In a Nutshell

The script updates the region information for PPC campaigns based on campaign naming conventions.

To Elaborate

• The script is designed to manage and update the regional classification of PPC campaigns.
• It uses campaign names to determine the correct region and applies changes where necessary.

Walking Through the Code

• Constants like RPT_COL_CAMPAIGN, RPT_COL_ACCOUNT, and RPT_COL_REGION are used to reference specific columns in a dataset.
• A temporary field TMP_FIELD is created to hold the new region values before they are finalized.
• The script searches campaign names for keywords (‘EMEA’, ‘AMER’, ‘APAC’) to assign the corresponding region to TMP_FIELD.
• It then copies the new region values from TMP_FIELD to the outputDf DataFrame if there is a change from the original region.
• Only campaigns with updated region information are included in the final output, ensuring that no redundant data is processed.
• The script uses inputDf as the source data and outputDf as the destination for the updated information.
• Multiple datasources are not explicitly mentioned, but the script seems to be designed to work with at least two DataFrames: one for input and one for output.

Vitals

• Script ID : 189
• Client ID / Customer ID: 1306920563 / 60268859
• Action Type: Bulk Upload
• Item Changed: Campaign
• Output Columns: Account, Campaign, Region
• Created by Jonathan Reichl on 2023-06-14 15:37:13
• Last Updated by Jonathan Reichl on 2023-12-06 04:01:47

> See it in Action

Python Code

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RPT_COL_CAMPAIGN = 'Campaign'
RPT_COL_ACCOUNT = 'Account'
RPT_COL_REGION = 'Region'
BULK_COL_ACCOUNT = 'Account'
BULK_COL_CAMPAIGN = 'Campaign'
BULK_COL_REGION = 'Region'

#outputDf[BULK_COL_REGION] = "<<YOUR VALUE>>"

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

#outputDf[BULK_COL_MARKET] = "<<YOUR VALUE>>"

TMP_FIELD = BULK_COL_REGION + '_new'
# blank out tmp field
inputDf[TMP_FIELD] = numpy.nan

inputDf.loc[ (inputDf[RPT_COL_CAMPAIGN].str.contains('EMEA', case=False)) , TMP_FIELD ] = 'EMEA'
inputDf.loc[ (inputDf[RPT_COL_CAMPAIGN].str.contains('AMER', case=False)) , TMP_FIELD ] = 'AMER'
inputDf.loc[ (inputDf[RPT_COL_CAMPAIGN].str.contains('APAC', case=False)) , TMP_FIELD ] = 'APAC'


print(tableize(inputDf))

print(inputDf.index.duplicated())

# copy new strategy to output
outputDf.loc[:,BULK_COL_REGION] = inputDf.loc[:, TMP_FIELD]

# only include campaigns with changed strategy in bulk file
outputDf = outputDf[ inputDf[TMP_FIELD].notnull() & (inputDf[RPT_COL_REGION] != inputDf[TMP_FIELD]) ]

Post generated on 2024-02-22 06:05:49 GMT