In [1]:
import pandas as pd
import json
import sys
sys.path.append('..')
import folium
print (folium.__file__)
print (folium.__version__)
Let's load a GeoJSON file, and try to choropleth it.
In [2]:
geo_json_data = json.load(open('us-states.json'))
unemployment = pd.read_csv('./US_Unemployment_Oct2012.csv')
unemployment_dict = unemployment.set_index('State')['Unemployment']
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
Out[4]:
In [5]:
import folium.colormap as cm
In [6]:
step = cm.StepColormap(['green','yellow','red'], vmin=3., vmax=10., index=[3,4,8,10], caption='step')
step
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In [7]:
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
Out[7]:
If you specify no index, colors will be set uniformely.
In [8]:
cm.StepColormap(['r','y','g','c','b','m'])
Out[8]:
In [9]:
linear = cm.LinearColormap(['green','yellow','red'], vmin=3., vmax=10.)
linear
Out[9]:
In [10]:
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
Out[10]:
Again, you can set the index if you want something irregular.
In [11]:
cm.LinearColormap(['red','orange', 'yellow','green'], index=[0,0.1,0.9,1.])
Out[11]:
If you want to transform a linear map into a step one, you can use the method to_step.
In [12]:
linear.to_step(6)
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You can also use more sophisticated rules to create the thresholds.
In [13]:
linear.to_step(6,
data=[30.6, 50, 51, 52, 53, 54, 55, 60, 70, 100],
method='quantiles',
round_method='int')
Out[13]:
And the opposite is also possible with to_linear.
In [14]:
step.to_linear()
Out[14]:
In [15]:
cm.linear.OrRd
Out[15]:
You can also use them to generate regular StepColormap.
In [16]:
cm.linear.PuBu.to_step(12)
Out[16]:
Of course, you may need to scale the colormaps to your bounds. This is doable with .scale.
In [17]:
cm.linear.YlGn.scale(3,12)
Out[17]:
In [18]:
cm.linear.RdGy.to_step(10).scale(5,100)
Out[18]:
At last, if you want to check them all, simply ask for linear in the notebook.
In [19]:
cm.linear
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By the way, a ColorMap is also a Folium Element that you can draw on a map.
In [20]:
m = folium.Map(tiles='cartodbpositron')
colormap = cm.linear.Set1.scale(0,35).to_step(10)
colormap.caption = 'A colormap caption'
m.add_children(colormap)
m
Out[20]: