To convert a DataFrame to a GeoDataFrame in Pandas, you can use the geopandas.GeoDataFrame constructor and provide the geometry column. Here's an example: import pandas as pd import geopandas as gpd from shapely
Then you could try this, first "conda activate geopandas" import geopandas as gp df = gp.read_file('Oregon.shp') df.to_file('Oregon_copy.shp') Just three lines to read and write a feature class... Of course you can do the usual Pandas dataframe manipul...
Open another code tab and let's use the Spark utils library provided by Microsoft to write the GeoPandas DataFrame as a GeoJSON file and save it in Azure Data Lake Gen 2. Unfortunately, copying the GeoPandas DataFrame directly from Synapse Notebook to Azure Data ...
to_file('Oregon_copy.shp') Just three lines to read and write a feature class... Of course you can do the usual Pandas dataframe manipulations on "df". Geopandas is not arcpy, so it won't be the same but it's nice to have alternatives when one thing does not ...
If you firstly set up an empty table in the file gedoatabase containing fields named as per your CSV file, you could insert the records from the pandas dataframe into you the file geodatabase table using an arcpy.da.InsertCursror - something like this: import pandas as pd i...
Solved! Go to Solution. arcpy python wkt Reply 2 Kudos All Posts Previous Topic Next Topic 1 Solution by jcarlson 02-16-2021 02:46 PM If you've got your data in a pandas dataframe, I'd definitely skip the export/import. Using GeoPandas and Shapely, alo...
# convert pandas dataframe to record array pivot_recarray = pivot.to_records(index=False) pivot_type = pivot_recarray.dtype.descr pivot_type_new = [(x[0], x[1].replace(x[1], "<i2")) for x in pivot_type] # change pivot record array data type to short integer pi...