A simple data pipeline package
Project description
data-pipeline
A simple and reusable Python data pipeline package for loading, cleaning, and validating CSV data.
This package is designed for beginners and data analysts who want a clean, structured way to process data.
Features
- Load CSV files into pandas DataFrames
- Clean data by removing duplicates and missing values
- Validate data to ensure it is usable
- Simple one-function pipeline execution
- Lightweight and easy to integrate into any project
Installation
Install the package from PyPI using pip:
pip install data_pipeline_tool
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
Built Distribution
Filter files by name, interpreter, ABI, and platform.
If you're not sure about the file name format, learn more about wheel file names.
Copy a direct link to the current filters
File details
Details for the file data_pipeline_tool-0.1.2.tar.gz.
File metadata
- Download URL: data_pipeline_tool-0.1.2.tar.gz
- Upload date:
- Size: 4.2 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/6.2.0 CPython/3.13.5
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
62329e6c0ac60003930dfd9f87e3c47d2d198dcbf510d8f81c91665bf4c729db
|
|
| MD5 |
9662ef9e9b1d7410384f748a9501c92c
|
|
| BLAKE2b-256 |
c0a40fb79934980b01b8375134456d184daefe8dcd3608d712967d357a8f43ae
|
File details
Details for the file data_pipeline_tool-0.1.2-py3-none-any.whl.
File metadata
- Download URL: data_pipeline_tool-0.1.2-py3-none-any.whl
- Upload date:
- Size: 5.6 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/6.2.0 CPython/3.13.5
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
17acf10a9e3978a6ead33acf5f284f0d69b41f84fc8268d1f24cafcc29ef6b56
|
|
| MD5 |
01341ae6c2cbfbefc2733c6e016db13f
|
|
| BLAKE2b-256 |
01bf60ce01292bd702b26abff657509c3dd08db4c887501549f38bd921e203fc
|
