Script 771: Pacing Campaign Bulk Sheet
Purpose
Python script to filter and process campaign data based on specific criteria.
To Elaborate
The Python script filters campaign data based on certain criteria and performs necessary operations on the filtered data. It aims to identify campaigns that have not ended and have “Traffic” as their SBA Traffic status. The script then applies operations to update the Daily Budget and Pacing Calculation Date columns of the filtered data.
Walking Through the Code
- The script starts by importing the necessary libraries and defining the current date.
- It sets up the primary data source and defines the column constants.
- The output columns are defined, with the Daily Budget column initially set to a placeholder value.
- The first filter is applied to exclude campaigns with the “Campaign Ended” threshold.
- The second filter is applied to include only campaigns with “Traffic” as their SBA Traffic status.
- Necessary operations are performed on the filtered data, updating the Daily Budget and Pacing Calculation Date columns.
- The filtered data is copied to the output dataframe.
- The output dataframe is printed, assuming it will be displayed or utilized further.
Vitals
- Script ID : 771
- Client ID / Customer ID: 1306927187 / 60270139
- Action Type: Bulk Upload (Preview)
- Item Changed: Campaign
- Output Columns: Account, Campaign, Daily Budget, Pacing Calculation Date
- Linked Datasource: M1 Report
- Reference Datasource: None
- Owner: ascott@marinsoftware.com (ascott@marinsoftware.com)
- Created by ascott@marinsoftware.com on 2024-03-06 22:10
- Last Updated by ascott@marinsoftware.com on 2024-03-19 18:45
> See it in Action
Python Code
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##
## name: Campaign Bulk Sheet
## description:
##
##
## author:
## created: 2024-03-04
##
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'
# output columns and initial values
BULK_COL_ACCOUNT = 'Account'
BULK_COL_CAMPAIGN = 'Campaign'
BULK_COL_DAILY_BUDGET = 'Daily Budget'
outputDf[BULK_COL_DAILY_BUDGET] = "<<YOUR VALUE>>"
# 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
outputDf = filteredDf.copy()
# Assuming you want to display or utilize outputDf
print(outputDf)
Post generated on 2024-05-15 07:44:05 GMT