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Hierarchical Date Dimensions

Models

Segments

Hierarchical Date Dimensions

Select different time frames from the dropdown of a date Column.

Hierarchical Date Dimensions

Now create a segment on this model by selecting a higher hierarchy date dimension along with the required measures.

Hierarchical Date Dimensions

In the above report select the higher hierarchy date dimension "Updated_At_Year”. Now you can drill down further to the lower hierarchy date dimensions like month, week, day etc.

Hierarchical Date Dimensions

Once the drill down is clicked, the result will display the Quarter in which that particular date resides with** **Distinct Bus Number shown.

Hierarchical Date Dimensions

Users can do drill ups as well at any level, if the date dimension is not the first one in the hierarchy.

Hierarchical Date Dimensions

import requests
from requests.auth import HTTPBasicAuth

auth =  HTTPBasicAuth(<API_KEY>, <API_SECRET>)
response = requests.get("https://<hostname>/api/v0.4/explore/streamresult/<EXPLORE_ID>", auth)

print(response.content)

library('httr')

username = '<API KEY>'
password = '<API SECRET>'

temp = GET("https://<hostname>/api/v0.4/explore/streamresult/<EXPLORE ID>",
           authenticate(username,password, type = "basic"))

temp = content(temp, 'text')
temp = textConnection(temp)
temp = read.csv(temp)

/*Download the Data*/

filename resp temp;
proc http
url="https://<hostname>/api/v0.4/explore/streamresult/<EXPLORE ID>"
   method= "GET"  
   WEBUSERNAME = "<API KEY>"
   WEBPASSWORD = "<API SECRET>"
   out=resp;
run;

/*Import the data in to csv dataset*/
proc import
   file=resp
   out=csvresp
   dbms=csv;
run;

/*Print the data */
PROC PRINT DATA=csvresp;
RUN;

import requests
import json

url='http://hostname/api/v0.4/createCSV'

username='API_KEY'
password='API_SECRET'

files={'file':open('FILE_PATH.csv','rb')}
values={'projectname':PROJECT_NAME','name':'CSV_DATASOURCE_NAME'}

r=requests.post(url, files=files, data=values, auth=(username,password))

res_json=json.loads(r.text)

print(res_json['success'])

import requests
import json

url='http://hostname/api/v0.4/updateCSV'

username='API_KEY'
password='API_SECRET'

files={'file':open('FILE_PATH.csv','rb')}
values={'projectname':PROJECT_NAME','name':'CSV_DATASOURCE_NAME'}

r=requests.post(url, files=files, data=values, auth=(username,password))

res_json=json.loads(r.text)

print(res_json['success'])

import requests

url='https://<hostname>/api/v0.4/explore/streamresult/<EXPLORE ID>'

username='API_KEY'
password='API_SECRET'

r=requests.get(url,auth=(username,password))
print(r)
print(r.text)

import requests

import pandas as pd

import io

url='https://<hostname>/api/v0.4/explore/streamresult/<EXPLORE ID>'

secret='API_SECRET'

r=requests.get(url,headers = {'Authorization': 'SprinkleUserKeys ' +secret } )

df = pd.read_csv(io.StringIO(r.text),sep=',')

import requests

import pandas as pd

import io

url='https://<hostname>/api/v0.4/segment/streamresult/<SEGMENT ID>'

secret='API_SECRET'

r=requests.get(url,headers = {'Authorization': 'SprinkleUserKeys ' +secret } )

df = pd.read_csv(io.StringIO(r.text),sep=',')

import requests

import json

url='http://hostname/api/v.o4/createCSV'

files={'file':open('path/file.csv’')}

values={'projectname':PROJECT_NAME,'name':'csv_datasource_name/table_name'}

secret='API_SECRET'

r=requests.post(url, files=files, data=values, headers = {'Authorization': 'SprinkleUserKeys ' +secret } )

res_json=json.loads(r.text)

import requests

import json

url='http://hostname/api/v.o4/updateCSV'

files={'file':open('path/file.csv’')}

values={'projectname':PROJECT_NAME,'name':'csv_datasource_name/table_name'}

secret='API_SECRET'

r=requests.post(url, files=files, data=values,headers = {'Authorization': 'SprinkleUserKeys ' +secret } )

res_json=json.loads(r.text)