HeatMap fails silently on incompatible data type

import pandas as gpd
import folium
from folium.plugins import HeatMap

# loading the shapefile and adding it to the folium map
shp = gpd.read_file('./shapefiles/fortal118.shp')
shp.crs = "+proj=utm +zone=24 +ellps=WGS84 +datum=WGS84 +units=m +no_defs +south"
shp = shp.to_crs("+proj=longlat +ellps=WGS84 +datum=WGS84 +no_defs")

Map = folium.Map(location=[-3.731862, -38.526669], zoom_start=12, tiles='cartodbpositron')
folium.GeoJson(shp).add_to(Map)

# loading the data to use in order to make the heatmap
cases2011 = pd.read_csv('cases2011.txt', sep=" ", names=['day', 'month', 'lon', 'lat', 'label'], usecols=['lon', 'lat'])
cases2011['amount'] = np.random.randint(0, 100, size=len(cases2011))

# constructing the heatmap and adding it to the folium map
max_amount = float(cases2011['amount'].max())
hm_wide = HeatMap(zip(cases2011.lat.values, cases2011.lon.values, cases2011.amount.values),
                 min_opacity=0.1,
                 max_val=max_amount,
                 radius=17, blur=15,
                 max_zoom=10)
Map.add_child(hm_wide)
# showing the figure
Map

Problem description

The issue is that it was supposed to show a figure with the folium map, the shapefile and the heatmap generated. The heatmap is not displayed, just the folium map and the shapefile appears.

Expected Output

The expected output should be similar to the figure of this post tutorial https://alcidanalytics.com/p/geographic-heatmap-in-python

Output of folium.__version__

0.5.0

Could anyone help me with this issue, please?

Necessary data

shapefiles.zip cases2011.txt

[Conengmo]

We should add a validation step in the initialization of Heatmap that checks if the data argument is a valid type (iterable or array or maybe also pandas types?) and has a valid shape.

Does somebody want to make a PR with this?

[Conengmo]

Alright I found the problem, it’s with using zip. The Heatmap class cannot handle that and it stays a zip object in unpacking. Unfortunately it fails silently.

You can solve this by converting it into a list before creating Heatmap.

data = list(zip(cases2011.lat.values, cases2011.lon.values, cases2011.amount.values))
hm_wide = HeatMap(data)