Air Quality Index Analysis: Case Study

Download the dataset below to solve this Data Science case study on the Air Quality Index Analysis.

The dataset provided contains air quality measurements for Delhi during January 2023. The dataset includes the following variables:

  • date: Date and time of the measurement.
  • co: Concentration of Carbon Monoxide (CO) in µg/m³.
  • no: Concentration of Nitric Oxide (NO) in µg/m³.
  • no2: Concentration of Nitrogen Dioxide (NO2) in µg/m³.
  • o3: Concentration of Ozone (O3) in µg/m³.
  • so2: Concentration of Sulfur Dioxide (SO2) in µg/m³.
  • pm2_5: Concentration of Particulate Matter (PM2.5) in µg/m³.
  • pm10: Concentration of Particulate Matter (PM10) in µg/m³.
  • nh3: Concentration of Ammonia (NH3) in µg/m³.

The aim of this analysis is to gain insights into the air quality index in Delhi during January 2023, using the provided dataset. Your task is to:

  1. Calculate and analyze the Air Quality Index (AQI) based on pollutant concentrations.
  2. Examine the distribution of AQI categories to understand the prevalence of different air quality conditions.
  3. Investigate hourly trends in AQI to identify patterns and peak pollution hours.
  4. Explore correlations between different pollutants to assess their relationships.
  5. Compare the calculated AQI metrics with recommended air quality metrics to evaluate the severity of air quality in Delhi.

References to Solve this Data Science Case Study