Window Function

Endpoint: POST /window-function

Request Parameters

File Upload

• file (required): The file to be processed. Supported formats include CSV, Excel, etc.

Form Parameters

• partition_by (optional): A list of columns to partition the data by. If not provided, the entire dataset is treated as a single partition.
• order_by (optional): A list of columns to order the data by within each partition.
• function (required): The window function to apply. Supported values:
  • SUM: Cumulative sum.
  • ROW_NUMBER: Row number within each partition.
  • AVG: Cumulative average.
  • MIN: Cumulative minimum.
  • MAX: Cumulative maximum.
  • COUNT: Cumulative count.
  • STDDEV: Cumulative standard deviation.
  • VARIANCE: Cumulative variance.
• input_column (required): The column to apply the window function to.
• output_column (required): The column to store the results of the window function.

Processing Logic

1. Read the uploaded file: The file is converted into a Pandas DataFrame.
2. Validate columns:
   • Checks if the input_column exists in the DataFrame.
   • Checks if all columns in partition_by and order_by exist in the DataFrame.
3. Sort the data: If partition_by or order_by is provided, the data is sorted accordingly.
4. Apply the window function:
   • SUM: Computes the cumulative sum for the input_column within each partition.
   • ROW_NUMBER: Assigns a row number to each row within each partition.
   • AVG: Computes the cumulative average for the input_column within each partition.
   • MIN: Computes the cumulative minimum for the input_column within each partition.
   • MAX: Computes the cumulative maximum for the input_column within each partition.
   • COUNT: Computes the cumulative count for the input_column within each partition.
   • STDDEV: Computes the cumulative standard deviation for the input_column within each partition.
   • VARIANCE: Computes the cumulative variance for the input_column within each partition.
5. Store the results: The results of the window function are stored in the output_column.
6. Return the modified file: The modified file is provided for download with the filename appended with _window_function.

Example Request

curl -X POST "http://localhost:8000/window-function" \
-F "file=@data.csv" \
-F "partition_by=category" \
-F "order_by=date" \
-F "function=SUM" \
-F "input_column=value" \
-F "output_column=cumulative_sum"