Purpose:

The Python script processes offline booking data by copying it from a primary data source to an output data frame, allowing for custom output columns.

To Elaborate

The script is designed to handle offline booking data by taking an existing data frame from a specified data source and copying it to a new data frame. This process ensures that the structure and content of the original data are preserved in the output. The script allows for flexibility in defining custom output columns, which means users can modify the output structure as needed without affecting the original data. The script also includes a mechanism to skip output validations, providing users with the option to bypass certain checks if they are confident in the integrity of their data. This approach is useful in scenarios where data needs to be quickly transferred and potentially customized for further analysis or reporting.

Walking Through the Code

1. Data Source Initialization
   • The script begins by defining the primary data source, inputDf, which is extracted from a dictionary named dataSourceDict using a specific key (“2_2”). This data frame serves as the basis for further processing.
2. Data Frame Copying
   • A new data frame, outputDf, is created by copying inputDf. This ensures that the original data remains unchanged while allowing modifications to the copy. The column headers of outputDf are explicitly set to match those of inputDf.
3. Custom Output Columns
   • The script includes a flag, skip_output_validations, set to True, which allows users to bypass output validations. This feature provides flexibility in handling the data, especially when custom output columns are defined.
4. Displaying Data
   • The script concludes by printing the first few rows of outputDf using a function tableize, which formats the data for easy viewing. This step helps in verifying the data transfer and structure.

Vitals

• Script ID : 1495
• Client ID / Customer ID: 1306927965 / 60270405
• Action Type: Revenue Upload (Preview)
• Item Changed: None
• Output Columns: Date, Keyword ID, Creative ID, Keyword, Match Type, Group ID, Booking (Conv Date) Conv, Booking (Conv Date) Rev, First Booking (Conv Date) Conv, First Booking (Conv Date) Rev
• Linked Datasource: FTP/Email Feed
• Reference Datasource: Google Sheets
• Owner: Tom McCaughey (tmccaughey@marinsoftware.com)
• Created by Tom McCaughey on 2024-11-07 15:10
• Last Updated by Tom McCaughey on 2024-11-07 15:10

> See it in Action

Python Code

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##
## name: Offline Booking Data
## description:
##  
## 
## author: 
## created: 2024-11-07
## 

import datetime

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

# primary data source and columns
inputDf = dataSourceDict["2_2"]

# Copy inputDf to outputDf without changes and set column headers
outputDf = inputDf.copy()
outputDf.columns = inputDf.columns  # Set column headers to match those of inputDf

#allow for custom output columns
skip_output_validations = True

# user code start here
print(tableize(outputDf.head()))

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