Script 633: ABO Budget Assignment Groups
Purpose:
The script assigns Meta ABO Budget values at the group level for active Meta Ad sets, removing any previously assigned values at the campaign level.
To Elaborate
The Python script is designed to manage budget allocations for Meta Ad sets by assigning budget values at the group level. It specifically targets active Ad sets, ensuring that any previously assigned ABO Budget values at the campaign level are removed. The script processes data to determine the appropriate account based on the Ad account name and sets the Meta ABO Budget to zero for Ad sets that are not active. It also filters the data to exclude any entries with unknown accounts or those that do not meet specific criteria, such as having a daily budget type or a start date after January 1, 2022. This ensures that only relevant and active Ad sets are considered for budget allocation.
Walking Through the Code
- Function Definitions:
set_meta_abo_budget: Sets the Meta ABO Budget to zero if the Ad Set Status is not ‘Play’.get_account: Determines the account name based on the Ad account value, mapping specific strings to predefined account names.
- Data Preparation:
- The script begins by creating a new column ‘Account’ in the input DataFrame using the
get_accountfunction to map Ad account names to specific account identifiers. - It then calculates the ‘Meta ABO Budget’ for each row, setting it to zero if the Ad Set Status is not ‘Play’, otherwise using the ‘Ad Set Daily Budget $’.
- The script begins by creating a new column ‘Account’ in the input DataFrame using the
- Data Transformation:
- The script renames columns in the output DataFrame to align with the desired output format, such as renaming ‘Campaign Name’ to ‘Campaign’ and ‘Ad Set Name’ to ‘Group’.
- It copies relevant data from the input DataFrame to the output DataFrame, ensuring that the ‘Group’, ‘Campaign’, and ‘Meta ABO Budget’ columns are populated correctly.
- Data Filtering:
- Rows with an ‘Account’ value of ‘Unknown’ are filtered out to ensure only recognized accounts are processed.
- The script further filters the data to include only rows where the ‘Ad Set Budget Type’ is ‘Daily’ and the ‘Ad Set Start Date’ is after January 1, 2022, ensuring that only relevant and current Ad sets are considered.
Vitals
- Script ID : 633
- Client ID / Customer ID: 1306926715 / 60270103
- Action Type: Bulk Upload
- Item Changed: AdGroup
- Output Columns: Account, Campaign, Group, Meta ABO Budget
- Linked Datasource: M1 Report
- Reference Datasource: None
- Owner: Chris Jetton (cjetton@marinsoftware.com)
- Created by Chris Jetton on 2024-01-03 17:39
- Last Updated by Chris Jetton on 2024-01-12 00:39
> See it in Action
Python Code
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##
## name: ABO Budget Assignment - Groups
## description:
## assign values to the Meta ABO Budget dimension value at the group level for active Meta Ad sets only, removing any ABO Budget values previously assigned at the campaign level
##
## author:
## created: 2024-01-03
##
# Define a function to set the ABO Budget value to 0 if Ad Set Status is not equal to 'Play'
def set_meta_abo_budget(row):
if row['Ad Set Status'] != 'Play':
return 0
else:
return row['Meta ABO Budget']
# Define a function to determine the Account based on Ad account value
def get_account(ad_account):
if 'South Carolina 22' in ad_account:
return 'South Carolina 22 - Meta'
elif 'Engage WI' in ad_account:
return 'Engage WI - Meta'
elif 'Indiana22' in ad_account:
return 'Indiana 22 - Meta'
elif 'Engage NH' in ad_account:
return 'NH - Meta'
elif 'Graduation Alliance' in ad_account:
return 'Graduation Alliance - Meta'
elif 'Kansas 20' in ad_account:
return 'KANSAS 20 - Meta'
elif 'Arizona21' in ad_account:
return 'Arizona 21 - Meta'
elif 'Michigan23' in ad_account:
return 'Michigan23+ - Meta'
elif 'Arkansas 21' in ad_account:
return 'Arkansas 21+ - Meta'
elif 'AchievePoint' in ad_account:
return 'AchievePoint Career Academy - Meta'
elif 'American Academy' in ad_account:
return 'The American Academy (new) - Meta'
elif 'Engage NM' in ad_account:
return 'Engage NM - Meta'
elif 'Engage SC' in ad_account:
return 'Engage SC - Meta'
elif 'Engage MI' in ad_account:
return 'Engage MI - Meta'
elif 'Engage AZ' in ad_account:
return 'Engage AZ - Meta'
elif 'Engage GA' in ad_account:
return 'Engage GA - Meta'
elif 'Engage OH' in ad_account:
return 'Engage OH - Meta'
elif 'Missouri 21' in ad_account:
return 'Missouri 21+ - Meta'
else:
return 'Unknown'
today = datetime.datetime.now(CLIENT_TIMEZONE).date()
# primary data source and columns
inputDf = dataSourceDict["1"]
RPT_COL_AD_SET_NAME = 'Ad Set Name'
RPT_COL_PUBLISHER = 'Publisher'
RPT_COL_OBJECTIVE = 'Objective'
RPT_COL_PUBLISHER_NAME = 'Publisher Name'
RPT_COL_AD_ACCOUNT = 'Ad Account'
RPT_COL_CAMPAIGN_NAME = 'Campaign Name'
RPT_COL_CAMPAIGN_STATUS = 'Campaign Status'
RPT_COL_CAMPAIGN_END_DATE = 'Campaign End Date'
RPT_COL_CAMPAIGN_START_DATE = 'Campaign Start Date'
RPT_COL_CAMPAIGN_BUDGET_TYPE = 'Campaign Budget Type'
RPT_COL_CAMPAIGN_LIFETIME_BUDGET = 'Campaign Lifetime Budget $'
RPT_COL_CAMPAIGN_DAILY_BUDGET = 'Campaign Daily Budget $'
RPT_COL_AD_SET_STATUS = 'Ad Set Status'
RPT_COL_AD_SET_START_DATE = 'Ad Set Start Date'
RPT_COL_AD_SET_END_DATE = 'Ad Set End Date'
RPT_COL_AD_SET_BUDGET_TYPE = 'Ad Set Budget Type'
RPT_COL_AD_SET_DAILY_BUDGET = 'Ad Set Daily Budget $'
RPT_COL_AD_SET_LIFETIME_BUDGET = 'Ad Set Lifetime Budget $'
RPT_COL_IMPR = 'Impr.'
RPT_COL_IMPR_CHG = 'Impr. Chg.'
RPT_COL_IMPR_CHG = 'Impr. Chg. %'
RPT_COL_MAIN_KPI = 'Main KPI'
RPT_COL_MAIN_KPI_CHG = 'Main KPI Chg.'
RPT_COL_PUB_COST = 'Pub. Cost $'
RPT_COL_MAIN_KPI_CHG = 'Main KPI Chg. %'
RPT_COL_PUB_COST__CHG = 'Pub. Cost $ Chg. %'
RPT_COL_PUB_COST__CHG = 'Pub. Cost $ Chg.'
# output columns and initial values
BULK_COL_ACCOUNT = 'Account'
BULK_COL_CAMPAIGN = 'Campaign'
BULK_COL_GROUP = 'Group'
BULK_COL_META_ABO_BUDGET = 'Meta ABO Budget'
# user code start here
# Create a new column 'Account' using the get_account function
inputDf['Account'] = inputDf['Ad Account'].apply(get_account)
# Assuming 'Ad Set Status' column is present in the inputDf
inputDf['Meta ABO Budget'] = inputDf.apply(lambda row: '0.0' if row['Ad Set Status'] != 'Play' else row['Ad Set Daily Budget $'], axis=1)
# Rename columns as per your requirements
outputDf.rename(columns={
'Campaign Name': 'Campaign',
'Ad Set Name': 'Group',
# 'Publisher Campaign ID': 'Campaign',
# 'Account': 'Account',
'Ad Set Daily Budget $': 'Meta ABO Budget'
}, inplace=True)
outputDf['Group'] = inputDf['Ad Set Name'].copy()
outputDf['Campaign'] = inputDf['Campaign Name'].copy()
outputDf['Meta ABO Budget'] = inputDf['Meta ABO Budget'].copy()
# Set the 'Account' column in outputDf to have the same values as inputDf['Account']
outputDf['Account'] = inputDf['Account'].copy()
# Filter out rows with Account = 'Unknown'
outputDf = outputDf[outputDf['Account'] != 'Unknown']
# Filter out rows where 'Ad Set Budget Type' is not equal to 'Daily'
outputDf = outputDf[inputDf['Ad Set Budget Type'] == 'Daily']
# Filter out rows where 'Ad Set Start Date' is later than 1/1/22
outputDf = outputDf[inputDf['Ad Set Start Date'] > '1/1/2022']
Post generated on 2025-03-11 01:25:51 GMT