 3...</td>
          <td>67059887.0</td>
          <td>France</td>
          <td>0.276615</td>
        </tr>
        <tr>
          <th>2</th>
          <td>POLYGON ((11.02737 58.85615, 11.46827 59.43239...</td>
          <td>10285453.0</td>
          <td>Sweden</td>
          <td>0.034167</td>
        </tr>
        <tr>
          <th>3</th>
          <td>POLYGON ((28.17671 56.16913, 29.22951 55.91834...</td>
          <td>9466856.0</td>
          <td>Belarus</td>
          <td>0.096774</td>
        </tr>
        <tr>
          <th>4</th>
          <td>POLYGON ((31.78599 52.10168, 32.15944 52.06125...</td>
          <td>44385155.0</td>
          <td>Ukraine</td>
          <td>0.186621</td>
        </tr>
        <tr>
          <th>5</th>
          <td>POLYGON ((23.48413 53.91250, 23.52754 53.47012...</td>
          <td>37970874.0</td>
          <td>Poland</td>
          <td>0.279088</td>
        </tr>
        <tr>
          <th>6</th>
          <td>POLYGON ((16.97967 48.12350, 16.90375 47.71487...</td>
          <td>8877067.0</td>
          <td>Austria</td>
          <td>0.260907</td>
        </tr>
        <tr>
          <th>7</th>
          <td>POLYGON ((22.08561 48.42226, 22.64082 48.15024...</td>
          <td>9769949.0</td>
          <td>Hungary</td>
          <td>0.266325</td>
        </tr>
        <tr>
          <th>8</th>
          <td>POLYGON ((26.61934 48.22073, 26.85782 48.36821...</td>
          <td>2657637.0</td>
          <td>Moldova</td>
          <td>0.206089</td>
        </tr>
        <tr>
          <th>9</th>
          <td>POLYGON ((28.23355 45.48828, 28.67978 45.30403...</td>
          <td>19356544.0</td>
          <td>Romania</td>
          <td>0.208615</td>
        </tr>
        <tr>
          <th>10</th>
          <td>POLYGON ((26.49433 55.61511, 26.58828 55.16718...</td>
          <td>2786844.0</td>
          <td>Lithuania</td>
          <td>0.088953</td>
        </tr>
        <tr>
          <th>11</th>
          <td>POLYGON ((27.28818 57.47453, 27.77002 57.24426...</td>
          <td>1912789.0</td>
          <td>Latvia</td>
          <td>0.056778</td>
        </tr>
        <tr>
          <th>12</th>
          <td>POLYGON ((27.98113 59.47537, 27.98112 59.47537...</td>
          <td>1326590.0</td>
          <td>Estonia</td>
          <td>0.053291</td>
        </tr>
        <tr>
          <th>13</th>
          <td>POLYGON ((14.11969 53.75703, 14.35332 53.24817...</td>
          <td>83132799.0</td>
          <td>Germany</td>
          <td>0.547376</td>
        </tr>
        <tr>
          <th>14</th>
          <td>POLYGON ((22.65715 44.23492, 22.94483 43.82379...</td>
          <td>6975761.0</td>
          <td>Bulgaria</td>
          <td>0.170384</td>
        </tr>
        <tr>
          <th>15</th>
          <td>MULTIPOLYGON (((26.29000 35.29999, 26.16500 35...</td>
          <td>10716322.0</td>
          <td>Greece</td>
          <td>0.232713</td>
        </tr>
        <tr>
          <th>16</th>
          <td>POLYGON ((21.02004 40.84273, 20.99999 40.58000...</td>
          <td>2854191.0</td>
          <td>Albania</td>
          <td>0.268249</td>
        </tr>
        <tr>
          <th>17</th>
          <td>POLYGON ((16.56481 46.50375, 16.88252 46.38063...</td>
          <td>4067500.0</td>
          <td>Croatia</td>
          <td>0.183671</td>
        </tr>
        <tr>
          <th>18</th>
          <td>POLYGON ((9.59423 47.52506, 9.63293 47.34760, ...</td>
          <td>8574832.0</td>
          <td>Switzerland</td>
          <td>0.475913</td>
        </tr>
        <tr>
          <th>19</th>
          <td>POLYGON ((6.04307 50.12805, 6.24275 49.90223, ...</td>
          <td>619896.0</td>
          <td>Luxembourg</td>
          <td>0.622395</td>
        </tr>
        <tr>
          <th>20</th>
          <td>POLYGON ((6.15666 50.80372, 6.04307 50.12805, ...</td>
          <td>11484055.0</td>
          <td>Belgium</td>
          <td>0.910184</td>
        </tr>
        <tr>
          <th>21</th>
          <td>POLYGON ((6.90514 53.48216, 7.09205 53.14404, ...</td>
          <td>17332850.0</td>
          <td>Netherlands</td>
          <td>1.000000</td>
        </tr>
        <tr>
          <th>22</th>
          <td>POLYGON ((-9.03482 41.88057, -8.67195 42.13469...</td>
          <td>10269417.0</td>
          <td>Portugal</td>
          <td>0.314522</td>
        </tr>
        <tr>
          <th>23</th>
          <td>POLYGON ((-7.45373 37.09779, -7.53711 37.42890...</td>
          <td>47076781.0</td>
          <td>Spain</td>
          <td>0.264485</td>
        </tr>
        <tr>
          <th>24</th>
          <td>POLYGON ((-6.19788 53.86757, -6.03299 53.15316...</td>
          <td>4941444.0</td>
          <td>Ireland</td>
          <td>0.186591</td>
        </tr>
        <tr>
          <th>25</th>
          <td>MULTIPOLYGON (((10.44270 46.89355, 11.04856 46...</td>
          <td>60297396.0</td>
          <td>Italy</td>
          <td>0.525439</td>
        </tr>
        <tr>
          <th>26</th>
          <td>MULTIPOLYGON (((9.92191 54.98310, 9.28205 54.8...</td>
          <td>5818553.0</td>
          <td>Denmark</td>
          <td>0.282656</td>
        </tr>
        <tr>
          <th>27</th>
          <td>MULTIPOLYGON (((-6.19788 53.86757, -6.95373 54...</td>
          <td>66834405.0</td>
          <td>United Kingdom</td>
          <td>0.591287</td>
        </tr>
        <tr>
          <th>28</th>
          <td>POLYGON ((-14.50870 66.45589, -14.73964 65.808...</td>
          <td>361313.0</td>
          <td>Iceland</td>
          <td>0.000000</td>
        </tr>
        <tr>
          <th>29</th>
          <td>POLYGON ((13.80648 46.50931, 14.63247 46.43182...</td>
          <td>2087946.0</td>
          <td>Slovenia</td>
          <td>0.281129</td>
        </tr>
        <tr>
          <th>30</th>
          <td>POLYGON ((28.59193 69.06478, 28.44594 68.36461...</td>
          <td>5520314.0</td>
          <td>Finland</td>
          <td>0.021063</td>
        </tr>
        <tr>
          <th>31</th>
          <td>POLYGON ((22.55814 49.08574, 22.28084 48.82539...</td>
          <td>5454073.0</td>
          <td>Slovakia</td>
          <td>0.284090</td>
        </tr>
        <tr>
          <th>32</th>
          <td>POLYGON ((15.01700 51.10667, 15.49097 50.78473...</td>
          <td>10669709.0</td>
          <td>Czechia</td>
          <td>0.316024</td>
        </tr>
        <tr>
          <th>33</th>
          <td>POLYGON ((18.56000 42.65000, 17.67492 43.02856...</td>
          <td>3301000.0</td>
          <td>Bosnia and Herzegovina</td>
          <td>0.171569</td>
        </tr>
        <tr>
          <th>34</th>
          <td>POLYGON ((22.38053 42.32026, 22.88137 41.99930...</td>
          <td>2083459.0</td>
          <td>North Macedonia</td>
          <td>0.229644</td>
        </tr>
        <tr>
          <th>35</th>
          <td>POLYGON ((18.82982 45.90887, 18.82984 45.90888...</td>
          <td>6944975.0</td>
          <td>Republic of Serbia</td>
          <td>0.241080</td>
        </tr>
        <tr>
          <th>36</th>
          <td>POLYGON ((20.07070 42.58863, 19.80161 42.50009...</td>
          <td>622137.0</td>
          <td>Montenegro</td>
          <td>0.123049</td>
        </tr>
        <tr>
          <th>37</th>
          <td>POLYGON ((20.59025 41.85541, 20.52295 42.21787...</td>
          <td>1794248.0</td>
          <td>Kosovo</td>
          <td>0.439454</td>
        </tr>
      </tbody>
    </table>
    </div>