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<div class="section" id="mapping-tools">
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<h1>Mapping Tools<a class="headerlink" href="#mapping-tools" title="Permalink to this headline">¶</a></h1>
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<p><em>geopandas</em> provides a high-level interface to the <code class="docutils literal"><span class="pre">matplotlib</span></code> library for making maps. Mapping shapes is as easy as using the <code class="docutils literal"><span class="pre">plot()</span></code> method on a <code class="docutils literal"><span class="pre">GeoSeries</span></code> or <code class="docutils literal"><span class="pre">GeoDataFrame</span></code>.</p>
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<p>Loading some example data:</p>
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<div class="highlight-ipython"><div class="highlight"><pre><span class="gp">In [1]: </span><span class="n">world</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">gpd</span><span class="o">.</span><span class="n">datasets</span><span class="o">.</span><span class="n">get_path</span><span class="p">(</span><span class="s">'naturalearth_lowres'</span><span class="p">))</span>
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<span class="gp">In [2]: </span><span class="n">cities</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">gpd</span><span class="o">.</span><span class="n">datasets</span><span class="o">.</span><span class="n">get_path</span><span class="p">(</span><span class="s">'naturalearth_cities'</span><span class="p">))</span>
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</pre></div>
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</div>
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<p>We can now plot those GeoDataFrames:</p>
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<div class="highlight-ipython"><div class="highlight"><pre><span class="go"># Examine country GeoDataFrame</span>
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<span class="gp">In [3]: </span><span class="n">world</span><span class="o">.</span><span class="n">head</span><span class="p">()</span>
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<span class="gh">Out[3]: </span><span class="go"></span>
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<span class="go"> continent gdp_md_est \</span>
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<span class="go">0 Asia 22270 </span>
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<span class="go">1 Africa 110300 </span>
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<span class="go">2 Europe 21810 </span>
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<span class="go">3 Asia 184300 </span>
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<span class="go">4 South America 573900 </span>
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<span class="go"> geometry iso_a3 \</span>
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<span class="go">0 POLYGON ((61.21081709172574 35.65007233330923,... AFG </span>
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<span class="go">1 (POLYGON ((16.32652835456705 -5.87747039146621... AGO </span>
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<span class="go">2 POLYGON ((20.59024743010491 41.85540416113361,... ALB </span>
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<span class="go">3 POLYGON ((51.57951867046327 24.24549713795111,... ARE </span>
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<span class="go">4 (POLYGON ((-65.50000000000003 -55.199999999999... ARG </span>
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<span class="go"> name pop_est </span>
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<span class="go">0 Afghanistan 28400000 </span>
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<span class="go">1 Angola 12799293 </span>
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<span class="go">2 Albania 3639453 </span>
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<span class="go">3 United Arab Emirates 4798491 </span>
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<span class="go">4 Argentina 40913584 </span>
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<span class="go"># Basic plot, random colors</span>
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<span class="gp">In [4]: </span><span class="n">world</span><span class="o">.</span><span class="n">plot</span><span class="p">();</span>
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</pre></div>
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</div>
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<a class="reference internal image-reference" href="_images/world_randomcolors.png"><img alt="_images/world_randomcolors.png" src="_images/world_randomcolors.png" style="width: 5in;" /></a>
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<p>Note that in general, any options one can pass to <a class="reference external" href="http://matplotlib.org/api/pyplot_api.html">pyplot</a> in <code class="docutils literal"><span class="pre">matplotlib</span></code> (or <a class="reference external" href="http://matplotlib.org/api/lines_api.html">style options that work for lines</a>) can be passed to the <code class="docutils literal"><span class="pre">plot()</span></code> method.</p>
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<div class="section" id="chloropleth-maps">
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<h2>Chloropleth Maps<a class="headerlink" href="#chloropleth-maps" title="Permalink to this headline">¶</a></h2>
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<p><em>geopandas</em> makes it easy to create Chloropleth maps (maps where the color of each shape is based on the value of an associated variable). Simply use the plot command with the <code class="docutils literal"><span class="pre">column</span></code> argument set to the column whose values you want used to assign colors.</p>
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<div class="highlight-ipython"><div class="highlight"><pre><span class="go"># Plot by GDP per capta</span>
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<span class="gp">In [5]: </span><span class="n">world</span> <span class="o">=</span> <span class="n">world</span><span class="p">[(</span><span class="n">world</span><span class="o">.</span><span class="n">pop_est</span><span class="o">></span><span class="mi">0</span><span class="p">)</span> <span class="o">&</span> <span class="p">(</span><span class="n">world</span><span class="o">.</span><span class="n">name</span><span class="o">!=</span><span class="s">"Antarctica"</span><span class="p">)]</span>
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<span class="gp">In [6]: </span><span class="n">world</span><span class="p">[</span><span class="s">'gdp_per_cap'</span><span class="p">]</span> <span class="o">=</span> <span class="n">world</span><span class="o">.</span><span class="n">gdp_md_est</span> <span class="o">/</span> <span class="n">world</span><span class="o">.</span><span class="n">pop_est</span>
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<span class="gp">In [7]: </span><span class="n">world</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="s">'gdp_per_cap'</span><span class="p">);</span>
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</pre></div>
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</div>
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<a class="reference internal image-reference" href="_images/world_gdp_per_cap.png"><img alt="_images/world_gdp_per_cap.png" src="_images/world_gdp_per_cap.png" style="width: 5in;" /></a>
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<div class="section" id="choosing-colors">
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<h3>Choosing colors<a class="headerlink" href="#choosing-colors" title="Permalink to this headline">¶</a></h3>
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<p>One can also modify the colors used by <code class="docutils literal"><span class="pre">plot</span></code> with the <code class="docutils literal"><span class="pre">cmap</span></code> option (for a full list of colormaps, see the <a class="reference external" href="http://matplotlib.org/users/colormaps.html">matplotlib website</a>):</p>
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<div class="highlight-ipython"><div class="highlight"><pre><span class="gp">In [8]: </span><span class="n">world</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="s">'gdp_per_cap'</span><span class="p">,</span> <span class="n">cmap</span><span class="o">=</span><span class="s">'OrRd'</span><span class="p">);</span>
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</pre></div>
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</div>
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<a class="reference internal image-reference" href="_images/world_gdp_per_cap_red.png"><img alt="_images/world_gdp_per_cap_red.png" src="_images/world_gdp_per_cap_red.png" style="width: 5in;" /></a>
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<p>The way color maps are scaled can also be manipulated with the <code class="docutils literal"><span class="pre">scheme</span></code> option (if you have <code class="docutils literal"><span class="pre">pysal</span></code> installed, which can be accomplished via <code class="docutils literal"><span class="pre">conda</span> <span class="pre">install</span> <span class="pre">pysal</span></code>). By default, <code class="docutils literal"><span class="pre">scheme</span></code> is set to ‘equal_intervals’, but it can also be adjusted to any other <a class="reference external" href="http://pysal.org/1.2/library/esda/mapclassify.html">pysal option</a>, like ‘quantiles’, ‘percentiles’, etc.</p>
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<div class="highlight-ipython"><div class="highlight"><pre><span class="gp">In [9]: </span><span class="n">world</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="s">'gdp_per_cap'</span><span class="p">,</span> <span class="n">cmap</span><span class="o">=</span><span class="s">'OrRd'</span><span class="p">,</span> <span class="n">scheme</span><span class="o">=</span><span class="s">'quantiles'</span><span class="p">);</span>
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</pre></div>
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</div>
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<a class="reference internal image-reference" href="_images/world_gdp_per_cap_quantiles.png"><img alt="_images/world_gdp_per_cap_quantiles.png" src="_images/world_gdp_per_cap_quantiles.png" style="width: 5in;" /></a>
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</div>
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</div>
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<div class="section" id="maps-with-layers">
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<h2>Maps with Layers<a class="headerlink" href="#maps-with-layers" title="Permalink to this headline">¶</a></h2>
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<p>There are two strategies for making a map with multiple layers – one more succinct, and one that is a littel more flexible.</p>
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<p>Before combining maps, however, remember to always ensure they share a common CRS (so they will align).</p>
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<div class="highlight-ipython"><div class="highlight"><pre><span class="go"># Look at capitals</span>
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<span class="go"># Note use of standard `pyplot` line style options</span>
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<span class="gp">In [10]: </span><span class="n">cities</span><span class="o">.</span><span class="n">plot</span><span class="p">(</span><span class="n">marker</span><span class="o">=</span><span class="s">'*'</span><span class="p">,</span> <span class="n">color</span><span class="o">=</span><span class="s">'green'</span><span class="p">,</span> <span class="n">markersize</span><span class="o">=</span><span class="mi">5</span><span class="p">);</span>
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<span class="go"># Check crs</span>
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<span class="gp">In [11]: </span><span class="n">cities</span> <span class="o">=</span> <span class="n">cities</span><span class="o">.</span><span class="n">to_crs</span><span class="p">(</span><span class="n">world</span><span class="o">.</span><span class="n">crs</span><span class="p">)</span>
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<span class="go"># Now we can overlay over country outlines</span>
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<span class="go"># And yes, there are lots of island capitals</span>
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<span class="go"># apparently in the middle of the ocean!</span>
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</pre></div>
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</div>
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<a class="reference internal image-reference" href="_images/capitals.png"><img alt="_images/capitals.png" src="_images/capitals.png" style="width: 5in;" /></a>
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<p><strong>Method 1</strong></p>
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<div class="highlight-ipython"><div class="highlight"><pre><span class="gp">In [12]: </span><span class="n">base</span> <span class="o">=</span> <span class="n">world</span><span class="o">.</span><span class="n">plot</span><span class="p">(</span><span class="n">color</span><span class="o">=</span><span class="s">'white'</span><span class="p">)</span>
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<span class="gp">In [13]: </span><span class="n">cities</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">base</span><span class="p">,</span> <span class="n">marker</span><span class="o">=</span><span class="s">'o'</span><span class="p">,</span> <span class="n">color</span><span class="o">=</span><span class="s">'red'</span><span class="p">,</span> <span class="n">markersize</span><span class="o">=</span><span class="mi">5</span><span class="p">);</span>
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</pre></div>
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</div>
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<a class="reference internal image-reference" href="_images/capitals_over_countries_1.png"><img alt="_images/capitals_over_countries_1.png" src="_images/capitals_over_countries_1.png" style="width: 5in;" /></a>
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<p><strong>Method 2: Using matplotlib objects</strong></p>
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<div class="highlight-ipython"><div class="highlight"><pre><span class="gp">In [14]: </span><span class="kn">import</span> <span class="nn">matplotlib.pyplot</span> <span class="kn">as</span> <span class="nn">plt</span>
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<span class="gp">In [15]: </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>
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<span class="go"># set aspect to equal. This is done automatically</span>
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<span class="go"># when using *geopandas* plot on it's own, but not when</span>
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<span class="go"># working with pyplot directly.</span>
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<span class="gp">In [16]: </span><span class="n">ax</span><span class="o">.</span><span class="n">set_aspect</span><span class="p">(</span><span class="s">'equal'</span><span class="p">)</span>
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<span class="gp">In [17]: </span><span class="n">world</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">ax</span><span class="p">,</span> <span class="n">color</span><span class="o">=</span><span class="s">'white'</span><span class="p">)</span>
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<span class="gh">Out[17]: </span><span class="go"><matplotlib.axes._subplots.AxesSubplot at 0x1196ae1d0></span>
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<span class="gp">In [18]: </span><span class="n">cities</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">ax</span><span class="p">,</span> <span class="n">marker</span><span class="o">=</span><span class="s">'o'</span><span class="p">,</span> <span class="n">color</span><span class="o">=</span><span class="s">'red'</span><span class="p">,</span> <span class="n">markersize</span><span class="o">=</span><span class="mi">5</span><span class="p">)</span>
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<span class="go"> Out[18]: <matplotlib.axes._subplots.AxesSubplot at 0x1196ae1d0></span>
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<span class="gp">In [19]: </span><span class="n">plt</span><span class="o">.</span><span class="n">show</span><span class="p">();</span>
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</pre></div>
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</div>
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<a class="reference internal image-reference" href="_images/capitals_over_countries_2.png"><img alt="_images/capitals_over_countries_2.png" src="_images/capitals_over_countries_2.png" style="width: 5in;" /></a>
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</div>
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<div class="section" id="other-resources">
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<h2>Other Resources<a class="headerlink" href="#other-resources" title="Permalink to this headline">¶</a></h2>
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<p>Links to jupyter Notebooks for different mapping tasks:</p>
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<p><a class="reference external" href="http://nbviewer.jupyter.org/gist/perrygeo/c426355e40037c452434">Making Heat Maps</a></p>
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