dataforgetoolkit 1.0.5

It is a library that facilitates converting CSV files to various formats (such as DataFrames or other CSV/Excel files) based on a JSON mapping

Project Title

DataForgeToolkit is a Python library for mapping CSV or Excel files based on JSON transformation mappings.

Description

DataForgeToolkit: Flexible Data Mapping for CSV/XLSX Files

The DataForgeToolkit is a Python library designed to streamline the process of converting CSV or Excel files into customized DataFrames based on user-defined JSON mapping configurations. Whether you're working with financial reports, customer datasets, or any other structured data, this toolkit empowers you to effortlessly transform raw data into actionable insights.

Features: Versatile File Support: Seamlessly process both CSV and Excel files, providing flexibility in handling various data formats commonly encountered in data analysis tasks.

Customizable Mapping: Define transformation mappings using a JSON file, allowing for precise specification of column names, data cleaning, and value substitutions tailored to your specific data requirements.

Efficient Data Processing: Automate data preprocessing tasks such as handling missing values, standardizing column names, and applying complex value mappings with ease.

Installation Usage/Examples

  pip install dataforgetoolkit

Define Transformation Mapping:

Create a JSON file specifying the transformation mappings for your data. Define column mappings, specify new column names, and define value substitutions as needed.

Use the Toolkit:

Import the DataForgeToolkit in your Python script and utilize the map function to convert your report files:

    from dataforgetoolkit import datamapper
    datamapper.map('report file path csv / xlsx format','mapping json file path')

Access Mapped Data:

Access the transformed data as a DataFrame for further analysis or export to other formats.

JSON Transformation Mapping

Transformation mappings are specified using a JSON file. Example:

{
    "transformation_mapping": [
        {
            "column": "Name",
            "new_name": "Student Name",
            "value_mappings": [
                {
                    "*": "Amit Singh"
                }
            ]
        },
        {
            "column": "Age_Column",
            "new_name": "Age",
            "value_mappings": [
                {
                    "FILTER": "30"
                }
            ]
        }
    ]
}

Authors

• @amitsingh

• Software Engineer

Contributing

Contributions are always welcome!

Please adhere to this project's code of conduct.

Suggest code and open PR/MR

Used By

'Intended Audience' :: Developers , Testers , BA