How to make a choropleth map with a slider using Plotly?

Question

I'm recreating the example choropleth and trying to add a slider that, when dragged, would change from year to year. Another user asked a similar question but they didn't receive a reply. I did some more searching and found an example where the user generated random values for the additional years and created a slider but it's in JavaScript and I'm not sure how to translate it into Python.

Here's the code in JavaScript:

Plotly.d3.csv('https://raw.githubusercontent.com/plotly/datasets/master/2011_us_ag_exports.csv', function(err, rows){
  function unpack(rows, key) {
    return rows.map(function(row) { return row[key]; });
  }

  var randomize = z => z.map(d => Math.pow(Math.random(), 2) * 30000);
  var data = unpack(rows, 'total exports');
  var frames = [{
    data: [{z: unpack(rows, 'total exports')}],
    traces: [0],
    name: '1990',
    layout: {title: '1990 US Agriculture Exports by State'}
  }, {
    data: [{z: randomize(data)}],
    traces: [0],
    name: '1995',
    layout: {title: '1995 US Agriculture Exports by State'}
  }, {
    data: [{z: randomize(data)}],
    traces: [0],
    name: '2000',
    layout: {title: '2000 US Agriculture Exports by State'}
  }, {
    data: [{z: randomize(data)}],
    traces: [0],
    name: '2005',
    layout: {title: '2005 US Agriculture Exports by State'}
  }]

  var data = [{
    type: 'choropleth',
    locationmode: 'USA-states',
    locations: unpack(rows, 'code'),
    z: unpack(rows, 'total exports'),
    text: unpack(rows, 'state'),
    zmin: 0,
    zmax: 17000,
    colorscale: [
      [0, 'rgb(242,240,247)'], [0.2, 'rgb(218,218,235)'],
      [0.4, 'rgb(188,189,220)'], [0.6, 'rgb(158,154,200)'],
      [0.8, 'rgb(117,107,177)'], [1, 'rgb(84,39,143)']
    ],
    colorbar: {
      title: 'Millions USD',
      thickness: 0.2
    },
    marker: {
      line:{
        color: 'rgb(255,255,255)',
        width: 2
      }
    }
  }];


  var layout = {
    title: '1990 US Agriculture Exports by State',
    geo:{
      scope: 'usa',
      showlakes: true,
      lakecolor: 'rgb(255,255,255)'
    },
    xaxis: {autorange: false},
    yaxis: {autorange: false},
    sliders: [{
      currentvalue: {
        prefix: 'Year: ',
      },
      steps: frames.map(f => ({
        label: f.name,
        method: 'animate',
        args: [[f.name], {frame: {duration: 0}}]
      }))
    }]
  };

  Plotly.plot('graph', {
    data: data,
    layout: layout,
    frames: frames,
    config: {showLink: false}
  });
});

Is there a way to do this in Python?

Answer 1

The code below is virtually a trimmed down version of the choropleth example for Python and the sliders code.

Randomized data is created based on the first data and each slider entry shows a different part of the data list.

import pandas as pd
import plotly
import numpy as np

plotly.offline.init_notebook_mode()
df = pd.read_csv('https://raw.githubusercontent.com/plotly/datasets/master/2011_us_ag_exports.csv')

data = [dict(type='choropleth',
             locations = df['code'].astype(str),
             z=df['total exports'].astype(float),
             locationmode='USA-states')]

# let's create some additional, random data
for i in range(5):
    data.append(data[0].copy())
    data[-1]['z'] = data[0]['z'] * np.random.rand(*data[0]['z'].shape)

# let's create the steps for the slider
steps = []
for i in range(len(data)):
    step = dict(method='restyle',
                args=['visible', [False] * len(data)],
                label='Year {}'.format(i + 1980))
    step['args'][1][i] = True
    steps.append(step)

sliders = [dict(active=0,
                pad={"t": 1},
                steps=steps)]    
layout = dict(geo=dict(scope='usa',
                       projection={'type': 'albers usa'}),
              sliders=sliders)

fig = dict(data=data, 
           layout=layout)
plotly.offline.iplot(fig)