I have a spatially-enabled dataframe with 16 columns:
sedf.columns
Index(['issuedDate', 'weatherType', 'warningLikelihood', 'warningLevel',
'warningStatus', 'warningHeadline', 'whatToExpect', 'warningId',
'warningVersion', 'warningFurtherDetails', 'modifiedDate',
'validFromDate', 'affectedAreas', 'warningImpact', 'validToDate',
'SHAPE'],
dtype='object')
sample:
>>> sedf.iloc[0]
issuedDate 2023-12-05T10:15:10Z
weatherType [RAIN]
warningLikelihood 1
warningLevel YELLOW
warningStatus ISSUED
warningHeadline Heavy rain is likely to bring some travel disr...
whatToExpect [There is a small chance that homes and busine...
warningId 9ac0f4c2-09ab-41ce-ba8a-6e6ea770e6d3
warningVersion 1.0
warningFurtherDetails Rain is expected to arrive during Wednesday ev...
modifiedDate 2023-12-05T10:15:10Z
validFromDate 2023-12-07T00:00:00Z
affectedAreas [{'regionName': 'South West England', 'regionC...
warningImpact 3
validToDate 2023-12-07T15:00:00Z
SHAPE {'rings': [[(-2.4005, 51.0966), (-2.2687, 50.9...
Name: 0, dtype: object
when I run sedf.to_featureclass("path/to/gdb/featureclass"), the resulting featureclass only has 4 of these columnd: SHAPE, modifiedDate, validFromDate, validToDate.
Exporting the same data from geopandas to geojson or GPKG works fine.
I've tried using sanitize_columns=False on the SEDF but it makes no difference.
Does anyone know what might be causing the loss of this attribute data and how I can keep it when saving to featureclass/GDB?
Solved! Go to Solution.
In the past, I remember to_featureclass failing if you had any Python lists in your dataframe. I'm not sure if this is a problem in your case (only noting it because I see lists in the screen).
In the past, I remember to_featureclass failing if you had any Python lists in your dataframe. I'm not sure if this is a problem in your case (only noting it because I see lists in the screen).
That was it, thank you!
I converted the lists to strings and now it works as expected.