Purpose:

The script parses campaign names to automatically tag them with a program identifier based on a specific naming convention.

To Elaborate

The Python script is designed to automate the process of tagging campaigns with a program identifier by parsing the campaign names. The script assumes that campaign names follow a specific naming convention where the program tag appears after the first underscore (‘_’). The script extracts this tag and updates the campaign data accordingly. This process helps in maintaining consistency and accuracy in campaign-level Marin Dimensions tagging, which is crucial for structured budget allocation (SBA) and reporting. The script ensures that only campaigns with a valid tag are updated, and it avoids unnecessary changes by checking if the new tag differs from the existing one.

Walking Through the Code

1. Configurable Parameters:
   • The script begins by defining configurable parameters such as the separator (SEP) and the tag location (TAG_LOCATION), which are used to parse the campaign names.
   • The primary data source is specified, and relevant columns for input and output are defined.
2. Tag Extraction Function:
   • A function get_tag_from_campaign_name is defined to extract the program tag from the campaign name. It checks for the presence of the separator and splits the name to retrieve the tag.
3. Data Processing:
   • The script copies the input data to an output DataFrame to preserve the original data.
   • It iterates over each row of the input data, extracting the campaign name and existing tag.
4. Tagging Logic:
   • For each campaign, the script checks if the separator is present. If so, it extracts the tag using the defined function.
   • It prints the campaign and tag information for verification.
   • The script updates the program tag in the output DataFrame only if the new tag is different from the existing one.
5. Final Output:
   • The script filters out rows with empty tags to ensure only valid updates are included.
   • It prints the final output DataFrame if it is not empty, otherwise, it indicates that the output is empty.

Vitals

• Script ID : 689
• Client ID / Customer ID: 1306926629 / 60270083
• Action Type: Bulk Upload
• Item Changed: Campaign
• Output Columns: Account, Campaign, Program, Campaign ID
• Linked Datasource: M1 Report
• Reference Datasource: None
• Owner: dwaidhas@marinsoftware.com (dwaidhas@marinsoftware.com)
• Created by dwaidhas@marinsoftware.com on 2024-02-09 19:20
• Last Updated by dwaidhas@marinsoftware.com on 2024-11-21 16:17

> See it in Action

Python Code

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##
## name: Campaign Name Dimension Auto Tagging: Program
## description:
## Parse Campaign Name and add Campaign-level Marin Dimensions Tag for Program.
## Tag appears after the first '_' underscore in campaign name.
## 
## author: Dana Waidhas 
## created: 2024-02-09
## 

########### Configurable Params - START ##########
SEP = '_'
TAG_LOCATION = 1  # Comes after the first separator
# Primary data source and columns
inputDf = dataSourceDict["1"]

# Output columns and initial values
RPT_COL_CAMPAIGN = 'Campaign'
RPT_COL_ACCOUNT = 'Account'
RPT_COL_CAMPAIGN_ID = 'Campaign ID'
RPT_COL_PROGRAM = 'Program'
BULK_COL_ACCOUNT = 'Account'
BULK_COL_CAMPAIGN = 'Campaign'
BULK_COL_CAMPAIGN_ID = 'Campaign ID'
BULK_COL_PROGRAM = 'Program'


def get_tag_from_campaign_name(campaign_name):
    # Check if the separator is present in the campaign name
    if SEP in campaign_name:
        # Split only after the first underscore
        vals = campaign_name.split(SEP, 1)
        
        # Extract the first 5 letters after the first underscore
        tag = vals[1][:5].strip() if len(vals) > 1 else campaign_name.strip()
        
        return tag
    else:
        # Return the entire campaign name if no separator is found
        return campaign_name.strip()

# Copy all input rows to output
outputDf = inputDf.copy()

# Loop through all rows
for index, row in inputDf.iterrows():
    existing_tag = row[RPT_COL_PROGRAM]
    campaign_name = row[RPT_COL_CAMPAIGN]
    
    # Skip processing if campaign name does not contain the separator
    if SEP not in campaign_name:
        continue

    tag = get_tag_from_campaign_name(campaign_name)

    # Print campaign and tag information
    print("Campaign [%s] => Tag [%s]" % (campaign_name, tag))

    # Only tag if it's different than the existing tag
    if (len(tag) > 0) & (tag != existing_tag):
        outputDf.at[index, BULK_COL_PROGRAM] = tag
    else:
        outputDf.at[index, BULK_COL_PROGRAM] = np.nan


# Only include non-empty tags in bulk
outputDf = outputDf.dropna(subset=[BULK_COL_PROGRAM])


if not outputDf.empty:
    print("outputDf", tableize(outputDf))
else:
    print("Empty outputDf")

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