#Banking Statistics of Nepal in pictures
#Written by Rohan Byanjankar
#Visit my blog: https://www.rohanbyanjankar.com.np/


#Importing libraries
library(readxl)
library(ggplot2)
library(ggthemes)
library(ggrepel)


#Retriving working directory
getwd()
#Setting working directory
setwd("D:/~Drive Share (Rohan)/01 Shared Access/Banking and Finance")
#Importing excel data
data <- read_excel("deposit and loan.xlsx")
data$deposit_karba=data$deposit/100000
#Attaching data to database
attach(data)
ln_deposit <- log(per_deposit)
ln_loan <- log(per_loan)
#District-wise per capita Deposit and Loan in 2019/20
p <- ggplot(data,aes(x=ln_deposit,y=ln_loan,label= District , color=Province,size=per_deposit/100000))+
  geom_point()+
  geom_text_repel(nudge_x = 0.4,size=6.5)+
  geom_abline(lty=4,color="black")+
  ggtitle("District-wise per capita Deposit and Loan in 2019/20")+
  xlab("Logged per capita deposit")+
  ylab("Logged per capita loan")+
  labs(caption = "Source: Nepal Rastra Bank (2020)", size=12)+
  theme_economist()+
  scale_size_continuous(name = "Rs. in Lakhs")
p+theme(
  plot.title = element_text(size=22,color="dark blue"),
  plot.caption = element_text(size=12.5,color="dark grey",hjust = 0,face = "italic"),
  axis.text = element_text(size=12),
  axis.title = element_text(size=15),
  legend.title = element_text(size=18),
  legend.text = element_text(size=16)
)


ln_depositt <- log(deposit)
ln_loant <- log(loan)


#District-wise Total Deposit and Loan in 2019/20
p1 <- ggplot(data,aes(x=ln_depositt,y=ln_loant,label= District , color=Province,size=deposit_karba))+
  geom_point()+
  geom_text_repel(nudge_x = 0.8,size=5.5)+
  geom_abline(lty=4,color="black")+
  ggtitle("District-wise Total Deposit and Loan in 2019/20")+
  xlab("Logged total deposit")+
  ylab("Logged total loan")+
  labs(caption = "Source: Nepal Rastra Bank (2020)", size=12)+
  scale_size_continuous(name = "Rs. in Kharba")+
  theme_economist()+
  theme(
    plot.title = element_text(size=22,color="dark blue"),
    plot.caption = element_text(size=12.5,color="dark grey",hjust = 0,face = "italic" ),
    axis.text = element_text(size=12),
    axis.title = element_text(size=15),
    legend.title = element_text(size=18),
    legend.text = element_text(size=16)
  )
p1


#District-wise number of branch and ATM in 2019/20
p2 <- ggplot(data,aes(x=log(branch),y=log(atm),label= District , color=Province,size=atm))+
  geom_point()+
  geom_text_repel(nudge_x = 0.8,size=5.5)+
  geom_abline(lty=4,color="black")+
  ggtitle("District-wise number of branch and ATM in 2019/20")+
  xlab("Total branches in log scale")+
  ylab("Total ATMs in log scale")+
  labs(caption = "Source: Nepal Rastra Bank (2020)", size=12)+
  scale_size_continuous(name = "Numbers")+
  theme_economist()+
  theme(
    plot.title = element_text(size=22,color="dark blue"),
    plot.caption = element_text(size=12.5,color="dark grey",hjust = 0,face = "italic" ),
    axis.text = element_text(size=12),
    axis.title = element_text(size=15),
    legend.title = element_text(size=18),
    legend.text = element_text(size=16)
  )
p2


#District-wise Financial Access Index in 2019/20
p3 <- ggplot(data,aes(x=District,y=fai,label= fai_label ,color=Province,size=fai))+
  geom_point()+
  geom_text_repel(nudge_x = 4,size=5)+
  geom_abline(lty=4,color="black")+
  ggtitle("District-wise Financial Access Index in 2019/20")+
  xlab("")+
  ylab("Financial Access Index")+
  labs(caption = "Source: Nepal Rastra Bank (2020)", size=12)+
  scale_size_continuous(name = "Index")+
  theme_economist()+
  theme(
    plot.title = element_text(size=22,color="dark blue"),
    plot.caption = element_text(size=12.5,color="dark grey",hjust = 0,face = "italic" ),
    axis.text = element_text(size=12),
    axis.text.x = element_text(size=0),
    axis.title = element_text(size=15),
    legend.title = element_text(size=18),
    legend.text = element_text(size=16)
  )
p3


#District-wise Total deposit and Financial Access Index in 2019/20
p4 <- ggplot(data,aes(x=ln_depositt,y=fai,label= District ,color=Province,size=deposit_karba))+
  geom_point()+
  geom_text_repel(nudge_x = 1.5,size=4)+
  geom_abline(lty=4,color="black")+
  ggtitle("District-wise Total deposit and Financial Access Index in 2019/20")+
  xlab("Total deposit in log scale")+
  ylab("Financial Access Index")+
  labs(caption = "Source: Nepal Rastra Bank (2020)", size=12)+
  scale_size_continuous(name = "Deposit in Rs. Kharba")+
  theme_economist()+
  theme(
    plot.title = element_text(size=22,color="dark blue"),
    plot.caption = element_text(size=12.5,color="dark grey",hjust = 0,face = "italic" ),
    axis.text = element_text(size=12),
    axis.text.x = element_text(size=12),
    axis.title = element_text(size=15),
    legend.title = element_text(size=18),
    legend.text = element_text(size=16)
  )
p4


#Box plot of per-capita deposit by Province
p5 <- ggplot(data,aes(x=Province,y=log(per_deposit),fill=Province,size=deposit_karba))+
  geom_boxplot(outlier.colour = "red",outlier.shape = 7,outlier.size = 5)+
  stat_boxplot(geom = "errorbar")+
  ggtitle("Per-capita Deposit by Province")+
  ylab("Per capita deposit in log scale")+
  xlab("Province")+
  theme_economist()+
  theme(
    plot.title = element_text(size=22,color="dark blue"),
    plot.caption = element_text(size=12.5,color="dark grey",hjust = 0,face = "italic" ),
    axis.text = element_text(size=12),
    axis.text.x = element_text(size=12),
    axis.title = element_text(size=15),
    legend.title = element_text(size=18),
    legend.text = element_text(size=16)
  )
p5


#Box plot of per-capita deposit by Province
p6 <- ggplot(data,aes(x=Province,y=log(per_deposit),fill=Province,size=deposit_karba))+
  geom_boxplot(outlier.colour = "red",outlier.shape = 7,outlier.size = 5)+
  stat_boxplot(geom = "errorbar")+
  ggtitle("Per-capita Deposit by Province")+
  ylab("Per capita deposit in log scale")+
  xlab("Province")+
  labs(caption = "Source: Nepal Rastra Bank (2020)")+
  theme_economist()+
  theme(
    plot.title = element_text(size=22,color="dark blue"),
    plot.caption = element_text(size=12.5,color="dark grey",hjust = 0,face = "italic" ),
    axis.text = element_text(size=12),
    axis.text.x = element_text(size=12),
    axis.title = element_text(size=15),
    legend.title = element_text(size=18),
    legend.text = element_text(size=16)
  )
p6


#Box plot of per-capita loan by Province
p7 <- ggplot(data,aes(x=Province,y=log(per_loan),fill=Province,size=deposit_karba))+
  geom_boxplot(outlier.colour = "red",outlier.shape = 7,outlier.size = 5)+
  stat_boxplot(geom = "errorbar")+
  ggtitle("Per-capita Loan by Province")+
  ylab("Per capita loan in log scale")+
  xlab("Province")+
  labs(caption = "Source: Nepal Rastra Bank (2020)")+
  theme_economist()+
  theme(
    plot.title = element_text(size=22,color="dark blue"),
    plot.caption = element_text(size=12.5,color="dark grey",hjust = 0,face = "italic" ),
    axis.text = element_text(size=12),
    axis.text.x = element_text(size=12),
    axis.title = element_text(size=15),
    legend.title = element_text(size=18),
    legend.text = element_text(size=16)
  )
p7


#Box plot of FAI by Province
p8 <- ggplot(data,aes(x=Province,y=fai,fill=Province,label=District))+
  geom_boxplot(outlier.colour = "red",outlier.shape = 7,outlier.size = 5)+
  stat_boxplot(geom = "errorbar")+
  ggtitle("Financial Access Index by Province")+
  ylab("Financial Access Index")+
  xlab("Province")+
  labs(caption = "Source: Nepal Rastra Bank (2020)")+
  theme_economist()+
  theme(
    plot.title = element_text(size=22,color="dark blue"),
    plot.caption = element_text(size=12.5,color="dark grey",hjust = 0,face = "italic" ),
    axis.text = element_text(size=12),
    axis.text.x = element_text(size=12),
    axis.title = element_text(size=15),
    legend.title = element_text(size=18),
    legend.text = element_text(size=16)
  )
p8