Graph to visualize mean group wise and pareto chart in R language - r

Question

I have a dataset which has regions of a country, states and sales in that state. I want to visualize the mean of that dataset region wise and also a pareto chart to know which state contributes more to the overall regional sales. How to do this in R language. Please help as I'm new to R
#dput for dataset
Region <- c('South','South','South','South','South','Central','Central','Central','North','North','North','North','East','East','East','East','West','West','West','West')
State <- c('TAMIL NADU', 'TELANGANA,'ANDHRA PRADESH','KARNATAKA,'KERALA','MADHYA PRADESH','ORISSA','CHATTISGARH','DELHI','UTTARAKHAND','HARYANA','PUNJAB','ASSAM','MIZORAM','WB','BIHAR','GUJARAT','RAJASTHAN','MAHARASHTRA','GOA')
sales <- C(89,109,92,56,43,103,26,41,126,56,64,98,26,16,61,40,61,101,191,38)
The dataset somewhat looks like this
Region
State
Gdp
South
Tamil Nadu
89
South
Telangana
109
South
Karnataka
92
South
Andhra Pradesh
56
South
Kerala
43
Central
Madhya Pradesh
103
Central
Chattisgarh
26
Central
Orissa
41
North
Delhi
126
North
Punjab
56
North
Haryana
64
North
Uttarakhand
98
East
Assam
26
East
Mizoram
16
East
West Bengal
61
East
Bihar
40
West
Gujarat
61
West
Rajasthan
101
West
Maharashtra
191
West
Goa
38

Answer 1

You did not provide a desired output, so here is my guess at it..
library(data.table)
library(ggplot2)
# setDT(DT) #not needed if your data is already in data.table format
# Order decreasing Gdp
setorder(DT, -Gdp)
# Data wrangling
DT[, `:=`(meanGdp_region = mean(Gdp),
cumGdp = cumsum(Gdp)), by = Region]
DT[, State_f := factor(State, levels = State)]
# Plot
ggplot(data = DT, aes(x = State_f)) +
geom_col(aes(y = Gdp)) +
geom_line(aes(y = cumGdp, group = 1), color = "red") +
geom_hline(aes(yintercept = meanGdp_region), color = "blue") +
facet_wrap(~Region, nrow = 1, scales = "free_x") +
theme(axis.text.x = element_text(angle = 90, vjust = 0.5, hjust = 1)) +
labs(x = "")
sample data used
# Sample data
DT <- fread("Region State Gdp
South Tamil Nadu 89
South Telangana 109
South Karnataka 92
South Andhra Pradesh 56
South Kerala 43
Central Madhya Pradesh 103
Central Chattisgarh 26
Central Orissa 41
North Delhi 126
North Punjab 56
North Haryana 64
North Uttarakhand 98
East Assam 26
East Mizoram 16
East West Bengal 61
East Bihar 40
West Gujarat 61
West Rajasthan 101
West Maharashtra 191
West Goa 38")

Answer 2

Another output guess:
Region <- c('South','South','South','South','South','Central','Central','Central','North','North','North','North','East','East','East','East','West','West','West','West')
State <- c('TAMIL NADU', 'TELANGANA','ANDHRA PRADESH','KARNATAKA','KERALA','MADHYA PRADESH','ORISSA','CHATTISGARH','DELHI','UTTARAKHAND','HARYANA','PUNJAB','ASSAM','MIZORAM','WB','BIHAR','GUJARAT','RAJASTHAN','MAHARASHTRA','GOA')
sales <- c(89,109,92,56,43,103,26,41,126,56,64,98,26,16,61,40,61,101,191,38)
df <- data.frame(Region, State, sales)
df2 <- df %>%
arrange(desc(sales)) %>%
mutate(State = factor(State)) %>%
mutate(cumulative = cumsum(sales)) %>%
mutate(State = fct_inorder(df$State))
ggplot(df2, aes(x=State)) +
geom_bar(aes(y=sales), fill='blue', stat="identity") +
geom_point(aes(y=cumulative), color = rgb(0, 1, 0), pch=16, size=1) +
geom_path(aes(y=cumulative, group=1), colour="slateblue1", lty=3, size=0.9) +
theme(axis.text.x = element_text(angle=90, vjust=0.6)) +
labs(title = "Pareto Plot", x = 'State', y = 'Count')

Answer 3

it's great that you want to explore R. I found few mistakes, these vectors will not work, you forgot to put ' in few places and you should use c instead of C (in the code I grouped by colour States in diff. way compared to previous answer - hope you can choose what works for you).
library(ggplot2)
Region <- c('South','South','South','South','South','Central','Central','Central','North','North','North','North','East','East','East','East','West','West','West','West')
State <- c('TAMIL NADU', 'TELANGANA','ANDHRA PRADESH','KARNATAKA','KERALA','MADHYA PRADESH','ORISSA','CHATTISGARH','DELHI','UTTARAKHAND','HARYANA','PUNJAB','ASSAM','MIZORAM','WB','BIHAR','GUJARAT','RAJASTHAN','MAHARASHTRA','GOA')
sales <- c(89,109,92,56,43,103,26,41,126,56,64,98,26,16,61,40,61,101,191,38)
myDf <- data.frame(Region, State, sales, stringsAsFactors = FALSE)
str(myDf)
myDf <- myDf\[order(myDf$sales, decreasing=TRUE), \]
myDf$State <- factor(myDf$State , levels=myDf$State)
myDf$cumulative <- cumsum(myDf$sales)
ggplot(myDf, aes(x = State)) +
geom_bar(aes(y = sales, fill = Region), stat = "identity") +
geom_point(aes(y = cumulative), color = rgb(0, 1, 0), pch = 16, size = 1) +
geom_path(aes(y = cumulative, group = 1), colour = "slateblue1", lty = 3, size = 0.9) +
theme(axis.text.x = element_text(angle = 90, vjust = 0.6)) +
labs(title = "Pareto Plot", x = 'States', y = 'Sales')]