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I'm trying to add weights to my folium heatmap layer, but I can't figure out how to correctly implement this.

I have a dataframe with 3 columns: LAT, LON and VALUE. Value being the total sales of that location.

self.map = folium.Map([mlat, mlon], tiles=tiles, zoom_start=8)
locs = zip(self.data.LAT, self.data.LON, self.data.VALUE)
HeatMap(locs, radius=30, blur=10).add_to(self.map)

I tried to use the absolute sales values and I also tried to normalize sales/sales.sum(). Both give me similar results.

The problem is:

Heatmap shows stronger red levels for regions with more stores. Even if the total sales of those stores together is a lot smaller than sales of a distant and isolate large store.

Expected behaviour:

I would expect that the intensity of the heatmap should use the value of sales of each store, as sales was passed in the zip object to the HeatMap plugin.

Let's say I have 2 regions: A and B.
In region A I have 3 stores: 10 + 15 + 10 = 35 total sales.
In region B I have 1 big store: 100 total sales

I'd expect a greater intensity for region B than for region A. I noticed that a similar behaviour only occurs when the difference is very large (if I try 35 vs 5000000 then region B becomes more relevant).

My CSV file is just a random sample, like this:

LAT,LON,VALUE,DATE,DIFFLAT1,DIFFLON1
-22.4056,-53.6193,14,2010,0.0242,0.4505
-22.0516,-53.7025,12,2010,0.3137,0.6636
-22.3239,-52.9108,100,2010,0.0514,0.0002
-22.6891,-53.7424,6,2010,0.0002,0.7887
-21.8762,-53.6866,16,2010,0.7283,0.6180
-22.1861,-53.5353,11,2010,0.1420,0.2924
Lazaro Pinheiro Domiciano
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1 Answers1

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from folium import plugins
from folium.plugins import HeatMap

heat_df = df.loc[:,["lat","lon","weight"]]
map_hooray = folium.Map(location=[45.517999 ,-73.568184 ], zoom_start=12 )

Format: list of lists as well as lat, lon and weight

heat_data = heat_df.values.tolist()

Plot it on the map

HeatMap(heat_data,radius=13).add_to(map_hooray)

Save the map

map_hooray.save('heat_map.html')
Meghdad
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