Purpose:

The Python script processes input data to set specific parameters for advertising campaigns, including search bids and alternative product requirements.

To Elaborate

The Python script is designed to manipulate and prepare data for advertising campaigns by setting specific parameters for each campaign entry. It takes input data, presumably from a DataFrame, and copies certain columns to an output DataFrame while assigning predefined values to other columns. The script sets a fixed search bid, tags for alternative products, and marks the requirement for alternative products as true. This setup is likely used to ensure that campaigns are configured consistently with specific business rules, such as promoting alternative products when the primary ones are unavailable or less desirable. The script aims to streamline the process of configuring campaigns by automating the assignment of these parameters.

Walking Through the Code

1. Initialization of Constants:
   • The script begins by defining constants for column names that will be used to access and modify data within the DataFrame. These constants represent various attributes of advertising campaigns, such as account, campaign, group, and custom parameters.
2. Data Copying and Modification:
   • The script copies specific columns from the input DataFrame to the output DataFrame. This ensures that the essential campaign data is preserved while allowing modifications to other columns.
   • It sets the ‘Search Bid’ column to a fixed value of ‘0.5’, indicating the bid amount for search advertising.
   • The ‘Alternative Product Required’ column is set to “true”, suggesting that alternative products should be considered in the campaign.
   • The ‘altproducttag’ column is assigned a specific tag, ‘#pdpSection_PFProdSubstit’, which might be used for tracking or categorizing alternative products.
   • The ‘Custom Parameters’ column is populated with a formatted string that includes the alternative product tag, potentially used for dynamic campaign adjustments.
3. Output Preparation:
   • The script prepares the output DataFrame with the modified data, ready for further processing or export.

Vitals

• Script ID : 303
• Client ID / Customer ID: 1306917939 / 64302
• Action Type: Bulk Upload
• Item Changed: AdGroup
• Output Columns: Account, Campaign, Group, Custom Parameters, Alternative Product Required, altproducttag
• Linked Datasource: M1 Report
• Reference Datasource: None
• Owner: Tom McCaughey (tmccaughey@marinsoftware.com)
• Created by Tom McCaughey on 2023-09-15 11:07
• Last Updated by Tom McCaughey on 2023-12-06 04:01

> See it in Action

Python Code

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BULK_COL_ACCOUNT = 'Account'
BULK_COL_CAMPAIGN = 'Campaign'
BULK_COL_GROUP = 'Group'
BULK_COL_CUSTOM_PARAMETERS = 'Custom Parameters'
BULK_COL_ALTERNATIVE_PRODUCTREQUIRED = 'Alternative Product Required'
BULK_COL_ALTPRODUCTTAG = 'altproducttag'
BULk_COL_SEARCH_BID = 'Search Bid'

# copy all input rows to output
#outputDf = inputDf.copy()
outputDf[BULK_COL_ACCOUNT] = inputDf[BULK_COL_ACCOUNT]
outputDf[BULK_COL_CAMPAIGN] = inputDf[BULK_COL_CAMPAIGN]
outputDf[BULK_COL_GROUP] = inputDf[BULK_COL_GROUP]
outputDf[BULk_COL_SEARCH_BID] = '0.5'
outputDf[BULK_COL_ALTPRODUCTTAG] = '#pdpSection_PFProdSubstit'
outputDf[BULK_COL_ALTERNATIVE_PRODUCTREQUIRED] = "true"
outputDf[BULK_COL_CUSTOM_PARAMETERS] = '{_altproduct}=[altproducttag]'

today = datetime.datetime.now(CLIENT_TIMEZONE).date()
print(tableize(inputDf))

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