Purpose:

The Python script ensures that the traffic dimension is consistently aligned across each bucket by setting all campaigns in a bucket to the maximum traffic value when one campaign is set to 1.

To Elaborate

The script addresses the problem of maintaining consistent traffic allocation across different campaigns within the same bucket. When a campaign within a bucket is set to a traffic value of 1, the script ensures that all other campaigns in the same bucket are also set to the maximum traffic value found within that bucket. This alignment is crucial for structured budget allocation (SBA) to ensure that traffic distribution is uniform and optimized across campaigns. The script processes input data, calculates the maximum traffic value for each bucket, and updates the traffic values accordingly to maintain consistency.

Walking Through the Code

1. Initialization and Data Preparation
   • The script begins by defining column names for both report and bulk data frames, which are used to identify and manipulate data related to campaigns, accounts, and SBA traffic.
   • It initializes the traffic column in the output data frame with a placeholder value, indicating where the updated traffic values will be stored.
2. Data Processing and Traffic Alignment
   • The script fills any missing traffic values in the input data frame with zeros and converts the traffic column to integer type to ensure consistent data handling.
   • It groups the input data by the SBA bucket name and calculates the maximum traffic value for each bucket, which is crucial for aligning traffic across campaigns.
   • The script merges this grouped data back into the original input data frame, appending the maximum traffic value for each bucket.
   • Finally, it updates the output data frame with these maximum traffic values, ensuring that all campaigns within a bucket have consistent traffic allocation. The script filters out rows where the traffic values have not changed, focusing only on those that require updates.

Vitals

• Script ID : 181
• Client ID / Customer ID: 1306923673 / 60269245
• Action Type: Bulk Upload
• Item Changed: Campaign
• Output Columns: Account, Campaign, SBA Traffic
• Linked Datasource: M1 Report
• Reference Datasource: None
• Owner: Jonathan Reichl (jreichl@marinsoftware.com)
• Created by Jonathan Reichl on 2023-06-09 10:18
• Last Updated by Jonathan Reichl on 2023-12-06 04:01

> See it in Action

Python Code

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RPT_COL_CAMPAIGN = 'Campaign'
RPT_COL_ACCOUNT = 'Account'
RPT_COL_SBA_BUCKETNAME = 'SBA Bucket Name'
RPT_COL_SBA_TRAFFIC = 'SBA Traffic'
BULK_COL_ACCOUNT = 'Account'
BULK_COL_CAMPAIGN = 'Campaign'
BULK_COL_SBA_TRAFFIC = 'SBA Traffic'

outputDf[BULK_COL_SBA_TRAFFIC] = "<<YOUR VALUE>>"

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

inputDf[RPT_COL_SBA_TRAFFIC].fillna(0, inplace=True)

inputDf[RPT_COL_SBA_TRAFFIC] = inputDf[RPT_COL_SBA_TRAFFIC].astype(int)

# Group by 'RPT_COL_CAMPAIGN' and calculate the maximum value of 'RPT_COL_SBA_TRAFFIC'
grouped = inputDf.groupby(RPT_COL_SBA_BUCKETNAME)[RPT_COL_SBA_TRAFFIC].max().reset_index()

inputDf = inputDf.merge(grouped, on= RPT_COL_SBA_BUCKETNAME, how='left', suffixes=('', '_max'))

outputDf[BULK_COL_SBA_TRAFFIC] = inputDf['SBA Traffic_max']

outputDf = outputDf[ inputDf[RPT_COL_SBA_TRAFFIC] != outputDf[BULK_COL_SBA_TRAFFIC] ]

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