结合 pandas 数据框和 ArcGIS 要素类

Question

I have a bit of a general question about the compatibility of Pandas dataframes and Arc featureclasses.

My current project is within ArcGIS and so I am mapping mostly with featureclasses. I am however, most familiar with using pandas to perform simple data analysis with tables. Therefore, I am attempting to work with dataframes for the most part, and then join their data to feature classes for final mapping using some key field common between sets.

Attempts:

1.I have come to find that arcpy AddJoin does not accept dfs.

2.I am currently trying convert df to csv and then do an Addjoin however I am unsure if this is supported and I far prefer the functionality of filtering dfs with "df.loc" etc.

3. Update cursor seems to be a good option, however, I am experiencing issues accessing the key field of the "row" in my loop to match records. I will post another question about this as it is a separate issue.

Which of these or other options is the best for this purpose?

Thanks!

Answer 1

Esri introduced something called Spatially Enabled DataFrame :

The Spatially Enabled DataFrame inserts a custom namespace called spatial into the popular Pandas DataFrame structure to give it spatial abilities. This allows you to use intutive, pandorable operations on both the attribute and spatial columns.

import arcpy
import pandas as pd

# important as it "enhances" Pandas by importing these classes
from arcgis.features import GeoAccessor, GeoSeriesAccessor

# from a shape file
df = pd.DataFrame.spatial.from_featureclass(r"data\hospitals.shp")

# from a map layer
project = arcpy.mp.ArcGISProject('CURRENT')
map = project.activeMap
first_layer = map.listLayers()[0]
layer_name = first_layer.name

df = pd.DataFrame.spatial.from_featureclass(layer_name)

# or directly by name
df = pd.DataFrame.spatial.from_featureclass("Streets")

# of if nested within a group layer (e.g. Buildings)
df = pd.DataFrame.spatial.from_featureclass("Buildings\Residential")

# save to shapefile
df.spatial.to_featureclass(location=r"c:\temp\residential_buildings.shp")

However, you have to use intermediate files if you go back and forth (to my knowledge). Although it's a bit tricky having geopandas installed along arcpy , it may be worth looking into (only) using geopandas .

IMHO, I would recommend that you avoid unnecessarily going back and forth between arcpy and pandas . Pandas allows to merge, join and concat dataframes. Or, you may be able to do everything in geopandas without needing to touch arcpy functions at all.