In [1]:

import os
import folium

print(folium.__version__)

0.8.3+52.g2758dc7.dirty

Using `folium.colormap`¶

A few examples of how to use folium.colormap in choropleths.

Let's load a GeoJSON file, and try to choropleth it.

In [2]:

import json
import pandas as pd
import requests


url = 'https://raw.githubusercontent.com/python-visualization/folium/master/examples/data'
us_states = f'{url}/us-states.json'
US_Unemployment_Oct2012 = f'{url}/US_Unemployment_Oct2012.csv'

geo_json_data = json.loads(requests.get(us_states).text)
unemployment = pd.read_csv(US_Unemployment_Oct2012)

unemployment_dict = unemployment.set_index('State')['Unemployment']

Self-defined¶

You can build a choropleth in using a self-defined function. It has to output an hexadecimal color string of the form #RRGGBB or #RRGGBBAA.

In [3]:

def my_color_function(feature):
    """Maps low values to green and hugh values to red."""
    if unemployment_dict[feature['id']] > 6.5:
        return '#ff0000'
    else:
        return '#008000'

In [4]:

m = folium.Map([43, -100], tiles='cartodbpositron', zoom_start=4)

folium.GeoJson(
    geo_json_data,
    style_function=lambda feature: {
        'fillColor': my_color_function(feature),
        'color': 'black',
        'weight': 2,
        'dashArray': '5, 5'
    }
).add_to(m)

m.save(os.path.join('results', 'Colormaps_0.html'))

m

Out[4]:

StepColormap¶

But to help you define you colormap, we've embedded StepColormap in folium.colormap.

You can simply define the colors you want, and the index (thresholds) that correspond.

In [5]:

import branca.colormap as cm


step = cm.StepColormap(
    ['green', 'yellow', 'red'],
    vmin=3, vmax=10,
    index=[3, 4, 8, 10],
    caption='step'
)

step

Out[5]:

In [6]:

m = folium.Map([43, -100], tiles='cartodbpositron', zoom_start=4)

folium.GeoJson(
    geo_json_data,
    style_function=lambda feature: {
        'fillColor': step(unemployment_dict[feature['id']]),
        'color': 'black',
        'weight': 2,
        'dashArray': '5, 5'
    }
).add_to(m)

m.save(os.path.join('results', 'Colormaps_1.html'))

m

Out[6]:

If you specify no index, colors will be set uniformely.

In [7]:

cm.StepColormap(['r', 'y', 'g', 'c', 'b', 'm'])

Out[7]:

LinearColormap¶

But sometimes, you would prefer to have a continuous set of colors. This can be done by LinearColormap.

In [8]:

linear = cm.LinearColormap(
    ['green', 'yellow', 'red'],
    vmin=3, vmax=10
)

linear

Out[8]:

In [9]:

m = folium.Map([43, -100], tiles='cartodbpositron', zoom_start=4)

folium.GeoJson(
    geo_json_data,
    style_function=lambda feature: {
        'fillColor': linear(unemployment_dict[feature['id']]),
        'color': 'black',
        'weight': 2,
        'dashArray': '5, 5'
    }
).add_to(m)

m.save(os.path.join('results', 'Colormaps_2.html'))

m

Out[9]:

Again, you can set the index if you want something irregular.

In [10]:

cm.LinearColormap(
    ['red', 'orange', 'yellow', 'green'],
    index=[0, 0.1, 0.9, 1.0]
)

Out[10]:

If you want to transform a linear map into a step one, you can use the method to_step.

In [11]:

linear.to_step(6)

Out[11]:

You can also use more sophisticated rules to create the thresholds.

In [12]:

linear.to_step(
    n=6,
    data=[30.6, 50, 51, 52, 53, 54, 55, 60, 70, 100],
    method='quantiles',
    round_method='int'
)

Out[12]:

And the opposite is also possible with to_linear.

In [13]:

step.to_linear()

Out[13]:

Build-in¶

For convenience, we provide a (small) set of built-in linear colormaps, in folium.colormap.linear.

In [14]:

cm.linear.OrRd_09

Out[14]:

You can also use them to generate regular StepColormap.

In [15]:

cm.linear.PuBuGn_09.to_step(12)

Out[15]:

Of course, you may need to scale the colormaps to your bounds. This is doable with .scale.

In [16]:

cm.linear.YlGnBu_09.scale(3, 12)

Out[16]:

In [17]:

cm.linear.RdGy_11.to_step(10).scale(5, 100)

Out[17]:

At last, if you want to check them all, simply ask for linear in the notebook.

In [18]:

cm.linear

Out[18]:

viridis
Pastel1_03
Pastel1_05
Pastel1_04
Pastel1_07
YlOrRd_04
Pastel1_09
Pastel1_08
Spectral_07
RdYlBu_05
PuBuGn_03
Set1_08
PuBuGn_05
PuBuGn_04
PuBuGn_07
PuBuGn_06
PuBuGn_09
PuBuGn_08
YlOrBr_04
YlOrBr_05
Set1_07
YlOrBr_03
Set1_05
YlOrRd_03
PuOr_06
PuOr_07
PuOr_04
PuOr_05
PuOr_03
Purples_09
Set2_06
RdYlBu_11
PuOr_08
PuOr_09
Paired_03
RdBu_03
RdYlBu_10
Paired_07
Paired_06
Paired_05
Paired_04
Paired_09
Paired_08
RdGy_03
PiYG_04
Accent_03
BuGn_08
BuGn_09
BuGn_04
BuGn_05
BuGn_06
BuGn_07
BuGn_03
YlGnBu_07
YlGnBu_06
YlGnBu_05
YlGnBu_04
YlGnBu_03
RdBu_06
RdBu_05
RdBu_04
Accent_08
RdBu_09
RdBu_08
Set2_04
YlGnBu_09
YlGnBu_08
Blues_08
Blues_09
RdPu_09
RdPu_08
Set3_07
Set3_06
RdPu_05
RdPu_04
RdPu_07
RdPu_06
Blues_06
Blues_07
RdPu_03
Blues_05
Paired_10
Paired_11
Paired_12
PuBu_06
PuBu_07
PuBu_04
PuBu_05
PuRd_05
PuBu_03
PuRd_07
PuRd_06
PuRd_09
PuRd_08
Set2_07
PuBu_08
PuBu_09
RdBu_10
RdBu_11
Accent_06
Set3_03
Set3_05
Set3_12
Set3_10
Set3_04
RdGy_11
RdGy_10
Set1_03
Set1_09
Set3_09
BuPu_08
BuPu_09
RdYlGn_11
Blues_03
Set2_05
BuPu_03
BuPu_06
BuPu_07
BuPu_04
BuPu_05
Accent_04
YlOrRd_05
YlOrBr_08
Oranges_08
Oranges_09
Oranges_06
Oranges_07
Oranges_04
YlOrBr_09
Oranges_03
YlOrBr_06
Dark2_06
Blues_04
YlOrBr_07
RdYlGn_05
Set3_08
YlOrRd_06
Dark2_03
Accent_05
RdYlGn_08
RdYlGn_09
PuOr_11
YlOrRd_07
Spectral_11
RdGy_08
RdGy_09
RdGy_06
RdGy_07
RdGy_04
RdGy_05
RdYlGn_04
PiYG_09
RdYlGn_06
RdYlGn_07
Spectral_04
Spectral_05
Spectral_06
PiYG_08
Set2_03
Spectral_03
Reds_08
Set1_04
Spectral_08
Spectral_09
Set2_08
Reds_09
Greys_07
Greys_06
Greys_05
Greys_04
Greys_03
PuOr_10
Accent_07
Reds_06
Greys_09
Greys_08
Reds_07
RdYlBu_08
RdYlBu_09
BrBG_09
BrBG_08
BrBG_07
BrBG_06
BrBG_05
BrBG_04
BrBG_03
PiYG_06
Reds_03
Set3_11
Set1_06
PuRd_03
PiYG_07
RdBu_07
Pastel1_06
Spectral_10
PuRd_04
OrRd_03
PiYG_03
Oranges_05
OrRd_07
OrRd_06
OrRd_05
OrRd_04
Reds_04
Reds_05
OrRd_09
OrRd_08
BrBG_10
BrBG_11
PiYG_05
YlOrRd_08
GnBu_04
GnBu_05
GnBu_06
GnBu_07
Purples_08
GnBu_03
Purples_06
Purples_07
Purples_04
Purples_05
GnBu_08
GnBu_09
YlOrRd_09
Purples_03
RdYlBu_04
PRGn_09
PRGn_08
PRGn_07
PRGn_06
PRGn_05
PRGn_04
PRGn_03
RdYlBu_06
RdYlGn_10
YlGn_08
YlGn_09
RdYlBu_07
PiYG_10
PiYG_11
YlGn_03
YlGn_04
YlGn_05
YlGn_06
YlGn_07
Dark2_05
Dark2_04
Dark2_07
Pastel2_03
Pastel2_04
Pastel2_05
Pastel2_06
Pastel2_07
Pastel2_08
RdYlBu_03
Dark2_08
RdYlGn_03
PRGn_11
Greens_08
Greens_09
Greens_06
Greens_07
Greens_04
Greens_05
PRGn_10
Greens_03

Draw a `ColorMap` on a map¶

By the way, a ColorMap is also a Folium Element that you can draw on a map.

In [19]:

m = folium.Map(tiles='cartodbpositron')

colormap = cm.linear.Set1_09.scale(0, 35).to_step(10)
colormap.caption = 'A colormap caption'
m.add_child(colormap)

m.save(os.path.join('results', 'Colormaps_3.html'))

m

Out[19]:

Using folium.colormap¶