R Notebook

setwd("~/R training")

data visualization with no coding

#install liabraries

library(gganimate)       
library(ggstatsplot)     
library(patchwork)     
library(plotly)        
library(gifski)        
library(GWalkR)        
library(esquisse)
library(rio)

``

# import the  data

gss=read.csv("GSSsubset.csv")
head(gss)

data visualization using esquisse

library(esquisse)
#esquisser(gss)
library(ggplot2)

p1=ggplot(gss) +
 aes(x = age, y = income) +
 geom_point(colour = "#1680E7") +
 labs(x = "age", y = "income", 
 title = "scatter plot", caption = "source:naomi 2025") +
 theme_bw()

#loaad library

library(esquisse)
#esquisser(gss)
library(ggplot2)

p2=ggplot(gss) +
 aes(x = degree, fill = degree) +
 geom_bar() +
 scale_fill_hue(direction = 1) +
 labs(x = "number of respondents", 
 y = "education level", title = "bar chat", caption = "source:naomi 2025") +
 theme_classic() +
 theme(axis.text.x = element_text(size = 14L))

library(esquisse)

library(ggplot2)

ggplot(gss) +
 aes(x = weight, y = height) +
 geom_point(colour = "#1DB81D") +
 labs(x = "height", y = "weight", 
 title = "bar chat", caption = "source:Naomi") +
 ggthemes::theme_economist() +
 theme(legend.text = element_text(face = "bold", 
 size = 14L), legend.title = element_text(face = "bold", size = 14L))


#esquisser(gss)

library(esquisse)

library(ggplot2)

ggplot(gss) +
 aes(x = sex, y = income) +
 geom_col(fill = "#112446") +
 geom_boxplot(aes(x = sex, y = income), 
 fill = "#112446") +
 labs(x = "sex", y = "income", title = "box plot", caption = "source: Naomi,2025") +
 theme_dark() +
 theme(legend.text = element_text(face = "bold"), legend.title = element_text(face = "bold"))
#esquisser(gss)
library(ggplot2)

height vs weight

#library(GWalkR)
#gwalkr(gss)

library(patchwork)

combine = (p1|p2)+
  plot_annotation(title="combined plots")
print(combine)