nav[aria-label="Primary Navigation"] { padding: 0; & ul { list-style: none; width: 100%; display: flex; flex-direction: row; justify-content: start; align-items: start; gap: 30px; padding: 0; & li { margin: 0; } & ul li { list-style: none; } } }

SpatialDataFrame has been deprecated

artzaifman

I receive following warning after this statement is run: sdf = features.SpatialDataframe(df)

opt/anaconda3/lib/python3.7/site-packages/arcgis/features/_data/geodataset/geodataframe.py:221: UserWarning: SpatialDataFrame has been deprecated.  Please switch to the GeoAccessor/GeoSeriesAccessor.   warnings.warn("SpatialDataFrame has been deprecated.  Please switch to the GeoAccessor/GeoSeriesAccessor.")

What is the correct way to create an 'sdf' now?

Encuentra más publicaciones etiquetadas con

Accepted answers

Egge-Jan_Pollé

Hi art zaifman,

The answer to your question might be found here: Introduction to the Spatially Enabled DataFrame | ArcGIS for Developers

New at version 1.5, the Spatially Enabled DataFrame is an evolution of the SpatialDataFrame object that you may be familiar with. While the SDF object is still avialable for use, the team has stopped active development of it and is promoting the use of this new Spatially Enabled DataFrame pattern. The SEDF provides you better memory management, ability to handle larger datasets and is the pattern that Pandas advocates as the path forward.

HTH,

Egge-Jan

All comments

artzaifman

Continuing to add to this thread since it may help other newbies to arcGIS Pro like like me!

Discovered that sdf.spatial.plot() will fail to render (without generation an error) if it encounters NaN values.

Here's snippet to remove NaNs from SEDF:

sdf = GeoAccessor.from_xy(df, 'x', 'y', sr=102100) # 102100 is necessary to render using sdf.spatial.plot() method

...

sdf[~sdf['SHAPE'].apply(lambda r: numpy.isnan(r['x']) or numpy.isnan(r['y']))] # drop NaNs which cause plot to silently fail

artzaifman

Found reason:

SEDF which works =

{'x': -13657899.64491753,  'y': 5749953.6899396395,  'spatialReference': {'wkid': 102100, 'latestWkid': 3857}}

SEDF which doesn't =

{'x': -13657899.64491753,  'y': 5749953.689939638,  'spatialReference': {'wkid': 4326}}

artzaifman

Related to the issues above, is it possible to use sdf.spatial.plot(map_widget=...) on an SEDF derived from a regular panda DF where the SEDF was NOT created with import_data() method? The SEDF was instead created as follows: sdf = GeoAccessor.from_xy(df, 'x', 'y')

artzaifman

from pyproj import Proj, transform

print(transform(Proj('epsg:4326'), Proj('epsg:3857'), 45.810, -122.691)) # longitude first, latitude second.

(-13657899.64491753, 5749953.689939638)

artzaifman

The points are mapped correctly and thank you again!

Egge-Jan_Pollé

... so that would be this WKID:102100/EPSG:3857 thing, as I mentioned above.

DanPatterson_Retired

webby stuff is usually in a Web Mercator projection

Egge-Jan_Pollé

Hi art zaifman,

Always happy to help 🙂 If you consider your initial question being answered you might consider to 'close the call' by marking my answer as correct.

Regarding your follow-up question: I guess this has something to do with the use of different coordinate systems being used. It looks like your input latitude and longitude are in WGS84 (EPSG:4326) whereas the coordinates in the SHAPE column are - most probably - in EPSG:3857. (EPSG:3857 is a Spherical Mercator projection coordinate system popularized by web services such as Google and later OpenStreetMap, and also being used by Esri, with WKID:102100).

I guess the points do appear in the right location when plotted on the map, don't they?

BR,

Egge-Jan

artzaifman

Are these UTM coordinates?

Thanks.

artzaifman

It does help and thank you for the rapid reply, Egge-Jan!

Short follow-up question: is there a description of the method in which GIS().content.import_data(panda data frame containing lat, lon columns) populates the SHAPE column? Main question is why are the 'x, y' values in the SHAPE column so different from the original 'latitude, longitude' values

Egge-Jan_Pollé

Hi art zaifman,

The answer to your question might be found here: Introduction to the Spatially Enabled DataFrame | ArcGIS for Developers

New at version 1.5, the Spatially Enabled DataFrame is an evolution of the SpatialDataFrame object that you may be familiar with. While the SDF object is still avialable for use, the team has stopped active development of it and is promoting the use of this new Spatially Enabled DataFrame pattern. The SEDF provides you better memory management, ability to handle larger datasets and is the pattern that Pandas advocates as the path forward.

HTH,

Egge-Jan

Únete a la Conversación

Los miembros registrados pueden publicar, seguir actualizaciones y más. ¿Nuevo aquí? Regístrate gratis.

Enlaces Rápidos

Community Help
Find useful guides, FAQs, and documents to help you navigate and make the most of Esri Community.