将具有 featurecollection 的 pandas 列转换为 GeoJSON

Question

I downloaded a CSV that contains a column which has a GeoJSON format, and imported it as a pandas dataframe. How can I convert this to a GeoJSON (.geojson)? I have about 10,000 rows, each with information as shown below:

This is an example of a cell in the column: {"type":"FeatureCollection","features":[{"type":"Feature","geometry":{"type":"Polygon","coordinates":[[[-0.0903517,9.488375],[-0.0905786,9.488523],[-0.0909767,9.48913],[-0.09122,9.4895258],[-0.0909733,9.4901503],[-0.0908833,9.4906802],[-0.0906984,9.4905612],[-0.0907146,9.4898184],[-0.090649,9.4895175],[-0.0907516,9.489142],[-0.0906146,9.4889654],[-0.0903517,9.488375]]]},"properties":{"pointCount":"11","length":"502.9413","area":"8043.091133117676"}}]}

Overview of my pandas dataframe print now:                             site_registration_gps_area  ...                   geometry
11    {"type":"FeatureCollection","features":[{"type...  ...  POINT (-76.75880 2.38031)
14    {"type":"FeatureCollection","features":[{"type...  ...  POINT (-76.73718 2.33163)
40    {"type":"FeatureCollection","features":[{"type...  ...   POINT (-0.15727 9.69560)
42    {"type":"FeatureCollection","features":[{"type...  ...   POINT (-0.11686 9.65522)
44    {"type":"FeatureCollection","features":[{"type...  ...   POINT (-0.10379 9.65226)

Answer 1

I would suggest to use GeoPandas for this task. The simplest solution would be to read your CSV file directly with GeoPandas using a GeoDataFrame . If you do this you need something like this:

import geopandas as gpd

# read the CSV file into a GeoDataFrame
gdf = gpd.read_file('myFile.csv')

# convert the GeoDataFrame to a geojson object
geo_json = gdf.to_json()

# however if the objects become very big, store the GeoDataFrame to a .geojson file
gdf.to_file('path', driver='GeoJSON')

However, if you work with the DataFrame from Pandas you can convert it to a GeoDataFrame and then use the same steps as in the above snippet.

import pandas as pd
import geopandas as gpd

# your code here ...

# extract the geojson column as a list 
geo_j_list = df['geometry'].tolist()

# temporary list for GeoDataFrames
gdfs = []

# iterate over the geojson objects in the list
for geom in geo_j_list:
    gdfs.append(gpd.GeoDataFrame.from_features(geom['features']))

# merge the list of GeoDataFrames into one
gdf = gpd.GeoDataFrame(pd.concat(gdfs, ignore_index=True))

# convert the gdf to a json object
geo_json = gdf.to_json()

# store the gdf in a geojson file
gdf.to_file('path', driver='GeoJSON')