So I have a geojson file that is part of a bigger collection, but I'm using this one to test something out.
I have no problem in reading the geojson:
import pandas as pd
import geopandas as gpd
import json
import plotly.express as px
with open('/content/cartaxo.geojson') as response:
county = json.load(response)
Running county["features"][0] returns
{'geometry': {'coordinates': [[[[-56497.98620000016, -56294.48699999973],
[-56538.73869999964, -56197.87010000087],
[-56587.94560000021, -56286.044600000605],
[-56616.04860000033, -56336.403999999166],
[-56627.22609999962, -56356.43209999986],
[-56643.096699999645, -56384.87030000053],
[-56658.49230000004, -56412.45839999989],
[-56674.48390000034, -56442.55460000038],
[-56690.07959999982, -56471.9068],
[-56658.87579999957, -56473.55159999989],
[-56580.009200000204, -56474.78099999949],
[-56546.001299999654, -56474.57569999993],
[-56531.39639999997, -56474.36959999986],
[-56473.800599999726, -56470.95419999957],
[-56473.39460000023, -56468.96419999935],
[-56471.68439999968, -56463.26009999961],
[-56442.968500000425, -56420.05379999988],
[-56441.460500000045, -56419.04780000076],
[-56449.69900000002, -56399.976800000295],
[-56456.69560000021, -56383.77690000087],
[-56462.82129999995, -56370.92889999971],
[-56488.1409, -56317.830000000075],
[-56497.98620000016, -56294.48699999973]]]],
'type': 'MultiPolygon'},
'properties': {'BGRI2021': '14060900412',
'CC': '06',
'DT': '14',
'DT21': '14',
'DTMN21': '1406',
'DTMNFR21': '140609',
'DTMNFRSEC21': '140609004',
'N_AGREGADOS': 0,
'N_ALOJAMENTOS': 1,
'N_EDIFICIOS_CLASSICOS': 1,
'N_INDIVIDUOS_RESIDENT': 0,
'OBJECTID': 1,
'OBJECTID_1': 149773,
'SEC': '004',
'SECNUM21': '004',
'SECSSNUM21': '00412',
'SS': '12',
'SSNUM21': '12',
'fr': '09'},
'type': 'Feature'}
I then read the geojson file into a dataframe and drop the geometry column
df = gpd.read_file('/content/cartaxo.geojson')
df = df.drop(['geometry'], axis=1)
Running df.info() returns the structure of the dataframe as expected
<class 'geopandas.geodataframe.GeoDataFrame'>
RangeIndex: 514 entries, 0 to 513
Data columns (total 19 columns):
# Column Non-Null Count Dtype
--- ------ -------------- -----
0 OBJECTID 514 non-null int64
1 BGRI2021 514 non-null object
2 DT21 514 non-null object
3 DTMN21 514 non-null object
4 DTMNFR21 514 non-null object
5 DTMNFRSEC21 514 non-null object
6 SECNUM21 514 non-null object
7 SSNUM21 514 non-null object
8 SECSSNUM21 514 non-null object
9 OBJECTID_1 514 non-null int64
10 DT 514 non-null object
11 CC 514 non-null object
12 fr 514 non-null object
13 SEC 514 non-null object
14 SS 514 non-null object
15 N_EDIFICIOS_CLASSICOS 514 non-null int64
16 N_ALOJAMENTOS 514 non-null int64
17 N_AGREGADOS 514 non-null int64
18 N_INDIVIDUOS_RESIDENT 514 non-null int64
dtypes: int64(6), object(13)
memory usage: 76.4+ KB
Since the only unique element for each county is DTMN21 I will use that to make my map:
fig = px.choropleth_mapbox(df, geojson=county,locations='DTMN21',featureidkey='properties.DTMN21',color='N_INDIVIDUOS_RESIDENT',
color_continuous_scale="Blues",
mapbox_style="open-street-map",
zoom=7,
opacity=1,
height=900
)
fig.show()
However what I get in return is a blank map with no added layers to it as you can see in the image.

I've already tried everything to sort this out, as much as my knowledge can, and I can't figure it out. Any help with be much appreciated.
Disclaimer: The solution will be used in a non-for-profit NGO project. No commercial use will be made of the solution presented
