Visualise the population of Switzerland using Python and bokeh

As some sort of simple introduction to displaying data on a map we can visualize the population of Switzerland. For this we need data on population per canton and the map to plot the data on. Fortunatley both are freely available.

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<h3 id="Getting-the-map">Getting the map</h3>
Shapefiles with the data on cantons and much more can be downloaded from <a href="https://shop.swisstopo.admin.ch/en/products/landscape/boundaries3D">https://shop.swisstopo.admin.ch/en/products/landscape/boundaries3D</a>
<h3 id="Population-data">Population data</h3>
The population data is available in the official report at:
<a href="https://www.bfs.admin.ch/bfs/en/home/statistics/population.gnpdetail.2017-0586.html">https://www.bfs.admin.ch/bfs/en/home/statistics/population.gnpdetail.2017-0586.html</a> unfortunatley only as a pdf. But it is relativly quick o copy-paste it to a csv file.
<h2 id="Imports">Imports</h2>
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<pre><span class="c1">#basic infrastructure</span>
<span class="kn">import</span> <span class="nn">os</span>
<span class="kn">import</span> <span class="nn">numpy</span> <span class="k">as</span> <span class="nn">np</span>
<span class="kn">import</span> <span class="nn">pandas</span> <span class="k">as</span> <span class="nn">pd</span>

<span class="c1">#plotting</span>
<span class="kn">from</span> <span class="nn">bokeh.models</span> <span class="k">import</span> <span class="n">ColumnDataSource</span><span class="p">,</span> <span class="n">HoverTool</span><span class="p">,</span> <span class="n">LinearColorMapper</span><span class="p">,</span> <span class="n">ColorBar</span><span class="p">,</span> <span class="n">AdaptiveTicker</span>
<span class="kn">from</span> <span class="nn">bokeh.io</span> <span class="k">import</span> <span class="n">show</span><span class="p">,</span> <span class="n">output_file</span><span class="p">,</span> <span class="n">output_notebook</span>
<span class="kn">from</span> <span class="nn">bokeh.plotting</span> <span class="k">import</span> <span class="n">figure</span><span class="p">,</span> <span class="n">save</span>
<span class="kn">from</span> <span class="nn">bokeh</span> <span class="k">import</span> <span class="n">palettes</span>

<span class="c1">#colormaps for bokeh</span>
<span class="kn">import</span> <span class="nn">colorcet</span> <span class="k">as</span> <span class="nn">cc</span>

<span class="c1">#read shapefiles</span>
<span class="kn">import</span> <span class="nn">shapefile</span>

<span class="c1">#Data path</span>
<span class="n">path</span> <span class="o">=</span> <span class="s1">'/Users/erikfrojdh/Dropbox/Data/'</span>
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<h2 id="Reading-population-data">Reading population data</h2>
After manually copy pasting the data into a text file we can read it using pandas and read_csv.

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<pre><span class="c1">#Reading data</span>
<span class="n">df</span> <span class="o">=</span> <span class="n">pd</span><span class="o">.</span><span class="n">read_csv</span><span class="p">(</span><span class="n">os</span><span class="o">.</span><span class="n">path</span><span class="o">.</span><span class="n">join</span><span class="p">(</span><span class="n">path</span><span class="p">,</span><span class="s1">'bevolkerung.csv'</span><span class="p">),</span> 
                 <span class="n">index_col</span><span class="o">=</span><span class="mi">0</span><span class="p">,</span><span class="n">skipinitialspace</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>

<span class="c1">#Create a dict to look up values</span>
<span class="n">pop</span> <span class="o">=</span> <span class="n">df</span><span class="o">.</span><span class="n">to_dict</span><span class="p">(</span><span class="s1">'index'</span><span class="p">)</span>

<span class="c1">#display sorted values</span>
<span class="n">df</span><span class="o">.</span><span class="n">sort_values</span><span class="p">(</span><span class="s1">'Total'</span><span class="p">,</span> <span class="n">ascending</span><span class="o">=</span><span class="kc">False</span><span class="p">)</span>
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<table class="dataframe" border="1">
<thead>
<tr style="text-align: right;">
<th></th>
<th>Total</th>
<th>Mann</th>
<th>Frau</th>
<th>Schweizer</th>
<th>Ausländer</th>
</tr>
<tr>
<th>Kanton</th>
<th></th>
<th></th>
<th></th>
<th></th>
<th></th>
</tr>
</thead>
<tbody>
<tr>
<th>Zürich</th>
<td>1487969</td>
<td>739814</td>
<td>748155</td>
<td>1092631</td>
<td>395338</td>
</tr>
<tr>
<th>Bern</th>
<td>1026513</td>
<td>503789</td>
<td>522724</td>
<td>861614</td>
<td>164899</td>
</tr>
<tr>
<th>Vaud</th>
<td>784822</td>
<td>385389</td>
<td>399433</td>
<td>520957</td>
<td>263865</td>
</tr>
<tr>
<th>Aargau</th>
<td>663462</td>
<td>333364</td>
<td>330098</td>
<td>499712</td>
<td>163750</td>
</tr>
<tr>
<th>St. Gallen</th>
<td>502552</td>
<td>251526</td>
<td>251026</td>
<td>382829</td>
<td>119723</td>
</tr>
<tr>
<th>Genève</th>
<td>489524</td>
<td>237112</td>
<td>252412</td>
<td>292641</td>
<td>196883</td>
</tr>
<tr>
<th>Luzern</th>
<td>403397</td>
<td>200897</td>
<td>202500</td>
<td>329264</td>
<td>74133</td>
</tr>
<tr>
<th>Ticino</th>
<td>354375</td>
<td>172877</td>
<td>181498</td>
<td>254828</td>
<td>99547</td>
</tr>
<tr>
<th>Valais</th>
<td>339176</td>
<td>168072</td>
<td>171104</td>
<td>260444</td>
<td>78732</td>
</tr>
<tr>
<th>Fribourg</th>
<td>311914</td>
<td>156334</td>
<td>155580</td>
<td>242087</td>
<td>69827</td>
</tr>
<tr>
<th>Basel-Landschaft</th>
<td>285624</td>
<td>140142</td>
<td>145482</td>
<td>221990</td>
<td>63634</td>
</tr>
<tr>
<th>Thurgau</th>
<td>270709</td>
<td>136199</td>
<td>134510</td>
<td>204378</td>
<td>66331</td>
</tr>
<tr>
<th>Solothurn</th>
<td>269441</td>
<td>134300</td>
<td>135141</td>
<td>210240</td>
<td>59201</td>
</tr>
<tr>
<th>Graubünden</th>
<td>197550</td>
<td>98853</td>
<td>98697</td>
<td>160932</td>
<td>36618</td>
</tr>
<tr>
<th>Basel-Stadt</th>
<td>193070</td>
<td>93212</td>
<td>99858</td>
<td>124026</td>
<td>69044</td>
</tr>
<tr>
<th>Neuchâtel</th>
<td>178567</td>
<td>87312</td>
<td>91255</td>
<td>132878</td>
<td>45689</td>
</tr>
<tr>
<th>Schwyz</th>
<td>155863</td>
<td>79852</td>
<td>76011</td>
<td>123597</td>
<td>32266</td>
</tr>
<tr>
<th>Zug</th>
<td>123948</td>
<td>62684</td>
<td>61264</td>
<td>89809</td>
<td>34139</td>
</tr>
<tr>
<th>Schaffhausen</th>
<td>80769</td>
<td>40020</td>
<td>40749</td>
<td>59889</td>
<td>20880</td>
</tr>
<tr>
<th>Jura</th>
<td>73122</td>
<td>36158</td>
<td>36964</td>
<td>62471</td>
<td>10651</td>
</tr>
<tr>
<th>Appenzell Ausserrhoden</th>
<td>54954</td>
<td>27778</td>
<td>27176</td>
<td>46044</td>
<td>8910</td>
</tr>
<tr>
<th>Nidwalden</th>
<td>42556</td>
<td>21795</td>
<td>20761</td>
<td>36521</td>
<td>6035</td>
</tr>
<tr>
<th>Glarus</th>
<td>40147</td>
<td>20329</td>
<td>19818</td>
<td>30650</td>
<td>9497</td>
</tr>
<tr>
<th>Obwalden</th>
<td>37378</td>
<td>18965</td>
<td>18413</td>
<td>31892</td>
<td>5486</td>
</tr>
<tr>
<th>Uri</th>
<td>36145</td>
<td>18427</td>
<td>17718</td>
<td>31850</td>
<td>4295</td>
</tr>
<tr>
<th>Appenzell Innerrhoden</th>
<td>16003</td>
<td>8237</td>
<td>7766</td>
<td>14230</td>
<td>1773</td>
</tr>
</tbody>
</table>
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<h2 id="Reading-shape-data">Reading shape data</h2>
To read the shapefile we can use the <strong><a href="https://pypi.python.org/pypi/pyshp/1.2.12">shapefile</a></strong> package. Each canton is stored with a record and a shape. Using iterShapeRecords we can iterate over them to extract the name and the points for the shape.

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<pre><span class="c1">#assuming the data was exctracted to path</span>
<span class="n">data_pathname</span> <span class="o">=</span> <span class="n">os</span><span class="o">.</span><span class="n">path</span><span class="o">.</span><span class="n">join</span><span class="p">(</span><span class="n">path</span><span class="p">,</span> 
                             <span class="s1">'BOUNDARIES_2017/DATEN/swissBOUNDARIES3D/'</span>\
                             <span class="s1">'SHAPEFILE_LV95_LN02/swissBOUNDARIES3D_1_3_TLM_KANTONSGEBIET.shp'</span><span class="p">)</span>

<span class="n">data</span> <span class="o">=</span> <span class="n">shapefile</span><span class="o">.</span><span class="n">Reader</span><span class="p">(</span><span class="n">data_pathname</span><span class="p">)</span>

<span class="c1">#lists to hold results</span>
<span class="n">x</span> <span class="o">=</span> <span class="p">[]</span>
<span class="n">y</span> <span class="o">=</span> <span class="p">[]</span>
<span class="n">canton_names</span> <span class="o">=</span> <span class="p">[]</span>
<span class="n">population</span> <span class="o">=</span> <span class="p">[]</span>

<span class="c1">#iterate over records and shapes</span>
<span class="k">for</span> <span class="n">sr</span> <span class="ow">in</span> <span class="n">data</span><span class="o">.</span><span class="n">iterShapeRecords</span><span class="p">():</span> 
    <span class="c1">#The names sometimes include special characters </span>
    <span class="c1">#in this case they are returned as byte strings instead</span>
    <span class="c1">#of strings, so before adding we try to decode</span>
    <span class="k">try</span><span class="p">:</span>
        <span class="n">name</span> <span class="o">=</span> <span class="n">sr</span><span class="o">.</span><span class="n">record</span><span class="p">[</span><span class="mi">18</span><span class="p">]</span><span class="o">.</span><span class="n">decode</span><span class="p">(</span><span class="s1">'cp1252'</span><span class="p">)</span>
    <span class="k">except</span> <span class="ne">AttributeError</span><span class="p">:</span>
        <span class="n">name</span> <span class="o">=</span> <span class="n">sr</span><span class="o">.</span><span class="n">record</span><span class="p">[</span><span class="mi">18</span><span class="p">]</span>
        
    <span class="c1">#Each canton can contain multiple closed loops </span>
    <span class="c1">#In order to plot we first need to extract them</span>
    <span class="c1">#To get the right color scale we also need one to </span>
    <span class="c1">#duplicate the population note for the canton</span>
    <span class="k">for</span> <span class="n">i</span><span class="p">,</span> <span class="n">start</span> <span class="ow">in</span> <span class="nb">enumerate</span><span class="p">(</span><span class="n">sr</span><span class="o">.</span><span class="n">shape</span><span class="o">.</span><span class="n">parts</span><span class="p">):</span>
        <span class="k">try</span><span class="p">:</span>
            <span class="n">stop</span> <span class="o">=</span> <span class="n">sr</span><span class="o">.</span><span class="n">shape</span><span class="o">.</span><span class="n">parts</span><span class="p">[</span><span class="n">i</span><span class="o">+</span><span class="mi">1</span><span class="p">]</span>
        <span class="k">except</span> <span class="ne">IndexError</span><span class="p">:</span>
            <span class="n">stop</span> <span class="o">=</span> <span class="nb">len</span><span class="p">(</span><span class="n">sr</span><span class="o">.</span><span class="n">shape</span><span class="o">.</span><span class="n">points</span><span class="p">)</span>
        <span class="c1">#append x,y and lookup population</span>
        <span class="n">x</span><span class="o">.</span><span class="n">append</span><span class="p">(</span> <span class="p">[</span><span class="n">p</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span> <span class="k">for</span> <span class="n">p</span> <span class="ow">in</span> <span class="n">sr</span><span class="o">.</span><span class="n">shape</span><span class="o">.</span><span class="n">points</span><span class="p">[</span><span class="n">start</span><span class="p">:</span><span class="n">stop</span><span class="p">]]</span> <span class="p">)</span>
        <span class="n">y</span><span class="o">.</span><span class="n">append</span><span class="p">(</span> <span class="p">[</span><span class="n">p</span><span class="p">[</span><span class="mi">1</span><span class="p">]</span> <span class="k">for</span> <span class="n">p</span> <span class="ow">in</span> <span class="n">sr</span><span class="o">.</span><span class="n">shape</span><span class="o">.</span><span class="n">points</span><span class="p">[</span><span class="n">start</span><span class="p">:</span><span class="n">stop</span><span class="p">]]</span> <span class="p">)</span>
        <span class="n">canton_names</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">name</span><span class="p">)</span>
        <span class="n">population</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">pop</span><span class="p">[</span><span class="n">name</span><span class="p">][</span><span class="s1">'Total'</span><span class="p">])</span>
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From the data we can now create a ColumnDataSource which will be used to create the patches. Then we set up a color_mapper to translate the population into colors. Since the colormaps included in bokeh supports relatively few numbers we use colorcet to set up.

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<pre><span class="c1">#data source</span>
<span class="n">source</span> <span class="o">=</span> <span class="n">ColumnDataSource</span><span class="p">(</span><span class="n">data</span><span class="o">=</span><span class="nb">dict</span><span class="p">(</span>
    <span class="n">x</span><span class="o">=</span><span class="n">x</span><span class="p">,</span> <span class="n">y</span><span class="o">=</span><span class="n">y</span><span class="p">,</span>
    <span class="n">name</span><span class="o">=</span><span class="n">canton_names</span><span class="p">,</span>
    <span class="n">population</span> <span class="o">=</span> <span class="n">population</span>
<span class="p">))</span>

<span class="c1">#colormap from colorcet, between 0 and the maximum population</span>
<span class="n">color_mapper</span> <span class="o">=</span> <span class="n">LinearColorMapper</span><span class="p">(</span>
    <span class="n">palette</span><span class="o">=</span><span class="n">cc</span><span class="o">.</span><span class="n">blues</span><span class="p">,</span>
    <span class="n">low</span> <span class="o">=</span> <span class="mi">0</span><span class="p">,</span>
    <span class="n">high</span> <span class="o">=</span> <span class="n">df</span><span class="o">.</span><span class="n">Total</span><span class="o">.</span><span class="n">max</span><span class="p">()</span>
<span class="p">)</span>

<span class="c1">#tools visible in the figure</span>
<span class="n">tools</span> <span class="o">=</span> <span class="s2">"pan,wheel_zoom,reset,hover,save"</span>
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<pre><span class="n">fig</span> <span class="o">=</span> <span class="n">figure</span><span class="p">(</span>
    <span class="n">title</span><span class="o">=</span><span class="s2">"Population per canton"</span><span class="p">,</span> 
    <span class="n">tools</span><span class="o">=</span><span class="n">tools</span><span class="p">,</span>
    <span class="n">x_axis_location</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> 
    <span class="n">y_axis_location</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span>
    <span class="n">match_aspect</span><span class="o">=</span><span class="kc">True</span>
<span class="p">)</span>
<span class="n">fig</span><span class="o">.</span><span class="n">grid</span><span class="o">.</span><span class="n">grid_line_color</span> <span class="o">=</span> <span class="kc">None</span>
<span class="n">fig</span><span class="o">.</span><span class="n">patches</span><span class="p">(</span><span class="s1">'x'</span><span class="p">,</span> <span class="s1">'y'</span><span class="p">,</span> <span class="n">source</span><span class="o">=</span><span class="n">source</span><span class="p">,</span>
          <span class="n">fill_color</span><span class="o">=</span><span class="p">{</span><span class="s1">'field'</span><span class="p">:</span> <span class="s1">'population'</span><span class="p">,</span><span class="s1">'transform'</span><span class="p">:</span> <span class="n">color_mapper</span><span class="p">},</span>
          <span class="n">fill_alpha</span><span class="o">=</span><span class="mf">0.8</span><span class="p">,</span> <span class="n">line_color</span><span class="o">=</span><span class="s2">"black"</span><span class="p">,</span> <span class="n">line_width</span><span class="o">=</span><span class="mf">0.3</span><span class="p">)</span>

<span class="c1">#setup tooltip</span>
<span class="n">hover</span> <span class="o">=</span> <span class="n">fig</span><span class="o">.</span><span class="n">select_one</span><span class="p">(</span><span class="n">HoverTool</span><span class="p">)</span>
<span class="n">hover</span><span class="o">.</span><span class="n">point_policy</span> <span class="o">=</span> <span class="s2">"follow_mouse"</span>
<span class="n">hover</span><span class="o">.</span><span class="n">tooltips</span> <span class="o">=</span> <span class="p">[(</span><span class="s2">"Canton"</span><span class="p">,</span> <span class="s2">"@name"</span><span class="p">),(</span><span class="s2">"Population"</span><span class="p">,</span> <span class="s2">"@population"</span><span class="p">),</span>
                  <span class="p">(</span><span class="s2">"(E, N)"</span><span class="p">,</span> <span class="s2">"($x, $y)"</span><span class="p">)]</span>

<span class="n">output_file</span><span class="p">(</span><span class="s1">'test.html'</span><span class="p">)</span>
<span class="n">show</span><span class="p">(</span><span class="n">fig</span><span class="p">)</span>
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<h2 id="Matplotlib-rendering">Matplotlib rendering</h2>
Depending on your preferences or output format sometimes matplotlib renders nicer images.

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<pre><span class="kn">import</span> <span class="nn">matplotlib</span> <span class="k">as</span> <span class="nn">mpl</span>
<span class="kn">import</span> <span class="nn">matplotlib.pyplot</span> <span class="k">as</span> <span class="nn">plt</span>
<span class="kn">from</span> <span class="nn">matplotlib.patches</span> <span class="k">import</span> <span class="n">Polygon</span><span class="p">,</span> <span class="n">Rectangle</span>
<span class="kn">from</span> <span class="nn">matplotlib.collections</span> <span class="k">import</span> <span class="n">PatchCollection</span>
<span class="kn">import</span> <span class="nn">seaborn</span> <span class="k">as</span> <span class="nn">sns</span>
<span class="n">sns</span><span class="o">.</span><span class="n">set</span><span class="p">()</span>
<span class="n">sns</span><span class="o">.</span><span class="n">set_style</span><span class="p">(</span><span class="s1">'white'</span><span class="p">)</span>
<span class="n">sns</span><span class="o">.</span><span class="n">set_context</span><span class="p">(</span><span class="s1">'talk'</span><span class="p">,</span> <span class="n">font_scale</span><span class="o">=</span><span class="mf">1.1</span><span class="p">)</span>

<span class="n">patches</span> <span class="o">=</span> <span class="p">[]</span>
<span class="k">for</span> <span class="n">xx</span><span class="p">,</span><span class="n">yy</span> <span class="ow">in</span> <span class="nb">zip</span><span class="p">(</span><span class="n">x</span><span class="p">,</span><span class="n">y</span><span class="p">):</span>
    <span class="n">xy</span> <span class="o">=</span> <span class="nb">list</span><span class="p">(</span><span class="nb">zip</span><span class="p">(</span><span class="n">xx</span><span class="p">,</span><span class="n">yy</span><span class="p">))</span>
    <span class="n">polygon</span> <span class="o">=</span> <span class="n">Polygon</span><span class="p">(</span><span class="n">xy</span><span class="p">,</span> <span class="kc">True</span><span class="p">)</span>
    <span class="n">patches</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">polygon</span><span class="p">)</span>
    
<span class="n">p</span> <span class="o">=</span> <span class="n">PatchCollection</span><span class="p">(</span><span class="n">patches</span><span class="p">,</span> <span class="n">cmap</span><span class="o">=</span><span class="s1">'Reds'</span><span class="p">,</span> <span class="n">alpha</span><span class="o">=</span><span class="mi">1</span><span class="p">,</span> 
                    <span class="n">linestyle</span> <span class="o">=</span> <span class="s1">'-'</span><span class="p">,</span> 
                    <span class="n">linewidth</span> <span class="o">=</span> <span class="mi">1</span><span class="p">,</span>
                    <span class="n">edgecolor</span> <span class="o">=</span> <span class="s1">'Black'</span><span class="p">)</span>
<span class="n">p</span><span class="o">.</span><span class="n">set_array</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">array</span><span class="p">(</span><span class="n">population</span><span class="p">))</span>
<span class="n">fig</span><span class="p">,</span> <span class="n">ax</span> <span class="o">=</span> <span class="n">plt</span><span class="o">.</span><span class="n">subplots</span><span class="p">(</span><span class="mi">1</span><span class="p">,</span> <span class="n">figsize</span> <span class="o">=</span> <span class="p">(</span><span class="mi">14</span><span class="p">,</span><span class="mi">7</span><span class="p">))</span>
<span class="n">ax</span><span class="o">.</span><span class="n">add_collection</span><span class="p">(</span><span class="n">p</span><span class="p">)</span>
<span class="c1"># ax.plot(xy)</span>
<span class="n">ax</span><span class="o">.</span><span class="n">autoscale_view</span><span class="p">()</span>
<span class="n">ax</span><span class="o">.</span><span class="n">set_aspect</span><span class="p">(</span><span class="s1">'equal'</span><span class="p">)</span>
<span class="n">ax</span><span class="o">.</span><span class="n">grid</span><span class="p">(</span><span class="kc">True</span><span class="p">)</span>
<span class="n">plt</span><span class="o">.</span><span class="n">show</span><span class="p">()</span>
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One thought on “Visualise the population of Switzerland using Python and bokeh

  1. Thank you very much for sharing. After a lot of searching, it was exactly what i was looking for !!!!. Have you ever consider to post this in stackoverflow.com? I think you should.

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