ArcGIS API for Python Spatially Enabled Data Frame broken with datetime fields

[BenjaminSperry1]

I am trying to create a Spatially Enabled Data Frame object from a FeatureLayer object using the ArcGIS API for python version 1.5.3 and pandas version 0.24.1. When I use web layers that don't have date fields it works fine, but as soon as it has a date field it stops working and I get the following error:

Exception: Could not load the dataset: dtype '<class 'datetime.datetime'>' not understood‍

I copied the code directly from the Introduction to the Spatially Enabled Data Frame guide page and just substituted the item id for one of my own web layers. Here is my code:

from arcgis import GIS
gis = GIS("https://arcgis.com", ***, ***)
item = gis.content.get('The item id')
flayer = item.layers[0]

# create a Spatially Enabled DataFrame object
sdf = pd.DataFrame.spatial.from_layer(flayer)
sdf.head()‍‍‍‍‍‍‍‍

Any ideas? Has anyone else run into this problem?

[DanPatterson_Retired]

you might want to file an issue on their GitHub site as well

GitHub - Esri/arcgis-python-api: Documentation and samples for ArcGIS API for Python 

[MaxMarno]

There seems to be an underlying conflict between numpy and pandas... at least based on some forum crawling.

I was able to remedy the error by rolling back to pandas 0.23.4

Good luck!

[WightmanAdmin]

This is a shame, especially since they deprecated the spatial dataframe and replaced it with the spatially enabled dataframe. Not only is it less idiomatic, but it produces this error (while the original SDF does not).

[RobertWeber]

I ran into this issue.  Oddly enough the tool I have makes edits to a service and it fails if I start with an empty service or one that does not contain a feature that was created in AGOL or Pro.  Once I add a point that was created in AGOL or Pro I do not get the error anymore.  Not ideal.

[Anonymous User]

This issue has been fixed in the  latest version of ArcGIS API for Python 1.8.3.  To verify, you could create an anaconda environment using the following command:

conda create -n arcgis183

activate arcgis183

conda install -c esri arcgis

Then launch jupyter notebook in the desired directory.

code to verify:

from arcgis.gis import GIS
from arcgis.features import GeoAccessor, GeoSeriesAccessor
gis = GIS("https://geosaurus.maps.arcgis.com", "arcgis_python", "P@ssword123")

item=gis.content.get('d15eba5e9fe54a968e272c32d8e58e1f') #item has Date field
data = item.tables[0]
sdf = pd.DataFrame.spatial.from_layer(data)
sdf.head()

@PriyankaTuteja