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A tool for cleaning and processing CPCB air quality data

Project description

AirPy Tool

A Python package for cleaning and processing air quality data.

Installation

You can install AirPy from PyPI:

pip install airpy-tool

You can also install directly from GitHub:

pip install git+https://github.com/chandankr014/airpy-tool.git

Or clone the repository and install locally:

git clone https://github.com/chandankr014/airpy-tool.git
cd airpy-tool
pip install -e .

Usage

Command-line Interface

AirPy provides a command-line tool for processing air quality data:

# Process all data
airpy

# Process data for a specific city
airpy --city "Delhi"

# Process live data
airpy --live

# Specify custom directories
airpy --raw-dir /path/to/raw/data --clean-dir /path/to/output

# Process specific pollutants
airpy --pollutants PM25 PM10 NO2

Python API

You can also use AirPy as a Python library:

from airpy.core.processor import process_data

# Process data with default settings
process_data()

# Process data for a specific city
process_data(city="Delhi")

# Process live data
process_data(live=True)

# Specify custom directories
process_data(raw_dir="/path/to/raw/data", clean_dir="/path/to/output")

# Process specific pollutants
process_data(pollutants=["PM25", "PM10", "NO2"])

Features

AirPy provides the following features for air quality data processing:

  • Data cleaning and formatting
  • Outlier detection and removal
  • Consecutive repeat detection
  • Unit inconsistency correction for nitrogen compounds
  • Time series analysis and visualization

Data Format

AirPy supports the following file formats:

  • CSV files
  • Excel (XLSX) files

The data should follow one of these filename formats:

  • 15Min_YEAR_site_ID_STATION_CITY_ORG_15Min.csv
  • Raw_data_15Min_YEAR_site_ID_STATION_CITY_ORG_15Min.csv
  • site_ID_YEAR.csv
  • Live data format: site_IDYYYYMMDDHHMMSS.xlsx

License

This project is licensed under the MIT License - see the LICENSE file for details.

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