Sum Area Grouped By Attribute

[ChrisHolmes]

Hello everyone,

I have some data that looks like the attached pic. There's got to be an easy way to get a total area for each USE_CATEGORY and put the totals into a list or dictionary. Not sure if I need to maintain which total relates to which USE_CATEGORY. I don't need it for the current calculation I want to do, but may be worthwhile if I want to write it out to some external format later.

Thanks for any help/pointers.

[DanPatterson_Retired · Accepted solution]

summary statistics

[JoshuaBixby]

I agree with Dan, Summary Statistics is the first thing that comes to mind.  Since you mentioned putting "the totals into a list or dictionary," you could use a defaultdict:

from collections import defaultdict
use_areas = defaultdict(float)
fc = # path to feature class

with arcpy.da.SearchCursor(fc, ["USE_CATEGORY","SHAPE_Area"]) as cur:
    for use, area in cur:
        use_areas[use] += area‍‍‍‍‍‍‍

[ChrisHolmes]

Yes, summary statistics. I'm not sure why that didn't pop into my head as I've already used it previously. I think I was focused more on the list/dictionary. I'm working on using summary statistics now and trying to use in_memory tables. Once that's working I think I'll do it using the defaultdict, just for the learning. I'll update the thread as things progress.

Thanks all.

[JamesCrandall]

I'm surprised that Joshua didn't offer a pandas solution with its groupby function as well as a to_dict() --- the problem is with the limitations of FeatureClassToNumPyArray with some column types, but this may be something to consider.  This gets close but I don't think it's exactly what you are looking for.

fc = r'H:\MyfeatureClass'

#Create array
nparr = arcpy.da.FeatureClassToNumPyArray(fc, ['USE_CATEGORY','Shape_Area'])

#get array as pandas dataframe and populate the repeating values column
df = pandas.DataFrame(nparr,columns=['USE_CATEGORY','Shape_Area'])

#summarize as desired on shape area
df = df.groupby(by='USE_CATEGORY', as_index=True)['Shape_Area'].sum()

#make it a dictionary
myDictionary = df.to_dict()‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍

[DanPatterson_Retired]

James... numpy... did a split and count of a featureclass of mostly equal polygons.  The process is like df.groupby

The big difference is you call the da.SearchCursor as usual, the line 5 is the key, it is what the ArcGIS module uses extensively in its code as I posted in my last blog.

in_fc = r"C:\no_space\path\testdata.gdb\Carp_5x5"   # full 25 polygons

sc = arcpy.da.SearchCursor(in_fc, ['OBJECTID', 'Shape', 'Class'], explode_to_points=True)

arr = sc._as_narray()

un, idx, cnts = np.unique(arr['Class'], return_index=True, return_counts=True)

un
array(['A01', 'A02', 'A03', ..., 'E03', 'E04', 'E05'], 
      dtype='<U5')

idx
array([  0,   5,  10, ..., 109, 114, 119], dtype=int64)

cnts
array([5, 5, 5, ..., 5, 5, 5], dtype=int64)

result = np.asarray(list(zip(un, cnts)), dtype=[('Class', '<U5'), ('Counts', '<i4')])

result
array([('A01', 5), ('A02', 5), ('A03', 5), ..., ('E03', 5), ('E04', 5),
       ('E05', 5)], 
      dtype=[('Class', '<U5'), ('Counts', '<i4')])

result.tolist()
 
[('A01', 5),
 ('A02', 5),
 ('A03', 5),
 ('A04', 5),
 ('A05', 5),
 ('B01', 5),
 ('B02', 5),
 ('B03', 5),
 ('B04', 5),
 ('B05', 5),
 ('C01', 5),
 ('C02', 5),
 ('C03', 4),
 ('C03E', 4),
 ('C03N', 4),
 ('C03S', 4),
 ('C04', 5),
 ('C05', 5),
 ('D01', 5),
 ('D02', 5),
 ('D03', 5),
 ('D04', 5),
 ('D05', 5),
 ('E01', 5),
 ('E02', 5),
 ('E03', 5),
 ('E04', 5),
 ('E05', 5)]‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍‍

[JoshuaBixby]

I like pandas, and especially like that it is now bundled with ArcGIS, but one rub I have with it is the poor documentation compared to other Python documentation.  I find people new to Python struggle with the pandas documentation, unnecessarily so.  I know I could put my something where my mouth is and contribute to the docs myself, but it isn't a big enough priority to fit into my schedule for the time being.  In this case, a defaultdict works well and is a nice introduction to the extended data types in the collections module.

[ChrisHolmes]

What version of arcmap is pandas bundled?

I’m learning pandas right now and find the documentation tough. At least there’s stackexchange.

[JoshuaBixby]

Esri originally announced it would be 10.3.1, but it got pushed back to 10.4: What's new in ArcMap 10.4

[ChrisHolmes]

I've had no opportunity to date to look at doing this using dictionaries, but summary statistics is working great. So I think I'll just leave it at that.

Thanks everyone!