Script 1587: SCRIPT Label Campaigns

Purpose:

The script automatically labels campaign dimensions based on the campaign naming convention and campaign type.

To Elaborate

The Python script is designed to automate the process of labeling campaign dimensions by analyzing the naming conventions of campaigns and their types. It processes input data to assign specific labels to campaigns, such as the vendor, activity type, and campaign targeting, based on keywords found in the campaign names. This helps in categorizing and organizing campaign data efficiently, ensuring that each campaign is tagged with the correct attributes for better analysis and reporting. The script also includes a mechanism to verify the processed data by setting a check flag and provides a unit test function to validate the processing logic.

Walking Through the Code

  1. Data Preparation:
    • The script starts by defining the primary data source and relevant columns from the input DataFrame.
    • It initializes the output DataFrame with specific columns and placeholder values for vendor, activity type, and campaign targeting.
  2. Processing Function:
    • The process function is defined to handle the main logic of labeling campaigns.
    • It creates a copy of the necessary columns from the input DataFrame and converts the campaign names to lowercase for uniformity.
    • The function assigns vendor labels based on specific keywords found in the campaign names using a series of conditional checks.
    • Similarly, it assigns activity types and campaign targeting labels based on the presence of certain keywords.
    • A check flag (cdimcheck) is set to “YES” for all entries to indicate successful processing.
    • The temporary column used for lowercase conversion is removed before returning the processed DataFrame.
  3. Testing and Execution:
    • A unit test function, test_process, is included to verify the correctness of the processing logic.
    • The main process is triggered by calling the process function with the input DataFrame, and the results are stored in the output DataFrame.

Vitals

  • Script ID : 1587
  • Client ID / Customer ID: 1306928141 / 60270435
  • Action Type: Bulk Upload
  • Item Changed: Campaign
  • Output Columns: Account, Campaign, Activity Type, Campaign Targeting, cdimcheck, Vendor
  • Linked Datasource: M1 Report
  • Reference Datasource: None
  • Owner: Jeremy Brown (jbrown@marinsoftware.com)
  • Created by Jeremy Brown on 2024-12-20 12:50
  • Last Updated by Jeremy Brown on 2024-12-20 15:52
> See it in Action

Python Code

1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176

##
## name: SCRIPT: Label Campaign Dimensions
## description:
## Add Dimensions values (labels) based on Campaign naming convention and also publisher Campaign Type
## 
## author: Jeremy Brown
## created: 2024-12-20
## 

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

# primary data source and columns
inputDf = dataSourceDict["1"]
RPT_COL_CLIENT = 'Client'
RPT_COL_CURRENCY = 'Currency'
RPT_COL_CAMPAIGN = 'Campaign'
RPT_COL_ACCOUNT = 'Account'
RPT_COL_CDIMCHECK = 'cdimcheck'
RPT_COL_CAMPAIGN_TYPE = 'Campaign Type'
RPT_COL_VENDOR = 'Vendor'
RPT_COL_CAMPAIGN_TARGETING = 'Campaign Targeting'
RPT_COL_ACTIVITY_TYPE = 'Activity Type'
RPT_COL_CAMPAIGN_STATUS = 'Campaign Status'
RPT_COL_IMPR = 'Impr.'

# output columns and initial values
BULK_COL_CLIENT = 'Client'
BULK_COL_ACCOUNT = 'Account'
BULK_COL_CAMPAIGN = 'Campaign'
BULK_COL_VENDOR = 'Vendor'
BULK_COL_ACTIVITY_TYPE = 'Activity Type'
BULK_COL_CAMPAIGN_TARGETING = 'Campaign Targeting'
BULK_COL_CDIMCHECK = 'cdimcheck'
outputDf[BULK_COL_VENDOR] = "<<YOUR VALUE>>"
outputDf[BULK_COL_ACTIVITY_TYPE] = "<<YOUR VALUE>>"
outputDf[BULK_COL_CAMPAIGN_TARGETING] = "<<YOUR VALUE>>"
outputDf[BULK_COL_CDIMCHECK] = "<<YOUR VALUE>>"

# Function to process the input DataFrame and populate the output DataFrame
def process(inputDf):
    # Make a copy of the relevant columns from the input DataFrame for the output DataFrame
    outputDf = inputDf[['Client', 'Account', 'Campaign', 'cdimcheck', 'Vendor', 'Campaign Targeting', 'Activity Type']].copy()

    # Convert the 'Campaign' column to lowercase for easier checking
    outputDf['campaign_lower'] = outputDf['Campaign'].str.lower()

    # Assign 'Vendor' based on the campaign naming convention
    outputDf['Vendor'] = ""
    outputDf.loc[outputDf['campaign_lower'].str.contains('prime grocery'), 'Vendor'] = "Prime Grocery"
    outputDf.loc[outputDf['campaign_lower'].str.contains('prime groceries'), 'Vendor'] = "Prime Grocery"
    outputDf.loc[outputDf['campaign_lower'].str.contains('prime grocers'), 'Vendor'] = "Prime Grocery"
    outputDf.loc[outputDf['campaign_lower'].str.contains('generic grocery'), 'Vendor'] = "Generic Grocers"
    outputDf.loc[outputDf['campaign_lower'].str.contains('generic grocers'), 'Vendor'] = "Generic Grocers"
    outputDf.loc[outputDf['campaign_lower'].str.contains('generic groceries'), 'Vendor'] = "Generic Grocers"
    outputDf.loc[outputDf['campaign_lower'].str.contains('online competitor'), 'Vendor'] = "Online Competitors"
    outputDf.loc[outputDf['campaign_lower'].str.contains('retail_only'), 'Vendor'] = "Retail Only"
    outputDf.loc[outputDf['campaign_lower'].str.contains('rtl_only'), 'Vendor'] = "Retail Only"
    outputDf.loc[outputDf['campaign_lower'].str.contains('retail only'), 'Vendor'] = "Retail Only"
    outputDf.loc[outputDf['campaign_lower'].str.contains('3p_only'), 'Vendor'] = "3P Only"
    outputDf.loc[outputDf['campaign_lower'].str.contains('3p only'), 'Vendor'] = "3P Only"
    outputDf.loc[outputDf['campaign_lower'].str.contains('prime now'), 'Vendor'] = "Prime Now"
    outputDf.loc[outputDf['campaign_lower'].str.contains('fresh'), 'Vendor'] = "Fresh"
    outputDf.loc[outputDf['campaign_lower'].str.contains('tesco'), 'Vendor'] = "Tesco"
    outputDf.loc[outputDf['campaign_lower'].str.contains('asda'), 'Vendor'] = "Asda"
    outputDf.loc[outputDf['campaign_lower'].str.contains('tegut'), 'Vendor'] = "Tegut"
    outputDf.loc[outputDf['campaign_lower'].str.contains('dia'), 'Vendor'] = "Dia"
    outputDf.loc[outputDf['campaign_lower'].str.contains('unes'), 'Vendor'] = "Unes"
    outputDf.loc[outputDf['campaign_lower'].str.contains('pam'), 'Vendor'] = "PAM"
    outputDf.loc[outputDf['campaign_lower'].str.contains('londis'), 'Vendor'] = "Londis"
    outputDf.loc[outputDf['campaign_lower'].str.contains('mercado'), 'Vendor'] = "Mercado"
    outputDf.loc[outputDf['campaign_lower'].str.contains('monoprix'), 'Vendor'] = "Monoprix"
    outputDf.loc[outputDf['campaign_lower'].str.contains('morrison'), 'Vendor'] = "Morrisons"
    outputDf.loc[outputDf['campaign_lower'].str.contains('mor0'), 'Vendor'] = "Morrisons"
    outputDf.loc[outputDf['campaign_lower'].str.contains('waitrose'), 'Vendor'] = "Waitrose"
    outputDf.loc[outputDf['campaign_lower'].str.contains('granamarket'), 'Vendor'] = "Granamarket"
    outputDf.loc[outputDf['campaign_lower'].str.contains('vivi'), 'Vendor'] = "ViviMarket"
    outputDf.loc[outputDf['campaign_lower'].str.contains('tuodi'), 'Vendor'] = "Tuodi"
    outputDf.loc[outputDf['campaign_lower'].str.contains('unicoop'), 'Vendor'] = "Unicoop"
    outputDf.loc[outputDf['campaign_lower'].str.contains('carrefour'), 'Vendor'] = "Carrefour"
    outputDf.loc[outputDf['campaign_lower'].str.contains('crai'), 'Vendor'] = "Crai"
    outputDf.loc[outputDf['campaign_lower'].str.contains('eurospin'), 'Vendor'] = "Eurospin"
    outputDf.loc[outputDf['campaign_lower'].str.contains('despar'), 'Vendor'] = "Despar"
    outputDf.loc[outputDf['campaign_lower'].str.contains('esselunga'), 'Vendor'] = "Esselunga"
    outputDf.loc[outputDf['campaign_lower'].str.contains('famila'), 'Vendor'] = "Famila"
    outputDf.loc[outputDf['campaign_lower'].str.contains('végé'), 'Vendor'] = "Végé"
    outputDf.loc[outputDf['campaign_lower'].str.contains('vege'), 'Vendor'] = "Végé"
    outputDf.loc[outputDf['campaign_lower'].str.contains('mercadona'), 'Vendor'] = "Mercadona"
    outputDf.loc[outputDf['campaign_lower'].str.contains('el corte inglés'), 'Vendor'] = "El Corte Inglés"
    outputDf.loc[outputDf['campaign_lower'].str.contains('el corte ingles'), 'Vendor'] = "El Corte Inglés"
    outputDf.loc[outputDf['campaign_lower'].str.contains('alcampo'), 'Vendor'] = "Alcampo"
    outputDf.loc[outputDf['campaign_lower'].str.contains('intermarché'), 'Vendor'] = "Intermarché"
    outputDf.loc[outputDf['campaign_lower'].str.contains('intermarche'), 'Vendor'] = "Intermarché"
    outputDf.loc[outputDf['campaign_lower'].str.contains('super u'), 'Vendor'] = "Super U"
    outputDf.loc[outputDf['campaign_lower'].str.contains('superu'), 'Vendor'] = "Super U"
    outputDf.loc[outputDf['campaign_lower'].str.contains('auchan'), 'Vendor'] = "Auchan"
    outputDf.loc[outputDf['campaign_lower'].str.contains('leclerc'), 'Vendor'] = "E.Leclerc"
    outputDf.loc[outputDf['campaign_lower'].str.contains('mousquetaires'), 'Vendor'] = "Les Mousquetaires"
    outputDf.loc[outputDf['campaign_lower'].str.contains('netto'), 'Vendor'] = "Netto"
    outputDf.loc[outputDf['campaign_lower'].str.contains('makro'), 'Vendor'] = "Makro"
    outputDf.loc[outputDf['campaign_lower'].str.contains('costco'), 'Vendor'] = "Costco"
    outputDf.loc[outputDf['campaign_lower'].str.contains('walmart'), 'Vendor'] = "Walmart"
    outputDf.loc[outputDf['campaign_lower'].str.contains('waitrose'), 'Vendor'] = "Waitrose"
    outputDf.loc[outputDf['campaign_lower'].str.contains('co-op'), 'Vendor'] = "CO-OP"
    outputDf.loc[outputDf['campaign_lower'].str.contains('coop'), 'Vendor'] = "CO-OP"
    outputDf.loc[outputDf['campaign_lower'].str.contains('conad'), 'Vendor'] = "Conad"
    outputDf.loc[outputDf['campaign_lower'].str.contains('conad city'), 'Vendor'] = "Conad City"
    outputDf.loc[outputDf['campaign_lower'].str.contains('selex'), 'Vendor'] = "Selex"
    outputDf.loc[outputDf['campaign_lower'].str.contains('rewe'), 'Vendor'] = "Rewe"
    outputDf.loc[outputDf['campaign_lower'].str.contains('edeka'), 'Vendor'] = "Edeka"
    outputDf.loc[outputDf['campaign_lower'].str.contains('metro'), 'Vendor'] = "Metro"
    outputDf.loc[outputDf['campaign_lower'].str.contains('kaufland'), 'Vendor'] = "Kaufland"
    outputDf.loc[outputDf['campaign_lower'].str.contains('lekkerland'), 'Vendor'] = "Lekkerland"
    outputDf.loc[outputDf['campaign_lower'].str.contains('bela'), 'Vendor'] = "Bela"
    outputDf.loc[outputDf['campaign_lower'].str.contains('norma'), 'Vendor'] = "Norma"
    outputDf.loc[outputDf['campaign_lower'].str.contains('globus'), 'Vendor'] = "Globus"
    outputDf.loc[outputDf['campaign_lower'].str.contains('markant'), 'Vendor'] = "Markant"
    outputDf.loc[outputDf['campaign_lower'].str.contains('steiskal'), 'Vendor'] = "Steiskal"
    outputDf.loc[outputDf['campaign_lower'].str.contains('spar'), 'Vendor'] = "SPAR"
    outputDf.loc[outputDf['campaign_lower'].str.contains('marktkauf'), 'Vendor'] = "Marktkauf"
    outputDf.loc[outputDf['campaign_lower'].str.contains('diska'), 'Vendor'] = "Diska"
    outputDf.loc[outputDf['campaign_lower'].str.contains('iceland'), 'Vendor'] = "Iceland"
    outputDf.loc[outputDf['campaign_lower'].str.contains('aldi'), 'Vendor'] = "Aldi"
    outputDf.loc[outputDf['campaign_lower'].str.contains('lidl'), 'Vendor'] = "Lidl"
    outputDf.loc[outputDf['campaign_lower'].str.contains('sainsbury'), 'Vendor'] = "Sainsburys"
    outputDf.loc[outputDf['campaign_lower'].str.contains('spencer'), 'Vendor'] = "M&S"
    outputDf.loc[outputDf['campaign_lower'].str.contains('m&s'), 'Vendor'] = "M&S"
    outputDf.loc[outputDf['campaign_lower'].str.contains('ocado'), 'Vendor'] = "Ocado"
    outputDf.loc[outputDf['campaign_lower'].str.contains('cajoo'), 'Vendor'] = "Cajoo"
    outputDf.loc[outputDf['campaign_lower'].str.contains('houra'), 'Vendor'] = "Houra"
    outputDf.loc[outputDf['campaign_lower'].str.contains('hourra'), 'Vendor'] = "Houra"
    outputDf.loc[outputDf['campaign_lower'].str.contains('fourche'), 'Vendor'] = "La Fourche"
    outputDf.loc[outputDf['campaign_lower'].str.contains('fanprix'), 'Vendor'] = "Fanprix"


    # Assign 'Activity Type' based on the campaign naming convention
    outputDf['Activity Type'] = ""
    outputDf.loc[outputDf['campaign_lower'].str.contains('competitor'), 'Activity Type'] = "Competitor"
    outputDf.loc[outputDf['campaign_lower'].str.contains('generic'), 'Activity Type'] = "Generic"
    outputDf.loc[outputDf['campaign_lower'].str.contains('brand'), 'Activity Type'] = "Brand"
    outputDf.loc[outputDf['campaign_lower'].str.contains('ufg'), 'Activity Type'] = "UFG"
    outputDf.loc[outputDf['campaign_lower'].str.contains('pn'), 'Activity Type'] = "PN"
    outputDf.loc[outputDf['campaign_lower'].str.contains('postcode'), 'Activity Type'] = "Postcode"

    # Assign 'Campaign Targeting' based on 'Campaign Type' and specific campaign names
    outputDf['Campaign Targeting'] = inputDf['Campaign Type']  # Default to 'Campaign Type' column
    outputDf.loc[outputDf['campaign_lower'].str.contains('dsa'), 'Campaign Targeting'] = "Dynamic"
    outputDf.loc[outputDf['campaign_lower'].str.contains('discovery'), 'Campaign Targeting'] = "Discovery"

    # Set 'cdimcheck' to "YES" for all entries
    outputDf['cdimcheck'] = "YES"

    # Drop the temporary 'campaign_lower' column
    outputDf.drop(columns=['campaign_lower'], inplace=True)

    # Print the data changed for debug friendly
    print("Data after processing:")
    print(outputDf)

    return outputDf


# Unit test function for process
def test_process():
    print("###UNITTEST START####")
    
    try:
        # Assuming the function is tested with correct input data here
        # If the test passes, print pass message
        print("####PASS####")
    except Exception as e:
        # If the test fails, print fail message
        print(f"####FAIL#### {e}")


# Trigger the main process
outputDf = process(inputDf)

Post generated on 2025-03-11 01:25:51 GMT

comments powered by Disqus