Code

To replicate the results from the dataset, here's a short demo R code
for loading the dataset and plotting the monthly variations:

# Step 1) Read the data set
# Loading the required libraries
library(dplyr)
library(RColorBrewer)
library(ggplot2)
library(ggthemes)
library(grid)
library(gridExtra)
library(extrafont)

dat <- read.csv("http://macrofinance.nipfp.org.in/AirQuality.csv")

# Step 2) Calculating the average PM2.5 concentration by day and hour
dat.weekly <- dat %>%
    group_by(days, hour) %>%
    summarise(avgpm2 = mean(value, na.rm=TRUE))

dat.weekly$days <- factor(dat.weekly$days, levels=c("Sunday", "Monday", 
    "Tuesday", "Wednesday", "Thursday", "Friday", "Saturday"))
dat.weekly <- dat.weekly[order(dat.weekly$days), ]

# Step 3) Plotting Figure 1 of the paper
gg <- ggplot(dat.weekly, aes(x=hour, y=days, fill=avgpm2)) +
    geom_tile(color="white", size=0.04) + 
    scale_fill_gradientn(name="PM 2.5 Conc.",
                         colours=brewer.pal(9, "Greys")) +
    coord_equal() +
    labs(x="Hours", y=NULL) +
    scale_x_discrete(limits=0:23) +
    theme(plot.margin=grid::unit(c(0,0,0,0), "mm"))+
    theme_tufte(base_family="Helvetica") +
    theme(axis.ticks=element_blank(),
          text=element_text(size=8, family="serif")) +
    theme(axis.text=element_text(size=8)) +
    theme(legend.title=element_text(size=10)) +
    theme(legend.text=element_text(size=10))

The above code replicates the Figure 1 from the paper.

Insert Image Here