Script 1515: Pacing Daily Budget Alert Checked Status

Purpose

The Python script filters and processes campaign data to update daily budget alerts for campaigns with a “Checked” status.

To Elaborate

The Python script is designed to manage and update daily budget alerts for advertising campaigns. It processes a dataset containing various campaign details, focusing on campaigns that have not ended and have specific traffic conditions. The script updates the daily budget for these campaigns based on a recommended value and sets the pacing calculation date to the current date. It then filters the campaigns further to include only those with a “Checked” status in the daily budget alert column. The final output consists of selected columns, including account, campaign, daily budget, and a cleared daily budget alert status, ready for further use or display.

Walking Through the Code

  1. Data Filtering:
    • The script begins by filtering out campaigns that have ended, using the RPT_COL_AUTO_PACING_CYCLE_THRESHOLD column.
    • It further narrows down the dataset to include only campaigns with “Traffic” in the RPT_COL_SBA_TRAFFIC column.
  2. Data Processing:
    • For the filtered campaigns, the script updates the RPT_COL_DAILY_BUDGET with values from RPT_COL_RECOMMENDED_DAILY_BUDGET.
    • It sets the RPT_COL_PACING_CALCULATION_DATE to the current date.
  3. Final Filtering and Output Preparation:
    • The script filters the dataset to include only campaigns where RPT_COL_DAILY_BUDGET_ALERT is “Checked”.
    • It prepares the final output by creating new columns for account, campaign, and daily budget, and clears the “Checked” status in the RPT_COL_DAILY_BUDGET_ALERT.
    • The final output is a DataFrame with selected columns, ready for display or further processing.

Vitals

  • Script ID : 1515
  • Client ID / Customer ID: 1306928345 / 60270139
  • Action Type: Bulk Upload (Preview)
  • Item Changed: Campaign
  • Output Columns: Account, Campaign, Daily Budget, Daily Budget Alert
  • Linked Datasource: M1 Report
  • Reference Datasource: None
  • Owner: Arayla Caldwell (acaldwell@marinsoftware.com)
  • Created by Arayla Caldwell on 2024-11-11 22:58
  • Last Updated by Arayla Caldwell on 2024-11-11 22:58
> See it in Action

Python Code

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## 
## name: Daily Budget Alert "Checked" Status 
## description:
##  
## 
## author: Jesus A. Garza
## created: 2024-07-01
## 

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

# primary data source and columns
inputDf = dataSourceDict["1"]
RPT_COL_CAMPAIGN = 'Campaign'
RPT_COL_DATE = 'Date'
RPT_COL_ACCOUNT = 'Account'
RPT_COL_AUTO_PACING_CYCLE_START_DATE = 'Auto. Pacing Cycle Start Date'
RPT_COL_AUTO_PACING_CYCLE_END_DATE = 'Auto. Pacing Cycle End Date'
RPT_COL_AUTO_PACING_CYCLE_DAYS_ELAPSED = 'Auto. Pacing Cycle Days Elapsed'
RPT_COL_AUTO_PACING_CYCLE_DAYS_REMAINING = 'Auto. Pacing Cycle Days Remaining'
RPT_COL_AUTO_PACING_CYCLE_PACING = 'Auto. Pacing Cycle Pacing'
RPT_COL_AUTO_PACING_CYCLE_THRESHOLD = 'Auto. Pacing Cycle Threshold'
RPT_COL_TOTAL_TARGET_SPEND_PER_IMPRVIEWS = 'Total Target (Spend/Impr./Views)'
RPT_COL_TOTAL_DAYS = 'Total Days'
RPT_COL_TOTAL_DAYS_ELAPSED = 'Total Days Elapsed'
RPT_COL_TOTAL_PACING = 'Total Pacing'
RPT_COL_DELIVERY_STATUS = 'Delivery Status'
RPT_COL_RECOMMENDED_DAILY_BUDGET = 'Recommended Daily Budget'
RPT_COL_DAILY_BUDGET = 'Daily Budget'
RPT_COL_PACING_CALCULATION_DATE = 'Pacing Calculation Date'
RPT_COL_SOCIAL_BUDGET = 'Social Budget'
RPT_COL_SOCIAL_BUDGET_UPDATE_STATUS = 'Social Budget Update Status'
RPT_COL_AUTO_PACING_CYCLE_PUB_COST = 'Auto. Pacing Cycle Pub. Cost'
RPT_COL_AUTO_PACING_CYCLE_IMPR = 'Auto. Pacing Cycle Impr.'
RPT_COL_AUTO_PACING_CYCLE_CLICKS = 'Auto. Pacing Cycle Clicks'
RPT_COL_AUTO_PACING_CYCLE_VIEWS = 'Auto. Pacing Cycle Views'
RPT_COL_SBA_TRAFFIC = 'SBA Traffic'
RPT_COL_DAILY_BUDGET_ALERT = 'Daily Budget Alert'

# output columns and initial values
BULK_COL_ACCOUNT = 'Account'
BULK_COL_CAMPAIGN = 'Campaign'
BULK_COL_DAILY_BUDGET = 'Daily Budget'
BULK_DAILY_BUDGET_ALERT = 'Bulk Daily Budget Alert'

# First filter: Exclude campaigns with 'Campaign Ended'
campaigns_not_ended = inputDf[inputDf[RPT_COL_AUTO_PACING_CYCLE_THRESHOLD] != 'Campaign Ended']

# Second filter: From the remaining, only include those where SBA Traffic is 'Traffic'
filteredDf = campaigns_not_ended[campaigns_not_ended[RPT_COL_SBA_TRAFFIC] == 'Traffic']

# Apply necessary operations on filteredDf
filteredDf.loc[:, RPT_COL_DAILY_BUDGET] = filteredDf[RPT_COL_RECOMMENDED_DAILY_BUDGET]
filteredDf.loc[:, RPT_COL_PACING_CALCULATION_DATE] = today

# Filter to include only campaigns where DAILY_BUDGET_ALERT is 'Checked'
outputDf = filteredDf[filteredDf[RPT_COL_DAILY_BUDGET_ALERT] == 'Checked'].copy()

# Create new columns for output and clear the 'Checked' value in 'Bulk Daily Budget Alert'
outputDf[BULK_COL_ACCOUNT] = outputDf[RPT_COL_ACCOUNT]
outputDf[BULK_COL_CAMPAIGN] = outputDf[RPT_COL_CAMPAIGN]
outputDf[BULK_COL_DAILY_BUDGET] = outputDf[RPT_COL_DAILY_BUDGET]
outputDf[RPT_COL_DAILY_BUDGET_ALERT] = ''

# Select only the new columns for the final output
outputDf = outputDf[[BULK_COL_ACCOUNT, BULK_COL_CAMPAIGN, BULK_COL_DAILY_BUDGET, RPT_COL_DAILY_BUDGET_ALERT]]

# Assuming you want to display or utilize outputDf
print(outputDf)

Post generated on 2024-11-27 06:58:46 GMT

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