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<div class="section" id="static-maps">
<h1>Static maps<a class="headerlink" href="#static-maps" title="Permalink to this headline">¶</a></h1>
<p>We have already seen during the previous lessons quite many examples how to create static maps using Geopandas.</p>
<p>Thus, we won’t spend too much time repeating making such maps but let’s create a one with more layers on it than just one
which kind we have mostly done this far.</p>
<p>Let’s create a static accessibility map with roads and metro line on it.</p>
<p>First, we need to read the data.</p>
<div class="code python highlight-default"><div class="highlight"><pre><span></span><span class="kn">import</span> <span class="nn">geopandas</span> <span class="k">as</span> <span class="nn">gpd</span>
<span class="kn">import</span> <span class="nn">matplotlib.pyplot</span> <span class="k">as</span> <span class="nn">plt</span>
<span class="c1"># Filepaths</span>
<span class="n">grid_fp</span> <span class="o">=</span> <span class="s2">r"/home/geo/data/TravelTimes_to_5975375_RailwayStation.shp"</span>
<span class="n">roads_fp</span> <span class="o">=</span> <span class="s2">r"/home/geo/data/roads.shp"</span>
<span class="n">metro_fp</span> <span class="o">=</span> <span class="s2">r"/home/geo/data/metro.shp"</span>
<span class="c1"># Read files</span>
<span class="n">grid</span> <span class="o">=</span> <span class="n">gpd</span><span class="o">.</span><span class="n">read_file</span><span class="p">(</span><span class="n">grid_fp</span><span class="p">)</span>
<span class="n">roads</span> <span class="o">=</span> <span class="n">gpd</span><span class="o">.</span><span class="n">read_file</span><span class="p">(</span><span class="n">roads_fp</span><span class="p">)</span>
<span class="n">metro</span> <span class="o">=</span> <span class="n">gpd</span><span class="o">.</span><span class="n">read_file</span><span class="p">(</span><span class="n">metro_fp</span><span class="p">)</span>
</pre></div>
</div>
<p>Then, we need to be sure that the files are in the same coordinate system. Let’s use the crs of our travel time grid.</p>
<div class="code python highlight-default"><div class="highlight"><pre><span></span><span class="c1"># Get the CRS of the grid</span>
<span class="n">gridCRS</span> <span class="o">=</span> <span class="n">grid</span><span class="o">.</span><span class="n">crs</span>
<span class="c1"># Reproject geometries using the crs of travel time grid</span>
<span class="n">roads</span><span class="p">[</span><span class="s1">'geometry'</span><span class="p">]</span> <span class="o">=</span> <span class="n">roads</span><span class="p">[</span><span class="s1">'geometry'</span><span class="p">]</span><span class="o">.</span><span class="n">to_crs</span><span class="p">(</span><span class="n">crs</span><span class="o">=</span><span class="n">gridCRS</span><span class="p">)</span>
<span class="n">metro</span><span class="p">[</span><span class="s1">'geometry'</span><span class="p">]</span> <span class="o">=</span> <span class="n">metro</span><span class="p">[</span><span class="s1">'geometry'</span><span class="p">]</span><span class="o">.</span><span class="n">to_crs</span><span class="p">(</span><span class="n">crs</span><span class="o">=</span><span class="n">gridCRS</span><span class="p">)</span>
</pre></div>
</div>
<p>Finally we can make a visualization using the <code class="docutils literal"><span class="pre">.plot()</span></code> -function in Geopandas.</p>
<div class="code python highlight-default"><div class="highlight"><pre><span></span><span class="c1"># Visualize the travel times into 9 classes using "Quantiles" classification scheme</span>
<span class="c1"># Add also a little bit of transparency with `alpha` parameter</span>
<span class="c1"># (ranges from 0 to 1 where 0 is fully transparent and 1 has no transparency)</span>
<span class="n">my_map</span> <span class="o">=</span> <span class="n">grid</span><span class="o">.</span><span class="n">plot</span><span class="p">(</span><span class="n">column</span><span class="o">=</span><span class="s2">"car_r_t"</span><span class="p">,</span> <span class="n">linewidth</span><span class="o">=</span><span class="mf">0.03</span><span class="p">,</span> <span class="n">cmap</span><span class="o">=</span><span class="s2">"Reds"</span><span class="p">,</span> <span class="n">scheme</span><span class="o">=</span><span class="s2">"quantiles"</span><span class="p">,</span> <span class="n">k</span><span class="o">=</span><span class="mi">9</span><span class="p">,</span> <span class="n">alpha</span><span class="o">=</span><span class="mf">0.9</span><span class="p">)</span>
<span class="c1"># Add roads on top of the grid</span>
<span class="c1"># (use ax parameter to define the map on top of which the second items are plotted)</span>
<span class="n">roads</span><span class="o">.</span><span class="n">plot</span><span class="p">(</span><span class="n">ax</span><span class="o">=</span><span class="n">my_map</span><span class="p">,</span> <span class="n">color</span><span class="o">=</span><span class="s2">"grey"</span><span class="p">,</span> <span class="n">linewidth</span><span class="o">=</span><span class="mf">1.5</span><span class="p">)</span>
<span class="c1"># Add metro on top of the previous map</span>
<span class="n">metro</span><span class="o">.</span><span class="n">plot</span><span class="p">(</span><span class="n">ax</span><span class="o">=</span><span class="n">my_map</span><span class="p">,</span> <span class="n">color</span><span class="o">=</span><span class="s2">"red"</span><span class="p">,</span> <span class="n">linewidth</span><span class="o">=</span><span class="mf">2.5</span><span class="p">)</span>
<span class="c1"># Remove the empty white-space around the axes</span>
<span class="n">plt</span><span class="o">.</span><span class="n">tight_layout</span><span class="p">()</span>
<span class="c1"># Save the figure as png file with resolution of 300 dpi</span>
<span class="n">outfp</span> <span class="o">=</span> <span class="s2">r"/home/geo/data/static_map.png"</span>
<span class="n">plt</span><span class="o">.</span><span class="n">savefig</span><span class="p">(</span><span class="n">outfp</span><span class="p">,</span> <span class="n">dpi</span><span class="o">=</span><span class="mi">300</span><span class="p">)</span>
</pre></div>
</div>
<p>And this is how our map should look like:</p>
<div class="highlight-ipython"><div class="highlight"><pre><span></span>
</pre></div>
</div>
<a class="reference internal image-reference" href="_images/static_map.png"><img alt="_images/static_map.png" src="_images/static_map.png" style="width: 7in;" /></a>
<p>This kind of approach can be used really effectively to produce large quantities of nice looking maps
(<em>though this example of ours isn’t that pretty yet, but it could be</em>) which is one of the most useful aspects
of coding and what makes it so important to learn how to code.</p>
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