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System Error when exporting Spatially Enabled DataFrame to Feature Class

DarrenConly · 2021-04-07T22:07:27+00:00

Hi All, I'm trying to do the following: * Convert a non-spatial pandas dataframe to a spatial dataframe * Export the spatial dataframe to a feature class in an ESRI file geodatabase, based on the instructions provided in ESRI's Introduction to the Spatially Enabled DataFrame However, I get the error "SystemError:…

DarrenConly

Hi All,

I'm trying to do the following:

Convert a non-spatial pandas dataframe to a spatial dataframe
Export the spatial dataframe to a feature class in an ESRI file geodatabase, based on the instructions provided in ESRI's Introduction to the Spatially Enabled DataFrame

However, I get the error "SystemError: <da.funcInfo object at 0x0000029FA43C52A0> returned NULL without setting an error".

I googled the error and the only hits I got implied the issue has something to do with making a C extension. Do any of you have any insights on this?

Here's the full code for context:

out_fc_path = 'I:\\Projects\\Darren\\EmpInventory\\EmploymentInventory.gdb\\testrecs9581720210407_1435'

sdft = GeoAccessor.from_xy(master_df, fld_lat, fld_lon) # no issues here!

sdft.spatial.to_featureclass(location=out_fc_path)
Traceback (most recent call last):

  File "<ipython-input-29-2e5a93021399>", line 1, in <module>
    sdft.spatial.to_featureclass(location=out_fc_path)

  File "C:\Users\dconly\AppData\Local\ESRI\conda\envs\arcgispro-py3-dcmar21\lib\site-packages\arcgis\features\geo\_accessor.py", line 2122, in to_featureclass
    has_m=has_m)

  File "C:\Users\dconly\AppData\Local\ESRI\conda\envs\arcgispro-py3-dcmar21\lib\site-packages\arcgis\features\geo\_io\fileops.py", line 708, in to_featureclass
    arcpy.da.ExtendTable(fc, oidfld, array, join_dummy, append_only=False)

SystemError: <da.funcInfo object at 0x0000029FA43C52A0> returned NULL without setting an error

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Accepted answers

DarrenConly

I found the solution!

In trying to find a workaround, I discovered that you cannot export a spatial dataframe to a file or feature class if it contains categorical data types. To fix this, you must convert all categorical data types to string data type.

Example: if you have a column 'X' that is categorical, you must first convert to string data type by doing the following:

df['X'] = df['X'].astype('str')

I'm happy to have resolved this, and hope my solution is informative to others.

Cheers,

All comments

RoderickPerendy

Hello nzjs,

Does this function still work for you? I'm on Pro 3.0 and have a dataframe representing all the content within a group using the Group Object search method using search(query='type:web map', as_dict = True) and converting this to a dataframe. I then expand the 'results' key to additional columns with pd.series and it kicks out a ton of dtypes as objects. However when I run your function it doesn't do anything.

feralcatcolonist_old

@Anonymous User is this going to become a built-in for the API? I recently ran into this issue and am glad there's a workaround, but this seems to be a pretty significant defect.

Anonymous User

Thanks for posting the solution

jas_eagle

Darren, this led me in the right direction to solve similar issue. In my case I had a number of seemingly invalid data types, so this small function fixed it.

Cheers, John

def convert_dtypes_arcgis(df):
  # Convert dataframe dtypes which are not compatible with ArcGIS
  # Use builtin Pandas dtype conversion
  df = df.convert_dtypes(infer_objects=True)
  # Then str convert any remaining special object/category fields 
  for col in df.columns:
    # print(col, '/', df[col].dtype)
    if df[col].dtype == 'object' or df[col].dtype == 'category':
      df[col] = df[col].astype('str')
  # Return modified df
  return df

DarrenConly

I found the solution!

Example: if you have a column 'X' that is categorical, you must first convert to string data type by doing the following:

df['X'] = df['X'].astype('str')

I'm happy to have resolved this, and hope my solution is informative to others.

Cheers,

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