How to import, combine, summarize, and visualize two data sets in the R programming language. More details: https://statisticsglobe.com/read-row-bind-summarize-visualize-multiple-data-sets-r
The video analyzes group participants of the "Data Manipulation in R Using dplyr & the tidyverse" online course. More details here: https://statisticsglobe.com/online-course-data-manipulation-r-dplyr-tidyverse
R code of this video:
install.packages("tidyverse") # Install & load tidyverse package
library("tidyverse")
my_path ＜- "C:/Users/Joach/Desktop/my project/" # Specify working directory
data1 ＜- read_csv(str_c(my_path, "data1.csv")) # Import first data set
data1 # Print first data set
data2 ＜- read_csv(str_c(my_path, "data2.csv")) # Import second data set
data2 # Print second data set
data1_upd ＜- data1 %＞% # Filter rows
filter(! ID %in% c("ID5", "ID13", "ID55"))
data1_upd
data_all ＜- data1_upd %＞% # Row-bind multiple data sets
bind_rows(data2)
head(data_all) # Head of combined data
tail(data_all) # Tail of combined data
nrow(data_all) # Total number of participants
data_summ ＜- data_all %＞% # Convert vector to tibble
group_by(country) %＞% # Group tibble
summarize(country_count = n()) %＞% # Calculate country count
arrange(desc(country_count)) # Arrange tibble descendingly
data_summ # Print country data
data_summ %＞% # Create ggplot2 plot
ggplot(aes(x = reorder(country, - country_count),
y = country_count)) +
geom_col() + # Specify to draw a barplot
theme(axis.text.x = element_text(angle = 90, # Vertical x-axis labels
hjust = 1,
vjust = 0.3)) +
xlab("Country") + # Change x-axis label
ylab("Count") + # Change y-axis label
annotate("text", # Add text element to plot
x = 15,
y = 25,
label = "Course Participants\n by Country",
size = 15,
color = "#1b98e0")
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