How to break long list of geographic coordinates by latitude and longitude?

October 26, 2022

I have the following list of geographic coordinates organize in 2 mains blocks corresponding to 2 polygons :

 [[[31.547836, -103.7842], [31.639685, -104.03722], 
 [32.051894, -104.22097], [32.082813, -104.20363],
 [32.195333, -104.10359], [32.398168, -103.66786],
 [32.224538, -103.48232], [31.977848, -103.28086],
 [31.8019236, -103.30381], [31.688412, -103.482903],
 [31.607474, -103.62303]],
 [[31.582053, -101.93924], [31.585542, -102.16106],
 [31.6131197, -102.24417], [31.661732, -102.2972],
 [32.0562417, -102.28902], [32.4380094, -101.97873],
 [32.438598, -101.94766], [32.435146, -101.83021],
 [32.4000907, -101.78283], [31.905481, -101.73379],
 [31.781019, -101.72468], [31.650047, -101.71616],
 [31.6497171, -101.71621], [31.583703, -101.80637]]]

I would like to break this list in 2 dataframes (corresponding to the 2 blocks delimiter by double "[") with latitude and longitude columns.

Ex : first dataframe df :

    latitude   longitude 
    31.547836  -103.7842
    ...             ...

Second one df 1 :

    latitude   longitude 
    31.582053  -101.93924
    ...             ...

>Solution :

Try this:

import pandas as pd

df1 = pd.DataFrame(lst[0], columns=['latitude', 'longitude'])
df2 = pd.DataFrame(lst[1], columns=['latitude', 'longitude'])

print(df1)
print(df2)

Output:

# => df1
     latitude   longitude
0   31.547836 -103.784200
1   31.639685 -104.037220
2   32.051894 -104.220970
3   32.082813 -104.203630
4   32.195333 -104.103590
5   32.398168 -103.667860
6   32.224538 -103.482320
7   31.977848 -103.280860
8   31.801924 -103.303810
9   31.688412 -103.482903
10  31.607474 -103.623030

# => df2
     latitude  longitude
0   31.582053 -101.93924
1   31.585542 -102.16106
2   31.613120 -102.24417
3   31.661732 -102.29720
4   32.056242 -102.28902
5   32.438009 -101.97873
6   32.438598 -101.94766
7   32.435146 -101.83021
8   32.400091 -101.78283
9   31.905481 -101.73379
10  31.781019 -101.72468
11  31.650047 -101.71616
12  31.649717 -101.71621
13  31.583703 -101.80637