Purpose:

The script calculates and stores the average cost-per-click (CPC) for the last 28 days in a specified dimension called “Test.”

To Elaborate

The Python script is designed to process advertising data by extracting the average cost-per-click (CPC) from a data source and storing it in a new data structure. The script focuses on creating a new DataFrame that includes specific columns such as ‘Account’, ‘Campaign’, and ‘Test’, where ‘Test’ holds the average CPC values. The primary goal is to ensure that the average CPC for the last 28 days is accurately captured and stored for further analysis or reporting. If the ‘Avg. CPC $’ column is missing from the input data, the script handles this by setting the ‘Test’ column to None, ensuring robustness in data processing.

Walking Through the Code

1. Data Initialization:
   • The script begins by defining the primary data source, inputDf, which is expected to contain advertising data.
   • It initializes an empty DataFrame, outputDf, with columns ‘Account’, ‘Campaign’, and ‘Test’.
2. Data Copying:
   • The script copies the ‘Account’ and ‘Campaign’ columns from inputDf to outputDf, ensuring these identifiers are preserved in the output.
3. Average CPC Handling:
   • It checks if the ‘Avg. CPC $’ column exists in inputDf.
   • If present, the values are copied to the ‘Test’ column in outputDf.
   • If absent, a message is printed, and the ‘Test’ column is set to None, maintaining data integrity.
4. Output:
   • The final outputDf is printed, showcasing the processed data with the average CPC values stored in the ‘Test’ column.

Vitals

• Script ID : 733
• Client ID / Customer ID: 6968245 / 3374365
• Action Type: Bulk Upload
• Item Changed: Campaign
• Output Columns: Account, Campaign, Test
• Linked Datasource: M1 Report
• Reference Datasource: None
• Owner: wmaclaggan@marinsoftware.com (wmaclaggan@marinsoftware.com)
• Created by wmaclaggan@marinsoftware.com on 2024-03-01 23:11
• Last Updated by wmaclaggan@marinsoftware.com on 2024-03-01 23:24

> See it in Action

Python Code

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##
## name: WJM Test
## description:
##  
## 
## author: 
## created: 2024-03-01
## 

today = datetime.datetime.now(CLIENT_TIMEZONE).date()

# primary data source and columns
inputDf = dataSourceDict["1"]
print(tableize(inputDf))

# output columns and initial values
BULK_COL_ACCOUNT = 'Account'
BULK_COL_CAMPAIGN = 'Campaign'
BULK_COL_TEST = 'Test'

# Initialize outputDf with the required columns
outputDf = pd.DataFrame(columns=[BULK_COL_ACCOUNT, BULK_COL_CAMPAIGN, BULK_COL_TEST])

# Assuming 'Account' and 'Campaign' are columns in inputDf, copy them to outputDf
outputDf[BULK_COL_ACCOUNT] = inputDf['Account']
outputDf[BULK_COL_CAMPAIGN] = inputDf['Campaign']

# Check if 'Avg. CPC' column exists in inputDf and copy it to 'Test' in outputDf
if 'Avg. CPC $' in inputDf.columns:
    outputDf[BULK_COL_TEST] = inputDf['Avg. CPC $']
else:
    print("'Avg. CPC' column not found in inputDf")
    outputDf[BULK_COL_TEST] = None

# user code start here
print(tableize(outputDf))

Post generated on 2025-03-11 01:25:51 GMT