{"action":"created","comment":{"url":"https://api.github.com/repos/plotly/documentation/pulls/comments/169772184","pull_request_review_id":98353660,"id":169772184,"diff_hunk":"@@ -0,0 +1,796 @@\n+---\n+permalink: python/county-choropleth/\n+description: How to create colormaped representations of US counties by FIPS values in Python.\n+name: County Choropleth\n+has_thumbnail: true\n+thumbnail: thumbnail/county-choropleth-usa-greybkgd.jpg\n+layout: user-guide\n+language: python\n+title: Python County Choropleth | Plotly\n+display_as: maps\n+has_thumbnail: true\n+page_type: example_index\n+order: 0\n+---\n+{% raw %}<script type=\"text/javascript\"         src=\"https://cdnjs.cloudflare.com/ajax/libs/require.js/2.3.2/require.js\"></script>\n+<div class=\"cell border-box-sizing code_cell rendered\">\n+<div class=\"input\">\n+<div class=\"prompt input_prompt\">In&nbsp;[1]:</div>\n+<div class=\"inner_cell\">\n+    <div class=\"input_area\">\n+<div class=\" highlight hl-ipython2\"><pre><span></span><span class=\"n\">pwd</span>\n+</pre></div>\n+\n+</div>\n+</div>\n+</div>\n+\n+<div class=\"output_wrapper\">\n+<div class=\"output\">\n+\n+\n+<div class=\"output_area\">\n+\n+<div class=\"prompt output_prompt\">Out[1]:</div>\n+\n+\n+\n+\n+<div class=\"output_text output_subarea output_execute_result\">\n+<pre>u&#39;/Users/adamkulidjian/Desktop/Adam/Plotly/documentation/_posts/python/maps/county_choropleth&#39;</pre>\n+</div>\n+\n+</div>\n+\n+</div>\n+</div>\n+\n+</div>\n+<div class=\"cell border-box-sizing text_cell rendered\"><div class=\"prompt input_prompt\">\n+</div>\n+<div class=\"inner_cell\">\n+<div class=\"text_cell_render border-box-sizing rendered_html\">\n+<h4 id=\"New-to-Plotly?\">New to Plotly?<a class=\"anchor-link\" href=\"#New-to-Plotly?\">&#194;&#182;</a></h4><p>Plotly's Python library is free and open source! <a href=\"https://plot.ly/python/getting-started/\">Get started</a> by downloading the client and <a href=\"https://plot.ly/python/getting-started/\">reading the primer</a>.\n+<br>You can set up Plotly to work in <a href=\"https://plot.ly/python/getting-started/#initialization-for-online-plotting\">online</a> or <a href=\"https://plot.ly/python/getting-started/#initialization-for-offline-plotting\">offline</a> mode, or in <a href=\"https://plot.ly/python/getting-started/#start-plotting-online\">jupyter notebooks</a>.\n+<br>We also have a quick-reference <a href=\"https://images.plot.ly/plotly-documentation/images/python_cheat_sheet.pdf\">cheatsheet</a> (new!) to help you get started!</p>\n+\n+</div>\n+</div>\n+</div>\n+<div class=\"cell border-box-sizing text_cell rendered\"><div class=\"prompt input_prompt\">\n+</div>\n+<div class=\"inner_cell\">\n+<div class=\"text_cell_render border-box-sizing rendered_html\">\n+<h4 id=\"Version-Check\">Version Check<a class=\"anchor-link\" href=\"#Version-Check\">&#194;&#182;</a></h4><p>Note: <code>County Choropleths</code> are available in version <b>2.4.1+</b><br>\n+Run  <code>pip install plotly --upgrade</code> to update your Plotly version</p>\n+\n+</div>\n+</div>\n+</div>\n+<div class=\"cell border-box-sizing code_cell rendered\">\n+<div class=\"input\">\n+<div class=\"prompt input_prompt\">In&nbsp;[2]:</div>\n+<div class=\"inner_cell\">\n+    <div class=\"input_area\">\n+<div class=\" highlight hl-ipython2\"><pre><span></span><span class=\"kn\">import</span> <span class=\"nn\">plotly</span>\n+<span class=\"n\">plotly</span><span class=\"o\">.</span><span class=\"n\">__version__</span>\n+</pre></div>\n+\n+</div>\n+</div>\n+</div>\n+\n+<div class=\"output_wrapper\">\n+<div class=\"output\">\n+\n+\n+<div class=\"output_area\">\n+\n+<div class=\"prompt output_prompt\">Out[2]:</div>\n+\n+\n+\n+\n+<div class=\"output_text output_subarea output_execute_result\">\n+<pre>&#39;2.4.1&#39;</pre>\n+</div>\n+\n+</div>\n+\n+</div>\n+</div>\n+\n+</div>\n+<div class=\"cell border-box-sizing text_cell rendered\"><div class=\"prompt input_prompt\">\n+</div>\n+<div class=\"inner_cell\">\n+<div class=\"text_cell_render border-box-sizing rendered_html\">\n+<h4 id=\"FIPS-and-Values\">FIPS and Values<a class=\"anchor-link\" href=\"#FIPS-and-Values\">&#194;&#182;</a></h4><p>Every US State and County has an assined ID regulated by the US Federal Government under the term FIPS (Federal Information Processing Standards) Codes. There are State codes and County codes: the 2016 State and County FIPS Codes can be found at the <a href=\"https://www.census.gov/geographies/reference-files/2016/demo/popest/2016-fips.html\">US Census Website</a>.</p>\n+<p>Combine a State FIPS code (eg. <code>06</code> for California) with a County FIPS codes of the State (eg. <code>059</code> for Orange County) and this new State-County FIPS code (<code>06059</code>) uniquely refers to the specified State and County.</p>\n+<p><code>ff.create_choropleth</code> only needs a list of FIPS codes and a list of values.</p>\n+<p><b>Each FIPS code points to one county and each corresponding value in `values` determines the color of the county.</b></p>\n+<p>A simple example of this is a choropleth a few counties in California:</p>\n+\n+</div>\n+</div>\n+</div>\n+<div class=\"cell border-box-sizing code_cell rendered\">\n+<div class=\"input\">\n+<div class=\"prompt input_prompt\">In&nbsp;[3]:</div>\n+<div class=\"inner_cell\">\n+    <div class=\"input_area\">\n+<div class=\" highlight hl-ipython2\"><pre><span></span><span class=\"kn\">import</span> <span class=\"nn\">plotly.plotly</span> <span class=\"kn\">as</span> <span class=\"nn\">py</span>\n+<span class=\"kn\">import</span> <span class=\"nn\">plotly.figure_factory</span> <span class=\"kn\">as</span> <span class=\"nn\">ff</span>\n+\n+<span class=\"n\">fips</span> <span class=\"o\">=</span> <span class=\"p\">[</span><span class=\"s1\">&#39;06021&#39;</span><span class=\"p\">,</span> <span class=\"s1\">&#39;06023&#39;</span><span class=\"p\">,</span> <span class=\"s1\">&#39;06027&#39;</span><span class=\"p\">,</span>\n+        <span class=\"s1\">&#39;06029&#39;</span><span class=\"p\">,</span> <span class=\"s1\">&#39;06033&#39;</span><span class=\"p\">,</span> <span class=\"s1\">&#39;06059&#39;</span><span class=\"p\">,</span>\n+        <span class=\"s1\">&#39;06047&#39;</span><span class=\"p\">,</span> <span class=\"s1\">&#39;06049&#39;</span><span class=\"p\">,</span> <span class=\"s1\">&#39;06051&#39;</span><span class=\"p\">,</span>\n+        <span class=\"s1\">&#39;06055&#39;</span><span class=\"p\">,</span> <span class=\"s1\">&#39;06061&#39;</span><span class=\"p\">]</span>\n+<span class=\"n\">values</span> <span class=\"o\">=</span> <span class=\"nb\">range</span><span class=\"p\">(</span><span class=\"nb\">len</span><span class=\"p\">(</span><span class=\"n\">fips</span><span class=\"p\">))</span>\n+\n+<span class=\"n\">fig</span> <span class=\"o\">=</span> <span class=\"n\">ff</span><span class=\"o\">.</span><span class=\"n\">create_choropleth</span><span class=\"p\">(</span>\n+    <span class=\"n\">fips</span><span class=\"o\">=</span><span class=\"n\">fips</span><span class=\"p\">,</span> <span class=\"n\">values</span><span class=\"o\">=</span><span class=\"n\">values</span><span class=\"p\">,</span>\n+    <span class=\"n\">county_outline</span><span class=\"o\">=</span><span class=\"p\">{</span><span class=\"s1\">&#39;color&#39;</span><span class=\"p\">:</span> <span class=\"s1\">&#39;rgb(255,255,255)&#39;</span><span class=\"p\">,</span> <span class=\"s1\">&#39;width&#39;</span><span class=\"p\">:</span> <span class=\"mf\">0.5</span><span class=\"p\">},</span>\n+<span class=\"p\">)</span>\n+\n+<span class=\"n\">py</span><span class=\"o\">.</span><span class=\"n\">iplot</span><span class=\"p\">(</span><span class=\"n\">fig</span><span class=\"p\">,</span> <span class=\"n\">filename</span><span class=\"o\">=</span><span class=\"s1\">&#39;choropleth of some cali counties - full usa scope&#39;</span><span class=\"p\">)</span>\n+</pre></div>\n+\n+</div>\n+</div>\n+</div>\n+\n+<div class=\"output_wrapper\">\n+<div class=\"output\">\n+\n+\n+<div class=\"output_area\">\n+\n+<div class=\"prompt output_prompt\">Out[3]:</div>\n+\n+\n+\n+<div class=\"output_html rendered_html output_subarea output_execute_result\">\n+<iframe id=\"igraph\" scrolling=\"no\" style=\"border:none;\" seamless=\"seamless\" src=\"https://plot.ly/~AdamKulidjian/6690.embed\" height=\"450px\" width=\"900px\"></iframe>\n+</div>\n+\n+</div>\n+\n+</div>\n+</div>\n+\n+</div>\n+<div class=\"cell border-box-sizing text_cell rendered\"><div class=\"prompt input_prompt\">\n+</div>\n+<div class=\"inner_cell\">\n+<div class=\"text_cell_render border-box-sizing rendered_html\">\n+<h4 id=\"Change-your-Scope\">Change your Scope<a class=\"anchor-link\" href=\"#Change-your-Scope\">&#194;&#182;</a></h4><p>Even if your FIPS values belong to a single state, changing the <code>scope</code> of the choropleth shifts the zoom and position of the USA map to include any states. Specify a list of state names and the camera automatically adjusts to include the state outlines of the selected states.</p>\n+<p>By default <code>scope</code> is set to <code>['USA']</code> which the API treats as identical to passing a list of all 50 state names:<br></p>\n+<p><code>['AK', 'AL', 'CA', ...]</code></p>\n+<p>State abbreviations (eg. <code>CA</code>) or the proper names (eg. <code>California</code>) as strings are accepted. If the state name is not recognized, the API will throw a Warning and indicate which FIPS values were ignored.</p>\n+\n+</div>\n+</div>\n+</div>\n+<div class=\"cell border-box-sizing code_cell rendered\">\n+<div class=\"input\">\n+<div class=\"prompt input_prompt\">In&nbsp;[4]:</div>\n+<div class=\"inner_cell\">\n+    <div class=\"input_area\">\n+<div class=\" highlight hl-ipython2\"><pre><span></span><span class=\"kn\">import</span> <span class=\"nn\">plotly.plotly</span> <span class=\"kn\">as</span> <span class=\"nn\">py</span>\n+<span class=\"kn\">import</span> <span class=\"nn\">plotly.figure_factory</span> <span class=\"kn\">as</span> <span class=\"nn\">ff</span>\n+\n+<span class=\"kn\">import</span> <span class=\"nn\">numpy</span> <span class=\"kn\">as</span> <span class=\"nn\">np</span>\n+<span class=\"kn\">import</span> <span class=\"nn\">pandas</span> <span class=\"kn\">as</span> <span class=\"nn\">pd</span>\n+\n+<span class=\"n\">df_sample</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=\"s1\">&#39;https://raw.githubusercontent.com/plotly/datasets/master/minoritymajority.csv&#39;</span><span class=\"p\">)</span>\n+<span class=\"n\">df_sample_r</span> <span class=\"o\">=</span> <span class=\"n\">df_sample</span><span class=\"p\">[</span><span class=\"n\">df_sample</span><span class=\"p\">[</span><span class=\"s1\">&#39;STNAME&#39;</span><span class=\"p\">]</span> <span class=\"o\">==</span> <span class=\"s1\">&#39;California&#39;</span><span class=\"p\">]</span>\n+\n+<span class=\"n\">values</span> <span class=\"o\">=</span> <span class=\"n\">df_sample_r</span><span class=\"p\">[</span><span class=\"s1\">&#39;TOT_POP&#39;</span><span class=\"p\">]</span><span class=\"o\">.</span><span class=\"n\">tolist</span><span class=\"p\">()</span>\n+<span class=\"n\">fips</span> <span class=\"o\">=</span> <span class=\"n\">df_sample_r</span><span class=\"p\">[</span><span class=\"s1\">&#39;FIPS&#39;</span><span class=\"p\">]</span><span class=\"o\">.</span><span class=\"n\">tolist</span><span class=\"p\">()</span>\n+\n+<span class=\"n\">colorscale</span> <span class=\"o\">=</span> <span class=\"p\">[</span>\n+    <span class=\"s1\">&#39;rgb(193, 193, 193)&#39;</span><span class=\"p\">,</span>\n+    <span class=\"s1\">&#39;rgb(239,239,239)&#39;</span><span class=\"p\">,</span>\n+    <span class=\"s1\">&#39;rgb(195, 196, 222)&#39;</span><span class=\"p\">,</span>\n+    <span class=\"s1\">&#39;rgb(144,148,194)&#39;</span><span class=\"p\">,</span>\n+    <span class=\"s1\">&#39;rgb(101,104,168)&#39;</span><span class=\"p\">,</span>\n+    <span class=\"s1\">&#39;rgb(65, 53, 132)&#39;</span>\n+<span class=\"p\">]</span>\n+\n+<span class=\"n\">fig</span> <span class=\"o\">=</span> <span class=\"n\">ff</span><span class=\"o\">.</span><span class=\"n\">create_choropleth</span><span class=\"p\">(</span>\n+    <span class=\"n\">fips</span><span class=\"o\">=</span><span class=\"n\">fips</span><span class=\"p\">,</span> <span class=\"n\">values</span><span class=\"o\">=</span><span class=\"n\">values</span><span class=\"p\">,</span> <span class=\"n\">scope</span><span class=\"o\">=</span><span class=\"p\">[</span><span class=\"s1\">&#39;CA&#39;</span><span class=\"p\">,</span> <span class=\"s1\">&#39;AZ&#39;</span><span class=\"p\">,</span> <span class=\"s1\">&#39;Nevada&#39;</span><span class=\"p\">,</span> <span class=\"s1\">&#39;Oregon&#39;</span><span class=\"p\">,</span> <span class=\"s1\">&#39; Idaho&#39;</span><span class=\"p\">],</span>\n+    <span class=\"n\">binning_endpoints</span><span class=\"o\">=</span><span class=\"p\">[</span><span class=\"mi\">14348</span><span class=\"p\">,</span> <span class=\"mi\">63983</span><span class=\"p\">,</span> <span class=\"mi\">134827</span><span class=\"p\">,</span> <span class=\"mi\">426762</span><span class=\"p\">,</span> <span class=\"mi\">2081313</span><span class=\"p\">],</span> <span class=\"n\">colorscale</span><span class=\"o\">=</span><span class=\"n\">colorscale</span><span class=\"p\">,</span>\n+    <span class=\"n\">county_outline</span><span class=\"o\">=</span><span class=\"p\">{</span><span class=\"s1\">&#39;color&#39;</span><span class=\"p\">:</span> <span class=\"s1\">&#39;rgb(255,255,255)&#39;</span><span class=\"p\">,</span> <span class=\"s1\">&#39;width&#39;</span><span class=\"p\">:</span> <span class=\"mf\">0.5</span><span class=\"p\">},</span> <span class=\"n\">round_legend_values</span><span class=\"o\">=</span><span class=\"bp\">True</span><span class=\"p\">,</span>\n+    <span class=\"n\">legend_title</span><span class=\"o\">=</span><span class=\"s1\">&#39;Population by County&#39;</span><span class=\"p\">,</span> <span class=\"n\">title</span><span class=\"o\">=</span><span class=\"s1\">&#39;California and Nearby States&#39;</span>\n+<span class=\"p\">)</span>\n+<span class=\"n\">py</span><span class=\"o\">.</span><span class=\"n\">iplot</span><span class=\"p\">(</span><span class=\"n\">fig</span><span class=\"p\">,</span> <span class=\"n\">filename</span><span class=\"o\">=</span><span class=\"s1\">&#39;choropleth_california_and_surr_states_outlines&#39;</span><span class=\"p\">)</span>\n+</pre></div>\n+\n+</div>\n+</div>\n+</div>\n+\n+<div class=\"output_wrapper\">\n+<div class=\"output\">\n+\n+\n+<div class=\"output_area\">\n+\n+<div class=\"prompt output_prompt\">Out[4]:</div>\n+\n+\n+\n+<div class=\"output_html rendered_html output_subarea output_execute_result\">\n+<iframe id=\"igraph\" scrolling=\"no\" style=\"border:none;\" seamless=\"seamless\" src=\"https://plot.ly/~AdamKulidjian/6676.embed\" height=\"450px\" width=\"900px\"></iframe>\n+</div>\n+\n+</div>\n+\n+</div>\n+</div>\n+\n+</div>\n+<div class=\"cell border-box-sizing text_cell rendered\"><div class=\"prompt input_prompt\">\n+</div>\n+<div class=\"inner_cell\">\n+<div class=\"text_cell_render border-box-sizing rendered_html\">\n+<h4 id=\"Florida\">Florida<a class=\"anchor-link\" href=\"#Florida\">&#194;&#182;</a></h4>\n+</div>\n+</div>\n+</div>\n+<div class=\"cell border-box-sizing code_cell rendered\">\n+<div class=\"input\">\n+<div class=\"prompt input_prompt\">In&nbsp;[5]:</div>\n+<div class=\"inner_cell\">\n+    <div class=\"input_area\">\n+<div class=\" highlight hl-ipython2\"><pre><span></span><span class=\"kn\">import</span> <span class=\"nn\">plotly.plotly</span> <span class=\"kn\">as</span> <span class=\"nn\">py</span>\n+<span class=\"kn\">import</span> <span class=\"nn\">plotly.figure_factory</span> <span class=\"kn\">as</span> <span class=\"nn\">ff</span>\n+\n+<span class=\"kn\">import</span> <span class=\"nn\">numpy</span> <span class=\"kn\">as</span> <span class=\"nn\">np</span>\n+<span class=\"kn\">import</span> <span class=\"nn\">pandas</span> <span class=\"kn\">as</span> <span class=\"nn\">pd</span>\n+\n+<span class=\"n\">df_sample</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=\"s1\">&#39;https://raw.githubusercontent.com/plotly/datasets/master/minoritymajority.csv&#39;</span><span class=\"p\">)</span>\n+<span class=\"n\">df_sample_r</span> <span class=\"o\">=</span> <span class=\"n\">df_sample</span><span class=\"p\">[</span><span class=\"n\">df_sample</span><span class=\"p\">[</span><span class=\"s1\">&#39;STNAME&#39;</span><span class=\"p\">]</span> <span class=\"o\">==</span> <span class=\"s1\">&#39;Florida&#39;</span><span class=\"p\">]</span>\n+\n+<span class=\"n\">values</span> <span class=\"o\">=</span> <span class=\"n\">df_sample_r</span><span class=\"p\">[</span><span class=\"s1\">&#39;TOT_POP&#39;</span><span class=\"p\">]</span><span class=\"o\">.</span><span class=\"n\">tolist</span><span class=\"p\">()</span>\n+<span class=\"n\">fips</span> <span class=\"o\">=</span> <span class=\"n\">df_sample_r</span><span class=\"p\">[</span><span class=\"s1\">&#39;FIPS&#39;</span><span class=\"p\">]</span><span class=\"o\">.</span><span class=\"n\">tolist</span><span class=\"p\">()</span>\n+\n+<span class=\"n\">endpts</span> <span class=\"o\">=</span> <span class=\"nb\">list</span><span class=\"p\">(</span><span class=\"n\">np</span><span class=\"o\">.</span><span class=\"n\">mgrid</span><span class=\"p\">[</span><span class=\"nb\">min</span><span class=\"p\">(</span><span class=\"n\">values</span><span class=\"p\">):</span><span class=\"nb\">max</span><span class=\"p\">(</span><span class=\"n\">values</span><span class=\"p\">):</span><span class=\"mi\">4j</span><span class=\"p\">])</span>\n+<span class=\"n\">colorscale</span> <span class=\"o\">=</span> <span class=\"p\">[</span><span class=\"s2\">&quot;#030512&quot;</span><span class=\"p\">,</span><span class=\"s2\">&quot;#1d1d3b&quot;</span><span class=\"p\">,</span><span class=\"s2\">&quot;#323268&quot;</span><span class=\"p\">,</span><span class=\"s2\">&quot;#3d4b94&quot;</span><span class=\"p\">,</span><span class=\"s2\">&quot;#3e6ab0&quot;</span><span class=\"p\">,</span>\n+              <span class=\"s2\">&quot;#4989bc&quot;</span><span class=\"p\">,</span><span class=\"s2\">&quot;#60a7c7&quot;</span><span class=\"p\">,</span><span class=\"s2\">&quot;#85c5d3&quot;</span><span class=\"p\">,</span><span class=\"s2\">&quot;#b7e0e4&quot;</span><span class=\"p\">,</span><span class=\"s2\">&quot;#eafcfd&quot;</span><span class=\"p\">]</span>\n+<span class=\"n\">fig</span> <span class=\"o\">=</span> <span class=\"n\">ff</span><span class=\"o\">.</span><span class=\"n\">create_choropleth</span><span class=\"p\">(</span>\n+    <span class=\"n\">fips</span><span class=\"o\">=</span><span class=\"n\">fips</span><span class=\"p\">,</span> <span class=\"n\">values</span><span class=\"o\">=</span><span class=\"n\">values</span><span class=\"p\">,</span> <span class=\"n\">scope</span><span class=\"o\">=</span><span class=\"p\">[</span><span class=\"s1\">&#39;Florida&#39;</span><span class=\"p\">],</span> <span class=\"n\">show_state_data</span><span class=\"o\">=</span><span class=\"bp\">True</span><span class=\"p\">,</span>\n+    <span class=\"n\">colorscale</span><span class=\"o\">=</span><span class=\"n\">colorscale</span><span class=\"p\">,</span> <span class=\"n\">binning_endpoints</span><span class=\"o\">=</span><span class=\"n\">endpts</span><span class=\"p\">,</span> <span class=\"n\">round_legend_values</span><span class=\"o\">=</span><span class=\"bp\">True</span><span class=\"p\">,</span>\n+    <span class=\"n\">plot_bgcolor</span><span class=\"o\">=</span><span class=\"s1\">&#39;rgb(229,229,229)&#39;</span><span class=\"p\">,</span>\n+    <span class=\"n\">paper_bgcolor</span><span class=\"o\">=</span><span class=\"s1\">&#39;rgb(229,229,229)&#39;</span><span class=\"p\">,</span>\n+    <span class=\"n\">legend_title</span><span class=\"o\">=</span><span class=\"s1\">&#39;Population by County&#39;</span><span class=\"p\">,</span>\n+    <span class=\"n\">county_outline</span><span class=\"o\">=</span><span class=\"p\">{</span><span class=\"s1\">&#39;color&#39;</span><span class=\"p\">:</span> <span class=\"s1\">&#39;rgb(255,255,255)&#39;</span><span class=\"p\">,</span> <span class=\"s1\">&#39;width&#39;</span><span class=\"p\">:</span> <span class=\"mf\">0.5</span><span class=\"p\">},</span>\n+    <span class=\"n\">exponent_format</span><span class=\"o\">=</span><span class=\"bp\">True</span><span class=\"p\">,</span>\n+<span class=\"p\">)</span>\n+<span class=\"n\">py</span><span class=\"o\">.</span><span class=\"n\">iplot</span><span class=\"p\">(</span><span class=\"n\">fig</span><span class=\"p\">,</span> <span class=\"n\">filename</span><span class=\"o\">=</span><span class=\"s1\">&#39;choropleth_florida&#39;</span><span class=\"p\">)</span>\n+</pre></div>\n+\n+</div>\n+</div>\n+</div>\n+\n+<div class=\"output_wrapper\">\n+<div class=\"output\">\n+\n+\n+<div class=\"output_area\">\n+\n+<div class=\"prompt output_prompt\">Out[5]:</div>\n+\n+\n+\n+<div class=\"output_html rendered_html output_subarea output_execute_result\">\n+<iframe id=\"igraph\" scrolling=\"no\" style=\"border:none;\" seamless=\"seamless\" src=\"https://plot.ly/~AdamKulidjian/6678.embed\" height=\"450px\" width=\"900px\"></iframe>\n+</div>\n+\n+</div>\n+\n+</div>\n+</div>\n+\n+</div>\n+<div class=\"cell border-box-sizing text_cell rendered\"><div class=\"prompt input_prompt\">\n+</div>\n+<div class=\"inner_cell\">\n+<div class=\"text_cell_render border-box-sizing rendered_html\">\n+<h4 id=\"Multiple-States\">Multiple States<a class=\"anchor-link\" href=\"#Multiple-States\">&#194;&#182;</a></h4>\n+</div>\n+</div>\n+</div>\n+<div class=\"cell border-box-sizing code_cell rendered\">\n+<div class=\"input\">\n+<div class=\"prompt input_prompt\">In&nbsp;[6]:</div>\n+<div class=\"inner_cell\">\n+    <div class=\"input_area\">\n+<div class=\" highlight hl-ipython2\"><pre><span></span><span class=\"kn\">import</span> <span class=\"nn\">plotly.plotly</span> <span class=\"kn\">as</span> <span class=\"nn\">py</span>\n+<span class=\"kn\">import</span> <span class=\"nn\">plotly.figure_factory</span> <span class=\"kn\">as</span> <span class=\"nn\">ff</span>\n+\n+<span class=\"kn\">import</span> <span class=\"nn\">pandas</span> <span class=\"kn\">as</span> <span class=\"nn\">pd</span>\n+\n+<span class=\"n\">NE_states</span> <span class=\"o\">=</span> <span class=\"p\">[</span><span class=\"s1\">&#39;Connecticut&#39;</span><span class=\"p\">,</span> <span class=\"s1\">&#39;Maine&#39;</span><span class=\"p\">,</span> <span class=\"s1\">&#39;Massachusetts&#39;</span><span class=\"p\">,</span> <span class=\"s1\">&#39;New Hampshire&#39;</span><span class=\"p\">,</span> <span class=\"s1\">&#39;Rhode Island&#39;</span><span class=\"p\">,</span> <span class=\"s1\">&#39;Vermont&#39;</span><span class=\"p\">]</span>\n+<span class=\"n\">df_sample</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=\"s1\">&#39;https://raw.githubusercontent.com/plotly/datasets/master/minoritymajority.csv&#39;</span><span class=\"p\">)</span>\n+<span class=\"n\">df_sample_r</span> <span class=\"o\">=</span> <span class=\"n\">df_sample</span><span class=\"p\">[</span><span class=\"n\">df_sample</span><span class=\"p\">[</span><span class=\"s1\">&#39;STNAME&#39;</span><span class=\"p\">]</span><span class=\"o\">.</span><span class=\"n\">isin</span><span class=\"p\">(</span><span class=\"n\">NE_states</span><span class=\"p\">)]</span>\n+\n+<span class=\"n\">values</span> <span class=\"o\">=</span> <span class=\"n\">df_sample_r</span><span class=\"p\">[</span><span class=\"s1\">&#39;TOT_POP&#39;</span><span class=\"p\">]</span><span class=\"o\">.</span><span class=\"n\">tolist</span><span class=\"p\">()</span>\n+<span class=\"n\">fips</span> <span class=\"o\">=</span> <span class=\"n\">df_sample_r</span><span class=\"p\">[</span><span class=\"s1\">&#39;FIPS&#39;</span><span class=\"p\">]</span><span class=\"o\">.</span><span class=\"n\">tolist</span><span class=\"p\">()</span>\n+\n+<span class=\"n\">colorscale</span> <span class=\"o\">=</span> <span class=\"p\">[</span>\n+    <span class=\"s1\">&#39;rgb(68.0, 1.0, 84.0)&#39;</span><span class=\"p\">,</span>\n+    <span class=\"s1\">&#39;rgb(66.0, 64.0, 134.0)&#39;</span><span class=\"p\">,</span>\n+    <span class=\"s1\">&#39;rgb(38.0, 130.0, 142.0)&#39;</span><span class=\"p\">,</span>\n+    <span class=\"s1\">&#39;rgb(63.0, 188.0, 115.0)&#39;</span><span class=\"p\">,</span>\n+    <span class=\"s1\">&#39;rgb(216.0, 226.0, 25.0)&#39;</span>\n+<span class=\"p\">]</span>\n+\n+<span class=\"n\">fig</span> <span class=\"o\">=</span> <span class=\"n\">ff</span><span class=\"o\">.</span><span class=\"n\">create_choropleth</span><span class=\"p\">(</span>\n+    <span class=\"n\">fips</span><span class=\"o\">=</span><span class=\"n\">fips</span><span class=\"p\">,</span> <span class=\"n\">values</span><span class=\"o\">=</span><span class=\"n\">values</span><span class=\"p\">,</span>\n+    <span class=\"n\">scope</span><span class=\"o\">=</span><span class=\"n\">NE_states</span><span class=\"p\">,</span> <span class=\"n\">county_outline</span><span class=\"o\">=</span><span class=\"p\">{</span><span class=\"s1\">&#39;color&#39;</span><span class=\"p\">:</span> <span class=\"s1\">&#39;rgb(255,255,255)&#39;</span><span class=\"p\">,</span> <span class=\"s1\">&#39;width&#39;</span><span class=\"p\">:</span> <span class=\"mf\">0.5</span><span class=\"p\">},</span>\n+    <span class=\"n\">legend_title</span><span class=\"o\">=</span><span class=\"s1\">&#39;Population per county&#39;</span>\n+   \n+<span class=\"p\">)</span>\n+<span class=\"n\">fig</span><span class=\"p\">[</span><span class=\"s1\">&#39;layout&#39;</span><span class=\"p\">][</span><span class=\"s1\">&#39;legend&#39;</span><span class=\"p\">]</span><span class=\"o\">.</span><span class=\"n\">update</span><span class=\"p\">({</span><span class=\"s1\">&#39;x&#39;</span><span class=\"p\">:</span> <span class=\"mi\">0</span><span class=\"p\">})</span>\n+<span class=\"n\">fig</span><span class=\"p\">[</span><span class=\"s1\">&#39;layout&#39;</span><span class=\"p\">][</span><span class=\"s1\">&#39;annotations&#39;</span><span class=\"p\">][</span><span class=\"mi\">0</span><span class=\"p\">]</span><span class=\"o\">.</span><span class=\"n\">update</span><span class=\"p\">({</span><span class=\"s1\">&#39;x&#39;</span><span class=\"p\">:</span> <span class=\"o\">-</span><span class=\"mf\">0.12</span><span class=\"p\">,</span> <span class=\"s1\">&#39;xanchor&#39;</span><span class=\"p\">:</span> <span class=\"s1\">&#39;left&#39;</span><span class=\"p\">})</span>\n+<span class=\"n\">py</span><span class=\"o\">.</span><span class=\"n\">iplot</span><span class=\"p\">(</span><span class=\"n\">fig</span><span class=\"p\">,</span> <span class=\"n\">filename</span><span class=\"o\">=</span><span class=\"s1\">&#39;choropleth_new_england&#39;</span><span class=\"p\">)</span>\n+</pre></div>\n+\n+</div>\n+</div>\n+</div>\n+\n+<div class=\"output_wrapper\">\n+<div class=\"output\">\n+\n+\n+<div class=\"output_area\">\n+\n+<div class=\"prompt output_prompt\">Out[6]:</div>\n+\n+\n+\n+<div class=\"output_html rendered_html output_subarea output_execute_result\">\n+<iframe id=\"igraph\" scrolling=\"no\" style=\"border:none;\" seamless=\"seamless\" src=\"https://plot.ly/~AdamKulidjian/6674.embed\" height=\"450px\" width=\"900px\"></iframe>\n+</div>\n+\n+</div>\n+\n+</div>\n+</div>\n+\n+</div>\n+<div class=\"cell border-box-sizing text_cell rendered\"><div class=\"prompt input_prompt\">\n+</div>\n+<div class=\"inner_cell\">\n+<div class=\"text_cell_render border-box-sizing rendered_html\">\n+<h4 id=\"Offline-Choropleth\">Offline Choropleth<a class=\"anchor-link\" href=\"#Offline-Choropleth\">&#194;&#182;</a></h4><p>Setting <code>offline_mode=True</code> modifies the centroid markers so that they are only visible if you hoverdrag a box over them.</p>","path":"_posts/python/maps/county_choropleth/2015-06-30-county_choropleth.html","position":370,"original_position":370,"commit_id":"4dc97524950b42a2335be22f6592b03d28668fe6","original_commit_id":"4dc97524950b42a2335be22f6592b03d28668fe6","user":{"login":"cldougl","id":2789078,"avatar_url":"https://avatars1.githubusercontent.com/u/2789078?v=4","gravatar_id":"","url":"https://api.github.com/users/cldougl","html_url":"https://github.com/cldougl","followers_url":"https://api.github.com/users/cldougl/followers","following_url":"https://api.github.com/users/cldougl/following{/other_user}","gists_url":"https://api.github.com/users/cldougl/gists{/gist_id}","starred_url":"https://api.github.com/users/cldougl/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/cldougl/subscriptions","organizations_url":"https://api.github.com/users/cldougl/orgs","repos_url":"https://api.github.com/users/cldougl/repos","events_url":"https://api.github.com/users/cldougl/events{/privacy}","received_events_url":"https://api.github.com/users/cldougl/received_events","type":"User","site_admin":false},"body":"cool! I'd just remove this from the doc or change it to an online example if you still want to include this example.","created_at":"2018-02-21T20:46:13Z","updated_at":"2018-02-21T20:46:14Z","html_url":"https://github.com/plotly/documentation/pull/879#discussion_r169772184","pull_request_url":"https://api.github.com/repos/plotly/documentation/pulls/879","author_association":"MEMBER","_links":{"self":{"href":"https://api.github.com/repos/plotly/documentation/pulls/comments/169772184"},"html":{"href":"https://github.com/plotly/documentation/pull/879#discussion_r169772184"},"pull_request":{"href":"https://api.github.com/repos/plotly/documentation/pulls/879"}},"in_reply_to_id":169753458},"pull_request":{"url":"https://api.github.com/repos/plotly/documentation/pulls/879","id":170046858,"html_url":"https://github.com/plotly/documentation/pull/879","diff_url":"https://github.com/plotly/documentation/pull/879.diff","patch_url":"https://github.com/plotly/documentation/pull/879.patch","issue_url":"https://api.github.com/repos/plotly/documentation/issues/879","number":879,"state":"open","locked":false,"title":"Choropleth Docs","user":{"login":"Kully","id":10369095,"avatar_url":"https://avatars1.githubusercontent.com/u/10369095?v=4","gravatar_id":"","url":"https://api.github.com/users/Kully","html_url":"https://github.com/Kully","followers_url":"https://api.github.com/users/Kully/followers","following_url":"https://api.github.com/users/Kully/following{/other_user}","gists_url":"https://api.github.com/users/Kully/gists{/gist_id}","starred_url":"https://api.github.com/users/Kully/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/Kully/subscriptions","organizations_url":"https://api.github.com/users/Kully/orgs","repos_url":"https://api.github.com/users/Kully/repos","events_url":"https://api.github.com/users/Kully/events{/privacy}","received_events_url":"https://api.github.com/users/Kully/received_events","type":"User","site_admin":false},"body":"todo:\r\n- [x] I think https://plot.ly/python/choropleth-maps/ should have the USA county example at the bottom with a link to the full county choropleth docs, just in case people forget to search “county” when they search for choropleth maps (Jack's comment)\r\n- [x] https://plot.ly/python/county-level-choropleth/ move to the URL python/mapbox-county-choropleths","created_at":"2018-02-19T20:28:58Z","updated_at":"2018-02-21T20:46:14Z","closed_at":null,"merged_at":null,"merge_commit_sha":"5145dbd52eddc4592fc58899c24b63a565df94aa","assignee":null,"assignees":[],"requested_reviewers":[],"requested_teams":[],"labels":[],"milestone":null,"commits_url":"https://api.github.com/repos/plotly/documentation/pulls/879/commits","review_comments_url":"https://api.github.com/repos/plotly/documentation/pulls/879/comments","review_comment_url":"https://api.github.com/repos/plotly/documentation/pulls/comments{/number}","comments_url":"https://api.github.com/repos/plotly/documentation/issues/879/comments","statuses_url":"https://api.github.com/repos/plotly/documentation/statuses/4dc97524950b42a2335be22f6592b03d28668fe6","head":{"label":"plotly:choropleth-docs","ref":"choropleth-docs","sha":"4dc97524950b42a2335be22f6592b03d28668fe6","user":{"login":"plotly","id":5997976,"avatar_url":"https://avatars2.githubusercontent.com/u/5997976?v=4","gravatar_id":"","url":"https://api.github.com/users/plotly","html_url":"https://github.com/plotly","followers_url":"https://api.github.com/users/plotly/followers","following_url":"https://api.github.com/users/plotly/following{/other_user}","gists_url":"https://api.github.com/users/plotly/gists{/gist_id}","starred_url":"https://api.github.com/users/plotly/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/plotly/subscriptions","organizations_url":"https://api.github.com/users/plotly/orgs","repos_url":"https://api.github.com/users/plotly/repos","events_url":"https://api.github.com/users/plotly/events{/privacy}","received_events_url":"https://api.github.com/users/plotly/received_events","type":"Organization","site_admin":false},"repo":{"id":18997629,"name":"documentation","full_name":"plotly/documentation","owner":{"login":"plotly","id":5997976,"avatar_url":"https://avatars2.githubusercontent.com/u/5997976?v=4","gravatar_id":"","url":"https://api.github.com/users/plotly","html_url":"https://github.com/plotly","followers_url":"https://api.github.com/users/plotly/followers","following_url":"https://api.github.com/users/plotly/following{/other_user}","gists_url":"https://api.github.com/users/plotly/gists{/gist_id}","starred_url":"https://api.github.com/users/plotly/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/plotly/subscriptions","organizations_url":"https://api.github.com/users/plotly/orgs","repos_url":"https://api.github.com/users/plotly/repos","events_url":"https://api.github.com/users/plotly/events{/privacy}","received_events_url":"https://api.github.com/users/plotly/received_events","type":"Organization","site_admin":false},"private":false,"html_url":"https://github.com/plotly/documentation","description":"Plotly's 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