How can you convert a QgsVectorLayer object into a pandas dataframe to store into a variable in python?

My process starts with the calculation of the zonal statistics for a raster file using the following line of code:

result = processing.run("native:zonalstatisticsfb", {'INPUT': shapefile,
                                                'INPUT_RASTER': rasterfile,
                                                'RASTER_BAND': 1,
                                                'COLUMN_PREFIX': '_',
                                                'STATISTICS': [2],
                                                'OUTPUT': QgsProcessing.TEMPORARY_OUTPUT})

I tried the fields() extension but it only gives back the column names of the zonal statistics csv:

for field in result['OUTPUT'].fields():
   print(field)

<QgsField: T_k (string)>
<QgsField: Area (double)>
<QgsField: Perimeter (double)>
<QgsField: _mean (double)>

>Solution :

You can use:

# result['OUTPUT'] is a QgsVectorLayer

df = pd.DataFrame([feat.attributes() for feat in result['OUTPUT'].getFeatures()],
                  columns=[field.name() for field in result['OUTPUT'].fields()])