The goal of india.air is to make Indian air pollution data easily
available for analysis and visualization in R.
The development version of india.air is available from
GitHub with:
# install.packages("devtools")
devtools::install_github("Reed-Math241/india.air")This data was made available by the Central Pollution Control Board of India and compiled by Vopani on kaggle.
The data is within the public domain under the CC-0 license.
The package india.air contains one dataset, india_air. See
?india_air for a description of each of the variables.
head(india_air)
#> # A tibble: 6 x 14
#> city date PM2.5 NO NO2 NOx CO SO2 O3 benzene toluene
#> <chr> <date> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 Ahmedabad 2015-01-01 NA 0.92 18.2 17.2 0.92 27.6 133. 0 0.02
#> 2 Ahmedabad 2015-01-02 NA 0.97 15.7 16.5 0.97 24.6 34.1 3.68 5.5
#> 3 Ahmedabad 2015-01-03 NA 17.4 19.3 29.7 17.4 29.1 30.7 6.8 16.4
#> 4 Ahmedabad 2015-01-04 NA 1.7 18.5 18.0 1.7 18.6 36.1 4.43 10.1
#> 5 Ahmedabad 2015-01-05 NA 22.1 21.4 37.8 22.1 39.3 39.3 7.01 18.9
#> 6 Ahmedabad 2015-01-06 NA 45.4 38.5 81.5 45.4 45.8 46.5 5.42 10.8
#> # … with 3 more variables: xylene <dbl>, AQI <dbl>, AQI_bucket <chr>The dataset contains air pollution data for six Indian cities between the years of 2015 and 2020 at the day level. Not all pollution measurements were collected in each city on each date, so there is some intrinsic missingness within the dataset.
india.air is great for visualizing patterns in air pollution over
time. For example,
india.air is also great for comparing pollution among cities:
You can also easily produce summary stats of air pollution in India
using india.air:
#How many days in 2019 was each city's AQI higher than 100 (the maximum "satisfactory" AQI)?
india_air %>%
filter(date >= mdy("1/1/2019") & date <= mdy("12/31/2019")) %>%
group_by(city) %>%
count(AQI > 100)
#> # A tibble: 12 x 3
#> # Groups: city [6]
#> city `AQI > 100` n
#> <chr> <lgl> <int>
#> 1 Ahmedabad TRUE 352
#> 2 Ahmedabad NA 13
#> 3 Chennai FALSE 218
#> 4 Chennai TRUE 147
#> 5 Delhi FALSE 43
#> 6 Delhi TRUE 322
#> 7 Hyderabad FALSE 201
#> 8 Hyderabad TRUE 164
#> 9 Lucknow FALSE 75
#> 10 Lucknow TRUE 290
#> 11 Mumbai FALSE 212
#> 12 Mumbai TRUE 153
#What was the average Ozone concentration in each city in 2019?
india_air %>%
filter(date >= mdy("1/1/2019") & date <= mdy("12/31/2019")) %>%
group_by(city) %>%
summarise(meanO3 = mean(O3, na.rm = TRUE))
#> # A tibble: 6 x 2
#> city meanO3
#> * <chr> <dbl>
#> 1 Ahmedabad 46.6
#> 2 Chennai 35.2
#> 3 Delhi 38.9
#> 4 Hyderabad 29.0
#> 5 Lucknow 32.2
#> 6 Mumbai 28.9
#What was the average carbon monoxide concentration in each city in 2018?
india_air %>%
filter(date >= mdy("1/1/2018") & date <= mdy("12/31/2018")) %>%
group_by(city) %>%
summarise(meanCO = mean(CO, na.rm = TRUE))
#> # A tibble: 6 x 2
#> city meanCO
#> * <chr> <dbl>
#> 1 Ahmedabad 33.2
#> 2 Chennai 0.870
#> 3 Delhi 1.41
#> 4 Hyderabad 0.622
#> 5 Lucknow 1.04
#> 6 Mumbai 1.57