Convert JSON load to readable Pandas Dataframe

zape 0
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I am trying to load some data from ArcGis. I am used to working in Pandas Dataframes, not entirely sure how I can read from API's and get it in a nice table. I tried data['results'] and get feature dataset. But not sure how to organize the data by unique Object ID. Anyone have an idea how to read this into a pandas dataframe?

import urllib.request as urlopen
import urllib.parse as urlencode
import urllib.request as request
import json
import pandas as pd

inPts = {"geometryType" : "esriGeometryPoint",
         "spatialReference" : {"wkid" : 54003},
         'features':[{'geometry': {'x': -13308192.1956127, 'y': 4221903.58555983}}]}
dist = {'distance':8.5,'units':'esriMiles'}

data = {'Input_Observation_Point': inPts,
        'Viewshed_Distance': dist,
        'f': 'pjson'}

URL = 'http://sampleserver6.arcgisonline.com/ArcGIS/rest/services/Elevation/ESRI_Elevation_World/GPServer/Viewshed/execute'

req = request.Request(URL, urlencode.urlencode(data).encode('UTF-8'))
response = urlopen.urlopen(req)
response_bytes = response.read()
data = json.loads(response_bytes.decode('UTF-8'))
arcgis pandas rest api python
1 Answers

If I understood right you want to create a dataframe for all the features and the geometry. The following code creates the dataframe bellow:

import urllib.request as urlopen
import urllib.parse as urlencode
import urllib.request as request
import json
import pandas as pd
import numpy as np

inPts = {"geometryType" : "esriGeometryPoint",
         "spatialReference" : {"wkid" : 54003},
         'features':[{'geometry': {'x': -13308192.1956127, 'y': 4221903.58555983}}]}
dist = {'distance':8.5,'units':'esriMiles'}

data = {'Input_Observation_Point': inPts,
        'Viewshed_Distance': dist,
        'f': 'pjson'}

URL = 'http://sampleserver6.arcgisonline.com/ArcGIS/rest/services/Elevation/ESRI_Elevation_World/GPServer/Viewshed/execute'

req = request.Request(URL, urlencode.urlencode(data).encode('UTF-8'))
response = urlopen.urlopen(req)
response_bytes = response.read()
data = json.loads(response_bytes.decode('UTF-8'))#
arcgis_data = data["results"][0]["value"]
columns = ["geometry"]
attributes = []
for field in arcgis_data["fields"]:
    columns.append(field["name"])
    attributes.append(field["name"])

feature_values = []
for feature in arcgis_data["features"]:
    feature_line = [feature["geometry"]]
    for feature_name in attributes:
        feature_line.append(feature["attributes"][feature_name])
    feature_values.append(feature_line)

feature_df = pd.DataFrame(np.array(feature_values), columns=columns)

Dataframe resulting

I tried to keep the code as dynamic as possible to handle more attribute names if the response at "fields" got more fields. Only two attributes that are always required is "geometry" and "attributes".

Oivalf0
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