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import os
import folium
print(folium.__version__)
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import json
import pandas as pd
us_states = os.path.join('data', 'us-states.json')
US_Unemployment_Oct2012 = os.path.join('data', 'US_Unemployment_Oct2012.csv')
geo_json_data = json.load(open(us_states))
unemployment = pd.read_csv(US_Unemployment_Oct2012)
unemployment_dict = unemployment.set_index('State')['Unemployment']
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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'
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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
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import branca.colormap as cm
step = cm.StepColormap(['green', 'yellow', 'red'],
vmin=3, vmax=10, index=[3, 4, 8, 10],
caption='step')
step
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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
If you specify no index, colors will be set uniformely.
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cm.StepColormap(['r', 'y', 'g', 'c', 'b', 'm'])
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linear = cm.LinearColormap(['green', 'yellow', 'red'],
vmin=3, vmax=10)
linear
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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
Again, you can set the index if you want something irregular.
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cm.LinearColormap(['red', 'orange', 'yellow', 'green'],
index=[0, 0.1, 0.9, 1.0])
If you want to transform a linear map into a step one, you can use the method to_step.
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linear.to_step(6)
You can also use more sophisticated rules to create the thresholds.
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linear.to_step(
n=6,
data=[30.6, 50, 51, 52, 53, 54, 55, 60, 70, 100],
method='quantiles',
round_method='int'
)
And the opposite is also possible with to_linear.
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step.to_linear()
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cm.linear.OrRd
You can also use them to generate regular StepColormap.
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cm.linear.PuBu.to_step(12)
Of course, you may need to scale the colormaps to your bounds. This is doable with .scale.
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cm.linear.YlGn.scale(3, 12)
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cm.linear.RdGy.to_step(10).scale(5, 100)
At last, if you want to check them all, simply ask for linear in the notebook.
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cm.linear
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m = folium.Map(tiles='cartodbpositron')
colormap = cm.linear.Set1.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
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