How to Import, Manipulate & Visualize Data Using the tidyverse in R | readr, dplyr & ggplot2 Package

This video demonstrates how to import, manipulate, and visualize data using the tidyverse in the R programming language. The video is part of a teaser series for the Statistics Globe online course on "Data Manipulation in R Using dplyr & the tidyverse". More info: statisticsglobe.com/online-co...
Attribution: The data used in this video is taken from here www.kaggle.com/datasets/divya...
R code of this video:
install.packages("tidyverse") # Install tidyverse packages
library("tidyverse") # Load tidyverse packages
my_path ＜- "D:/Dropbox/Jock/Data Sets/" # Specify directory path
tib_dest ＜- read_csv(str_c(my_path, # Import CSV file
"Most_Visited_Destination_in_2018_and_2019.csv"))
tib_dest # Print tibble
tib_dest %＞% # Class of data set
class()
tib_dest %＞% # Show entire data set
View()
tib_dest_new ＜- tib_dest %＞% # Rename column
rename(T2019 = `International tourist arrivals (2019)`)
tib_dest_new # Print updated tibble
tib_dest_new2 ＜- tib_dest_new %＞% # Remove certain columns
select(- ...1, - `International tourist arrivals (2018)`)
tib_dest_new2 # Print updated tibble
tib_dest_new3 ＜- tib_dest_new2 %＞% # Replace values
mutate(across(everything(), ~ replace(., . == "-", NA)),
T2019 = as.numeric(str_replace(T2019, " million", "")) * 1e6)
tib_dest_new3 # Print updated tibble
tib_dest_new4 ＜- tib_dest_new3 %＞% # Remove NA rows
na.omit()
tib_dest_new4 # Print updated tibble
tib_dest_new5 ＜- tib_dest_new4 %＞% # Remove duplicate row
filter(Destination != "Egypt" | Region == "Africa")
tib_dest_new5 # Print updated tibble
my_ggp ＜- tib_dest_new5 %＞% # Create ggplot2 plot
mutate(Destination = reorder(Destination, - T2019)) %＞%
ggplot(aes(x = Destination,
y = T2019,
fill = Region)) +
geom_col() +
theme(axis.text.x = element_text(angle = 90,
hjust = 1,
vjust = 0.5))
my_ggp # Draw ggplot2 plot
tib_dest %＞% # Do all at once
rename(T2019 = `International tourist arrivals (2019)`) %＞%
select(- ...1, - `International tourist arrivals (2018)`) %＞%
mutate(across(everything(), ~ replace(., . == "-", NA)),
T2019 = as.numeric(str_replace(T2019, " million", "")) * 1e6) %＞%
na.omit() %＞%
filter(Destination != "Egypt" | Region == "Africa") %＞%
mutate(Destination = reorder(Destination, - T2019)) %＞%
ggplot(aes(x = Destination,
y = T2019,
fill = Region)) +
geom_col() +
theme(axis.text.x = element_text(angle = 90,
hjust = 1,
vjust = 0.25))
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[@nedlin7934]

always can learn new useful things from this channel.

[@matthias.statisticsglobe]

Thank you so much, what a great feedback! We really appreciate that!

[@saimajahan1000]

Awesome as usual !!!!

[@StatisticsGlobe]

Thank you so much Saima, looking forward to the start of the course! :)

[@dedisetiawan3245]

thank, how to change the first column to the name of the school? Thanks for the answer.

[@cansustatisticsglobe]

Hello, Sorry I couldn't get you very well. There is no school information in the dataset. Could you please give some more details? Best, Cansu

[@mayankpatel9379]

Can you please tell me how to add features in r studio my data is full of website in need to find is it malicious or benign

[@cansustatisticsglobe]

Hello! I am not sure if I got your questions very well. Do you want to add new variables/features to the imported dataset? Best, Cansu