Air Quality Of India - An Extensive Exploratory Data Analysis
In this EDA project, I have analyzed the air quality of several cities in India based on data compiled by Central Pollution Control Board (CPCB) from 2010 to 2023.
Air pollution is a pressing concern in India, where rapidly growing urbanization, industrialization, and vehicular emissions have contributed to deteriorating air quality. With its large population and diverse geographical features, India faces significant challenges in managing and mitigating pollution levels. The country has been grappling with high levels of particulate matter, including PM10 and PM2.5, which pose serious health risks. The government has implemented various measures and policies to address this issue, including the National Air Quality Index (NAQI), initiatives promoting renewable energy, and stricter emission standards for industries and vehicles. This EDA project focuses on analyzing air quality data from multiple cities in India, aiming to gain insights into pollution trends, identify contributing factors, and highlight the importance of ongoing efforts to combat air pollution.
The aim of this project is to conduct an exploratory data analysis (EDA) on the provided air quality dataset for Indian cities. By analyzing the data, we seek to uncover meaningful insights into the temporal and spatial variations of air pollution levels across different cities and states in India. Our objective is to identify patterns, trends, and potential correlations between various pollutants, such as PM2.5, PM10, NO2, NOx, NH3, SO2, CO, Ozone, Benzene, Toluene, and other relevant parameters. Through this analysis, we aim to shed light on the severity and distribution of air pollution in India, understand the impact of different pollutants on air quality, and highlight areas that require immediate attention and intervention. By gaining a deeper understanding of the data, we strive to contribute to informed decision-making, policy formulation, and initiatives aimed at mitigating air pollution and improving the overall well-being of the population.
Project Outline
- Setting Up The Project
- Downloading & Importing Modules
- Downloading the Dataset
2. Exploring the Data
- Available Data
- Available Parameters
- Data and Parameters that the exploration is focused on
- Parameter Definitions and Significance
3. Data Processing Pipeline
- Data Reading
- Feature Engineering
- Data Filtering
- Putting it all together
4. Open Ended Exploratory Data Analysis and Visualization
- Univariate Analysis
- Time Series Analysis
- Multivariate Analysis
5. Ask & Answer Questions
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Summary & Conclusions
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Future Work & Reference