arcgis.mapping.renderer.generate_renderer(???????)

275
3
05-24-2021 05:50 AM
HenriqueJoner
New Contributor II

Hello, 

I'm new has developer in esri products.

I'm having trouble with this method. I'm trying to create a chorolopeth map using esriClassifyNaturalBreaks, but the API reference doesn't mention any argument for the number of breaks, i found it in a video for other method (sdf.spatial.plot), the argument is "class_count=", and it works, i don't know why it is not in the documentation. But surprisenly the argument "method = ", does not work at all. No matter the value used it creates the same renderer. Am i doing something wrong here?

 

renderer_classed = arcgis.mapping.renderer.generate_renderer(geometry_type = 'Polygon',
sdf_or_series = sdf, 
render_type ='c',
colors = 'Reds',
method = 'esriClassifyNaturalBreaks',
field = 'media_10',
class_count = 5)

 

 

Which is the best way to create a renderer in python arcgis API?

 

Thanks

0 Kudos
3 Replies
HenriqueJoner
New Contributor II

Just for update this topic:

When using sdf.spatial.plot() i get the same result. Any method, same renderer...

sdf.spatial.plot(kind ='map',
                map_widget = mapa1,
                renderer_type = 'c',
                method = 'esriClassifyNaturalBreaks',
                col = 'media_10',
                class_count = 5,
                cmap = 'Reds',
                outline_color = [0,0,0,150],
                line_width = 0.5)

It always retrieve equal intervals...

0 Kudos
HenriqueJoner
New Contributor II

And additionaly, the very sample code from esri doesn't work has it should be:

https://developers.arcgis.com/python/guide/visualizing-data-with-the-spatially-enabled-dataframe/

If you try m4 sample code, you will realise that this method doesn't work at all:

df.spatial.plot(map_widget=m4,
               renderer_type='c',  # for class breaks renderer
               method='esriClassifyNaturalBreaks',  # classification algorithm
               class_count=20,  # choose the number of classes
               col='POPULATION',  # numeric column to classify
               cmap='prism',  # color map to pick colors from for each class
               alpha=0.7  # specify opacity
               )

You can change to any method here (e.g., esriClassifyQuantile), and you will always get equal intervals breaks. 

Now, the most strange thing is that to very sample code shows that there's no esriClassifyNaturalBreaks hapening there, has they show in the sample script, it is equal intervals....

cbs_list = []
cmap_list = []
for cb in class_breaks:
    print(cb.description)  # print the class break labels
    cbs_list.append(cb.classMaxValue)
    cmap_list.append([x/255.0 for x in cb.symbol.color])
7957.0 - 11659.315789473683
11659.315789473683 - 15361.631578947368
15361.631578947368 - 19063.947368421053
19063.947368421053 - 22766.263157894737
22766.263157894737 - 26468.57894736842
26468.57894736842 - 30170.894736842107
30170.894736842107 - 33873.21052631579
33873.21052631579 - 37575.52631578947
37575.52631578947 - 41277.84210526316
41277.84210526316 - 44980.15789473684
44980.15789473684 - 48682.47368421053
48682.47368421053 - 52384.78947368421
52384.78947368421 - 56087.10526315789
56087.10526315789 - 59789.42105263158
59789.42105263158 - 63491.73684210526
63491.73684210526 - 67194.05263157895
67194.05263157895 - 70896.36842105264
70896.36842105264 - 74598.68421052632
74598.68421052632 - 78301.0
78301.0 - 78301.0
0 Kudos
HenriqueJoner
New Contributor II

Now the question is, has someone had success using this Python API for choropleth maps with these methods? Please, show me how.

method                  Determines the classification method that was used to
                        generate class breaks.

                        Must be one of the following values:

                        + esriClassifyDefinedInterval
                        + esriClassifyEqualInterval
                        + esriClassifyGeometricalInterval
                        + esriClassifyNaturalBreaks
                        + esriClassifyQuantile
                        + esriClassifyStandardDeviation
                        + esriClassifyManual

 

0 Kudos