Purpose

Clear Daily Winner and Overspend labels daily

To Elaborate

The Python script clears the Daily Winner and Overspend labels on a daily basis. It identifies any changes in the labels and outputs the updated labels in a specific format.

Walking Through the Code

1. The script defines column constants for various columns used in the code.
2. It creates temporary column names for the Daily Winner and Overspend labels.
3. It adds the temporary columns to the input dataframe and fills any missing values with an empty string.
4. It checks for changes in the Daily Winner and Overspend labels by comparing the original columns with the temporary columns.
5. It prints the number of changes detected.
6. It creates an output dataframe by selecting the relevant columns from the input dataframe where changes were detected.
7. It renames the temporary columns to the desired column names for the output dataframe.
8. It prints the output dataframe in a specific format.

Vitals

• Script ID : 45
• Client ID / Customer ID: 1306925293 / 60269377
• Action Type: Bulk Upload
• Item Changed: AdGroup
• Output Columns: Account, Campaign, Group, Daily Winner, Daily (Overspent)
• Linked Datasource: M1 Report
• Reference Datasource: None
• Owner: Michael Huang (mhuang@marinsoftware.com)
• Created by Michael Huang on 2023-04-10 12:08
• Last Updated by Michael Huang on 2023-12-06 04:01

> See it in Action

Python Code

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RPT_COL_GROUP = 'Group'
RPT_COL_DAILY_WINNER = 'Daily Winner'
RPT_COL_DAILY_OVERSPENT = 'Daily (Overspent)'
RPT_COL_PUBLISHER = 'Publisher'
RPT_COL_ACCOUNT = 'Account'
RPT_COL_CAMPAIGN = 'Campaign'
BULK_COL_ACCOUNT = 'Account'
BULK_COL_CAMPAIGN = 'Campaign'
BULK_COL_GROUP = 'Group'
BULK_COL_DAILY_OVERSPENT = 'Daily (Overspent)'
BULK_COL_DAILY_WINNER = 'Daily Winner'

winner_tmp = RPT_COL_DAILY_WINNER + "_"
overspend_tmp = RPT_COL_DAILY_OVERSPENT + "_"

inputDf[winner_tmp] = np.nan
inputDf[overspend_tmp] = np.nan

inputDf.fillna('', inplace=True)
changed = ( (inputDf[RPT_COL_DAILY_WINNER] != inputDf[winner_tmp]) | \
            (inputDf[RPT_COL_DAILY_OVERSPENT] != inputDf[overspend_tmp]) \
          )

print("changed: ", sum(changed))

outputDf = inputDf.loc[changed, [RPT_COL_ACCOUNT, RPT_COL_CAMPAIGN, RPT_COL_GROUP, winner_tmp, overspend_tmp]].copy()
outputDf.rename(columns={
                winner_tmp: BULK_COL_DAILY_WINNER, \
                overspend_tmp: BULK_COL_DAILY_OVERSPENT}, \
            inplace=True)

print(outputDf.to_string())

Post generated on 2024-05-15 07:44:05 GMT