Analyzing the data of air quality using traditional data analytical methods with the help of R studio
We decided to analyze the air quality data of India to find some underlying principles or patterns which might give me an insight into how severe the problem is.
This data is a dirty version of the Historical Daily Ambient Air Quality Data released by the Ministry of Environment and Forests and Central Pollution Control Board of India under the National Data Sharing and Accessibility Policy (NDSAP). The dataset contains the following features :
- stn code : A code is given to each station that recorded the data.
- sampling date: The date when the data was recorded.
- state: It represents the states whose air quality data is measured.
- location: It represents the city whose air quality data is measured.
- agency: Name of the agency that measured the data.
- type: The type of area where the measurement was made.
- so2: The amount of Sulphur Dioxide measured.
- no2: The amount of Nitrogen Dioxide measured
- rspm: Respirable Suspended Particulate Matter measured.
- spm: Suspended Particulate Matter measured.
- location monitoring station: It indicates the location of the monitoring area.
- pm2 5: It represents the value of particulate matter measured.
- For the repository.
- Make changes in the .RMD file by creating a new code chunk'
- Knit the .RMD file and view the analysis