Script 343: MediaType tagging

Purpose

Python script for media type tagging.

To Elaborate

This Python script is used for media type tagging. It assigns media types and sub-types to different rows in a DataFrame based on specific conditions. The media types and sub-types are determined by the values in certain columns of the DataFrame.

Walking Through the Code

  1. The script defines column constants and client timezone.
  2. It initializes some variables and imports necessary libraries.
  3. The script prints the input DataFrame in a table format.
  4. It uses the loc function to assign media types and sub-types to rows in the DataFrame based on specific conditions.
  5. The conditions are defined using the str.contains function to check if certain values are present in specific columns.
  6. The assigned media types and sub-types are stored in temporary fields in the DataFrame.
  7. The script prints the updated DataFrame in a table format.
  8. The media types and sub-types are copied from the temporary fields to the corresponding columns in the output DataFrame.
  9. The script prints the output DataFrame in a table format.

Vitals

  • Script ID : 343
  • Client ID / Customer ID: 1306925579 / 60269545
  • Action Type: Bulk Upload
  • Item Changed: AdGroup
  • Output Columns: Account, Campaign, Group, Media sub-type, Media Type
  • Linked Datasource: M1 Report
  • Reference Datasource: None
  • Owner: Tom McCaughey (tmccaughey@marinsoftware.com)
  • Created by Tom McCaughey on 2023-10-12 14:48
  • Last Updated by Tom McCaughey on 2024-04-18 10:47
> See it in Action

Python Code

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RPT_COL_ACCOUNT = 'Account'
RPT_COL_CAMPAIGN = 'Campaign'
RPT_COL_GROUP = 'Group'
RPT_COL_MEDIA_SUBTYPE = 'Media sub-type'
RPT_COL_MEDIA_TYPE = 'Media Type'
RPT_COL_ACCOUNT_PUBLISHER_NAME = 'Publisher Name'
RPT_COL_ACCOUNT_PUBLISHER = 'Publisher'
BULK_COL_ACCOUNT = 'Account'
BULK_COL_CAMPAIGN = 'Campaign'
BULK_COL_GROUP = 'Group'
BULK_COL_MEDIA_SUBTYPE = 'Media sub-type'
BULK_COL_MEDIA_TYPE = 'Media Type'
BULK_COL_ACCOUNT_PUBLISHER_NAME = 'Publisher Name'
BULK_COL_ACCOUNT_PUBLISHER = 'Publisher'

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

TMP_MediaType = 'Unknown Media Type'
TMP_SubType = 'Unknown Media sub-type'
# blank out tmp field
inputDf[TMP_MediaType] = numpy.nan
inputDf[TMP_SubType] = numpy.nan

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


inputDf.loc[ (inputDf[RPT_COL_ACCOUNT_PUBLISHER_NAME].str.contains('Taboola', na=False)) , TMP_MediaType ] = 'Native'
inputDf.loc[ (inputDf[RPT_COL_ACCOUNT_PUBLISHER_NAME].str.contains('Taboola', na=False)) , TMP_SubType ] = 'Native'
inputDf.loc[ (inputDf[RPT_COL_ACCOUNT_PUBLISHER_NAME].str.contains('TikTok', na=False)) , TMP_MediaType ] = 'Social'
inputDf.loc[ (inputDf[RPT_COL_ACCOUNT_PUBLISHER_NAME].str.contains('TikTok', na=False)) , TMP_SubType ] = 'TikTok'
inputDf.loc[ (inputDf[RPT_COL_ACCOUNT_PUBLISHER_NAME].str.contains('Facebook', na=False)) , TMP_MediaType ] = 'Social'
inputDf.loc[ (inputDf[RPT_COL_ACCOUNT_PUBLISHER_NAME].str.contains('Facebook', na=False)) , TMP_SubType ] = 'Meta'
inputDf.loc[ (inputDf[RPT_COL_ACCOUNT_PUBLISHER_NAME].str.contains('BING', na=False)) , TMP_MediaType ] = 'SEM'
inputDf.loc[ (inputDf[RPT_COL_ACCOUNT_PUBLISHER_NAME].str.contains('BING', na=False)) , TMP_SubType ] = 'SEM-Bing'
inputDf.loc[ (inputDf[RPT_COL_ACCOUNT_PUBLISHER_NAME].str.contains('Google', na=False)) , TMP_MediaType ] = 'SEM'
inputDf.loc[ (inputDf[RPT_COL_ACCOUNT_PUBLISHER_NAME].str.contains('Google', na=False)) , TMP_SubType ] = 'SEM-Google'
inputDf.loc[ (inputDf[RPT_COL_ACCOUNT_PUBLISHER_NAME].str.contains('Google', na=False)) & (inputDf[RPT_COL_CAMPAIGN].str.contains('\[GDN\]', na=False)), TMP_MediaType ] = 'Display'
inputDf.loc[ (inputDf[RPT_COL_ACCOUNT_PUBLISHER_NAME].str.contains('Google', na=False)) & (inputDf[RPT_COL_CAMPAIGN].str.contains('\[GDN\]', na=False)), TMP_SubType ] = 'Standard display'
inputDf.loc[ (inputDf[RPT_COL_ACCOUNT_PUBLISHER_NAME].str.contains('Google', na=False)) & (inputDf[RPT_COL_CAMPAIGN].str.contains('\[Demand Gen\]', na=False)), TMP_MediaType ] = 'Display & Online video'
inputDf.loc[ (inputDf[RPT_COL_ACCOUNT_PUBLISHER_NAME].str.contains('Google', na=False)) & (inputDf[RPT_COL_CAMPAIGN].str.contains('\[Demand Gen\]', na=False)), TMP_SubType ] = 'Demand Gen'
inputDf.loc[ (inputDf[RPT_COL_ACCOUNT_PUBLISHER_NAME].str.contains('Google', na=False)) & (inputDf[RPT_COL_CAMPAIGN].str.contains('\[YT\]', na=False)), TMP_MediaType ] = 'Online video'
inputDf.loc[ (inputDf[RPT_COL_ACCOUNT_PUBLISHER_NAME].str.contains('Google', na=False)) & (inputDf[RPT_COL_CAMPAIGN].str.contains('\[YT\]', na=False)), TMP_SubType ] = 'VIDEO-Instream'
inputDf.loc[ (inputDf[RPT_COL_ACCOUNT_PUBLISHER_NAME].str.contains('Google', na=False)) & (inputDf[RPT_COL_CAMPAIGN].str.contains('\[YT\]', na=False)) & (inputDf[RPT_COL_CAMPAIGN].str.contains('Bumper', na=False)), TMP_SubType ] = 'VIDEO-Bumper'
inputDf.loc[ (inputDf[RPT_COL_ACCOUNT].str.contains('Adform', na=False)) & (inputDf[RPT_COL_GROUP].str.contains('\[DISPLAY\]', na=False)), TMP_MediaType ] = 'Display'
inputDf.loc[ (inputDf[RPT_COL_ACCOUNT].str.contains('Adform', na=False)) & (inputDf[RPT_COL_GROUP].str.contains('\[DISPLAY\]', na=False)), TMP_SubType ] = 'Standard display'
inputDf.loc[ (inputDf[RPT_COL_ACCOUNT].str.contains('Adform', na=False)) & (inputDf[RPT_COL_GROUP].str.contains('\[DISPLAY-Premium\]', na=False)), TMP_MediaType ] = 'Display'
inputDf.loc[ (inputDf[RPT_COL_ACCOUNT].str.contains('Adform', na=False)) & (inputDf[RPT_COL_GROUP].str.contains('\[DISPLAY-Premium\]', na=False)), TMP_SubType ] = 'Premium display'
inputDf.loc[ (inputDf[RPT_COL_ACCOUNT].str.contains('Adform', na=False)) & (inputDf[RPT_COL_GROUP].str.contains('\[Email-Newsletter\]', na=False)), TMP_MediaType ] = 'Email'
inputDf.loc[ (inputDf[RPT_COL_ACCOUNT].str.contains('Adform', na=False)) & (inputDf[RPT_COL_GROUP].str.contains('\[Email-Newsletter\]', na=False)), TMP_SubType ] = 'Email-Newsletter'
inputDf.loc[ (inputDf[RPT_COL_ACCOUNT].str.contains('Adform', na=False)) & (inputDf[RPT_COL_GROUP].str.contains('\[Native\]', na=False)), TMP_MediaType ] = 'Native'
inputDf.loc[ (inputDf[RPT_COL_ACCOUNT].str.contains('Adform', na=False)) & (inputDf[RPT_COL_GROUP].str.contains('\[Native\]', na=False)), TMP_SubType ] = 'Native'
inputDf.loc[ (inputDf[RPT_COL_ACCOUNT].str.contains('Adform', na=False)) & (inputDf[RPT_COL_GROUP].str.contains('\[AUDIO - Podcast\]', na=False)), TMP_MediaType ] = 'Online Audio'
inputDf.loc[ (inputDf[RPT_COL_ACCOUNT].str.contains('Adform', na=False)) & (inputDf[RPT_COL_GROUP].str.contains('\[AUDIO - Podcast\]', na=False)), TMP_SubType ] = 'Audio-Podcast'
inputDf.loc[ (inputDf[RPT_COL_ACCOUNT].str.contains('Adform', na=False)) & (inputDf[RPT_COL_GROUP].str.contains('\[VIDEO-Instream\]', na=False)), TMP_MediaType ] = 'Online Video'
inputDf.loc[ (inputDf[RPT_COL_ACCOUNT].str.contains('Adform', na=False)) & (inputDf[RPT_COL_GROUP].str.contains('\[VIDEO-Instream\]', na=False)), TMP_SubType ] = 'VIDEO-Instream'
inputDf.loc[ (inputDf[RPT_COL_ACCOUNT].str.contains('Adform', na=False)) & (inputDf[RPT_COL_GROUP].str.contains('\[VIDEO-Bumper\]', na=False)), TMP_MediaType ] = 'Online Video'
inputDf.loc[ (inputDf[RPT_COL_ACCOUNT].str.contains('Adform', na=False)) & (inputDf[RPT_COL_GROUP].str.contains('\[VIDEO-Bumper\]', na=False)), TMP_SubType ] = 'VIDEO-Bumper'
inputDf.loc[ (inputDf[RPT_COL_ACCOUNT].str.contains('Adform', na=False)) & (inputDf[RPT_COL_GROUP].str.contains('OOH', na=False)), TMP_MediaType ] = 'OOH'
inputDf.loc[ (inputDf[RPT_COL_ACCOUNT].str.contains('Adform', na=False)) & (inputDf[RPT_COL_GROUP].str.contains('OOH', na=False)), TMP_SubType ] = 'OOH'
inputDf.loc[ (inputDf[RPT_COL_ACCOUNT].str.contains('Adform', na=False)) & (inputDf[RPT_COL_GROUP].str.contains('Radio', na=False)), TMP_MediaType ] = 'Radio'
inputDf.loc[ (inputDf[RPT_COL_ACCOUNT].str.contains('Adform', na=False)) & (inputDf[RPT_COL_GROUP].str.contains('Radio', na=False)), TMP_SubType ] = 'Radio'
inputDf.loc[ (inputDf[RPT_COL_ACCOUNT].str.contains('Adform', na=False)) & (inputDf[RPT_COL_GROUP].str.contains('TV', na=False)), TMP_MediaType ] = 'TV'
inputDf.loc[ (inputDf[RPT_COL_ACCOUNT].str.contains('Adform', na=False)) & (inputDf[RPT_COL_GROUP].str.contains('TV', na=False)), TMP_SubType ] = 'TV'
inputDf.loc[ (inputDf[RPT_COL_ACCOUNT].str.contains('Adform', na=False)) & (inputDf[RPT_COL_GROUP].str.contains('Print', na=False)), TMP_MediaType ] = 'Print'
inputDf.loc[ (inputDf[RPT_COL_ACCOUNT].str.contains('Adform', na=False)) & (inputDf[RPT_COL_GROUP].str.contains('Print', na=False)), TMP_SubType ] = 'Print'
inputDf.loc[ (inputDf[RPT_COL_ACCOUNT].str.contains('Offline', na=False)) & (inputDf[RPT_COL_GROUP].str.contains('OOH', na=False)), TMP_MediaType ] = 'OOH'
inputDf.loc[ (inputDf[RPT_COL_ACCOUNT].str.contains('Offline', na=False)) & (inputDf[RPT_COL_GROUP].str.contains('OOH', na=False)), TMP_SubType ] = 'OOH'
inputDf.loc[ (inputDf[RPT_COL_ACCOUNT].str.contains('Offline', na=False)) & (inputDf[RPT_COL_GROUP].str.contains('Radio', na=False)), TMP_MediaType ] = 'Radio'
inputDf.loc[ (inputDf[RPT_COL_ACCOUNT].str.contains('Offline', na=False)) & (inputDf[RPT_COL_GROUP].str.contains('Radio', na=False)), TMP_SubType ] = 'Radio'
inputDf.loc[ (inputDf[RPT_COL_ACCOUNT].str.contains('Offline', na=False)) & (inputDf[RPT_COL_GROUP].str.contains('TV', na=False)), TMP_MediaType ] = 'TV'
inputDf.loc[ (inputDf[RPT_COL_ACCOUNT].str.contains('Offline', na=False)) & (inputDf[RPT_COL_GROUP].str.contains('TV', na=False)), TMP_SubType ] = 'TV'
inputDf.loc[ (inputDf[RPT_COL_ACCOUNT].str.contains('Offline', na=False)) & (inputDf[RPT_COL_GROUP].str.contains('Print', na=False)), TMP_MediaType ] = 'Print'
inputDf.loc[ (inputDf[RPT_COL_ACCOUNT].str.contains('Offline', na=False)) & (inputDf[RPT_COL_GROUP].str.contains('Print', na=False)), TMP_SubType ] = 'Print'
inputDf.loc[ (inputDf[RPT_COL_ACCOUNT].str.contains('Offline', na=False)) & (inputDf[RPT_COL_GROUP].str.contains('\[DISPLAY\]', na=False)), TMP_MediaType ] = 'Display'
inputDf.loc[ (inputDf[RPT_COL_ACCOUNT].str.contains('Offline', na=False)) & (inputDf[RPT_COL_GROUP].str.contains('\[DISPLAY\]', na=False)), TMP_SubType ] = 'Standard display'
inputDf.loc[ (inputDf[RPT_COL_ACCOUNT].str.contains('Offline', na=False)) & (inputDf[RPT_COL_GROUP].str.contains('\[DISPLAY-Premium\]', na=False)), TMP_MediaType ] = 'Display'
inputDf.loc[ (inputDf[RPT_COL_ACCOUNT].str.contains('Offline', na=False)) & (inputDf[RPT_COL_GROUP].str.contains('\[DISPLAY-Premium\]', na=False)), TMP_SubType ] = 'Premium display'
inputDf.loc[ (inputDf[RPT_COL_ACCOUNT].str.contains('Offline', na=False)) & (inputDf[RPT_COL_GROUP].str.contains('\[Email-Newsletter\]', na=False)), TMP_MediaType ] = 'Email'
inputDf.loc[ (inputDf[RPT_COL_ACCOUNT].str.contains('Offline', na=False)) & (inputDf[RPT_COL_GROUP].str.contains('\[Email-Newsletter\]', na=False)), TMP_SubType ] = 'Email-Newsletter'
inputDf.loc[ (inputDf[RPT_COL_ACCOUNT].str.contains('Offline', na=False)) & (inputDf[RPT_COL_GROUP].str.contains('\[Native\]', na=False)), TMP_MediaType ] = 'Native'
inputDf.loc[ (inputDf[RPT_COL_ACCOUNT].str.contains('Offline', na=False)) & (inputDf[RPT_COL_GROUP].str.contains('\[Native\]', na=False)), TMP_SubType ] = 'Native'
inputDf.loc[ (inputDf[RPT_COL_ACCOUNT].str.contains('Offline', na=False)) & (inputDf[RPT_COL_GROUP].str.contains('\[AUDIO - Podcast\]', na=False)), TMP_MediaType ] = 'Online Audio'
inputDf.loc[ (inputDf[RPT_COL_ACCOUNT].str.contains('Offline', na=False)) & (inputDf[RPT_COL_GROUP].str.contains('\[AUDIO - Podcast\]', na=False)), TMP_SubType ] = 'Audio-Podcast'
inputDf.loc[ (inputDf[RPT_COL_ACCOUNT].str.contains('Offline', na=False)) & (inputDf[RPT_COL_GROUP].str.contains('\[VIDEO-Instream\]', na=False)), TMP_MediaType ] = 'Online Video'
inputDf.loc[ (inputDf[RPT_COL_ACCOUNT].str.contains('Offline', na=False)) & (inputDf[RPT_COL_GROUP].str.contains('\[VIDEO-Instream\]', na=False)), TMP_SubType ] = 'VIDEO-Instream'
inputDf.loc[ (inputDf[RPT_COL_ACCOUNT].str.contains('Offline', na=False)) & (inputDf[RPT_COL_GROUP].str.contains('\[VIDEO-Bumper\]', na=False)), TMP_MediaType ] = 'Online Video'
inputDf.loc[ (inputDf[RPT_COL_ACCOUNT].str.contains('Offline', na=False)) & (inputDf[RPT_COL_GROUP].str.contains('\[VIDEO-Bumper\]', na=False)), TMP_SubType ] = 'VIDEO-Bumper'
inputDf.loc[ (inputDf[RPT_COL_ACCOUNT].str.contains('Email', na=False)) & (inputDf[RPT_COL_GROUP].str.contains('\[Email-Newsletter\]', na=False)), TMP_MediaType ] = 'Email'
inputDf.loc[ (inputDf[RPT_COL_ACCOUNT].str.contains('Email', na=False)) & (inputDf[RPT_COL_GROUP].str.contains('\[Email-Newsletter\]', na=False)), TMP_SubType ] = 'Email-Newsletter'
inputDf.loc[ (inputDf[RPT_COL_ACCOUNT].str.contains('Email', na=False)) & (inputDf[RPT_COL_GROUP].str.contains('\[Email-Standalone\]', na=False)), TMP_MediaType ] = 'Email'
inputDf.loc[ (inputDf[RPT_COL_ACCOUNT].str.contains('Email', na=False)) & (inputDf[RPT_COL_GROUP].str.contains('\[Email-Standalone\]', na=False)), TMP_SubType ] = 'Email-Standalone'
inputDf.loc[ (inputDf[RPT_COL_ACCOUNT].str.contains('Email', na=False)) & (inputDf[RPT_COL_GROUP].str.contains('\[SMS\]', na=False)), TMP_MediaType ] = 'SMS'
inputDf.loc[ (inputDf[RPT_COL_ACCOUNT].str.contains('Email', na=False)) & (inputDf[RPT_COL_GROUP].str.contains('\[SMS\]', na=False)), TMP_SubType ] = 'SMS'
inputDf.loc[ (inputDf[RPT_COL_ACCOUNT].str.contains('Email', na=False)) & (inputDf[RPT_COL_GROUP].str.contains('\[Quiz\]', na=False)), TMP_MediaType ] = 'Quiz'
inputDf.loc[ (inputDf[RPT_COL_ACCOUNT].str.contains('Email', na=False)) & (inputDf[RPT_COL_GROUP].str.contains('\[Quiz\]', na=False)), TMP_SubType ] = 'Quiz-Primetime'
inputDf.loc[ (inputDf[RPT_COL_ACCOUNT].str.contains('Email', na=False)) & (inputDf[RPT_COL_GROUP].str.contains('Affiliate', na=False)), TMP_MediaType ] = 'Affiliate'
inputDf.loc[ (inputDf[RPT_COL_ACCOUNT].str.contains('Email', na=False)) & (inputDf[RPT_COL_GROUP].str.contains('\[Affiliate]', na=False)), TMP_SubType ] = 'Affiliate'
inputDf.loc[ (inputDf[RPT_COL_ACCOUNT].str.contains('Email', na=False)) & (inputDf[RPT_COL_GROUP].str.contains('\[Affiliate-cashback]', na=False)), TMP_SubType ] = 'Affiliate-cashback'
inputDf.loc[ (inputDf[RPT_COL_ACCOUNT].str.contains('Email', na=False)) & (inputDf[RPT_COL_GROUP].str.contains('\[Affiliate-campaign]', na=False)), TMP_SubType ] = 'Affiliate-campaign'
inputDf.loc[ (inputDf[RPT_COL_ACCOUNT].str.contains('Email', na=False)) & (inputDf[RPT_COL_GROUP].str.contains('\[Affiliate-partner]', na=False)), TMP_SubType ] = 'Affiliate-partner'
print(tableize(inputDf))

#print(inputDf.index.duplicated())

# copy new strategy to output
outputDf.loc[:,BULK_COL_MEDIA_TYPE] = inputDf.loc[:, TMP_MediaType]
outputDf.loc[:,BULK_COL_MEDIA_SUBTYPE] = inputDf.loc[:, TMP_SubType]

#outputDf = outputDf[inputDf[TMP_MediaType].notnull() & inputDf[TMP_SubType].notnull() & ~inputDf[BULK_COL_CAMPAIGN].str.contains('"')]
print(tableize(outputDf))

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

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