CODEWITHSUNDEEP
pythonpandastabpytableau-prep
mxs
mxs

Reputation: 645

Dataframe object not callable when working Python script moved from Replit to local TabPy server

I have written a Python script that calls a National Oceanic and Atmospheric Administration (NOAA) endpoint with a zip code and gets a list of weather stations in response. The script then converts the response to a Pandas dataframe.

I believe I have it working correctly based on this Replit.The dataframe appears to print to console correctly and I can inspect it using breakpoints.

Using this blog tutorial as my guide, my real goal is to leverage this Python script in a Tableau Prep flow. Tableau Prep is basically a desktop ETL tool, similar to PowerQuery, but different :).

I have a local working instance of a TabPy server, whose logs also appear to be showing proper construction of the dataframe (image below). However, I'm getting a TypeError : 'DataFrame' object is not callable. I've also provided an image of the same error surfaced in the Tableau Prep interface.

Any help is sincerely appreciated.

Local Tabpy logs

Tableau Prep Error

Here's the syntax of the actual script running on my TabPy server - with minimal modifications from what's on Replit.

import requests;
import pandas as pd;
import json;

zip = '97034'
userToken = 'foobar123'
headerCreds = dict(token = userToken)
url = 'https://www.ncei.noaa.gov/cdo-web/api/v2/stations?&locationid=ZIP:' + zip
global dfWorking

def get_stations_for_zip():

    r = requests.get(url, headers = headerCreds)
    data = json.loads(r.text)
                     
    if 'results' in data:
        data = data.get('results')
        dfWorking = pd.DataFrame(data)
    
        # Column datatypes as received
        # elevation        float64
        # mindate           object
        # maxdate           object
        # latitude         float64
        # name               int64
        # datacoverage     float64
        # id                object
        # elevationUnit     object
        # longitude        float64

        dfWorking = dfWorking.astype({'name': 'str'})
      
        # dfWorking['name'] = dfWorking.index
        # defining an index converts back to float64
  
        print(dfWorking)
    else:
      print('no results object in response')
      
    return dfWorking

# Note: the below prep functions are undefined until they are on a TabPy server
  
def get_output_schema():
    return pd.DataFrame({
        'elevation' : prep_decimal(),
        'mindate' : prep_string(),
        'maxdate' : prep_decimal(),
        'latitude' : prep_date(),
        'name' : prep_string(),
        'datacoverage' : prep_decimal(),     
        'id' : prep_decimal(),
        'name' : prep_string(),
        'elevationUnit' : prep_decimal(),     
        'longitude' : prep_decimal()      
    });

get_stations_for_zip()

Upvotes: 0

Views: 253

Answers (2)

mxs
mxs

Reputation: 645

The solution required two changes:

  1. In the Tableau Prep interface where stating the function name, I had get_stations_for_zip(), but needed get_stations_for_zip without parenthesis

Tableau Prep interface

  1. In my script, the get_stations_for_zip function needed to take "df" (for dataframe) as an argument. So def get_stations_for_zip(df):. Strangely this argument is never used within the function, but it's necessary and the blog I was referencing shows the same.

Here's a quote from help.tableau.com's article Use Python scripts in your flow

When you create your script, include a function that specifies a pandas (pd.DataFrame) as an argument of the function. This will call your data from Tableau Prep Builder.

Upvotes: 1

404pio
404pio

Reputation: 1032

This line is wrong:

execution_result = get_stations_for_zip()(pd.DataFrame(_arg1))

because get_stations_for_zip is returning DataFrame, and you are threating it as python function, so you are trying:

df = get_stations_for_zip()
df(pd.DataFrame(_arg1)) # and error is right here

Upvotes: 0

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