To calculate a mean or average in R, you can “use the mean() function.” For example, mean(c(1, 2, 3, 4)) function returns 2.5. Syntax mean(x, trim, na.rm) Parameters x: The x is a Numeric Vector. trim: It drops some observations from both ends of the sorted vector. na.rm: It is a boolean value to ignore the NA … Read more
Here are two ways to add/append an element to a list in R. Using append() function Using c() function Method 1: Use the append() method The main way to add or append an element to a list in R is to use the “append()” function. The append() function accepts three parameters input list, a string … Read more
Here are three ways to import CSV files into R: Using the read.csv() function from base R Using the read_csv() function from the readr package Using the fread() function from data.table package Method 1: Using the read.csv() function from base R The read_csv() function comes with base R, so no additional libraries are needed, and it … Read more
Here are three methods to export DataFrame to CSV in R: Using the write.csv() function from the base package Using the write_csv() function from readr package Using the fwrite() function from data.table package Method 1: Using write.csv() function To export data frame to csv in R, you can “use the write.csv() function.” The write.csv() function “writes … Read more
Here are two ways to import Excel files in R: Using read_excel() Using the built-in menu Options of Rstudio Let’s say we have an Excel file like this, and we will import this file in R. Method 1: Using read_excel() The easiest method for reading Excel files in R is using the readxl package’s “read_excel()” … Read more
The error: discrete value supplied to continuous scale typically occurs in R when you use “erroneous use of the scale function along with ggplot().“ library(ggplot2) df <- data.frame(x = 1:10, y = c(“bmw”, “audi”, “mercedez”, “ferrari”, “jaguar”)) ggplot(df, aes(x, y)) + geom_point() + scale_y_continuous(limits = c(0, 10)) Output Error: Discrete value supplied to continuous scale … Read more
The n_distinct() function in R is “used to count the number of unique/distinct combinations in a set of one or more vectors.” It’s a faster and more concise equivalent to the nrow(unique(data.frame(…))) function. Syntax n_distinct(…, na.rm = FALSE) Parameters …: Unnamed vectors. If multiple vectors are supplied, then they should have the same length. na.rm: … Read more
To Rank Variables by Group using dplyr in R, you can “combine arrange(), group_by(), or mutate() functions.” Syntax df %>% arrange(group_var, numeric_var) %>% group_by(group_var) %>% mutate(rank = rank(numeric_var)) Example 1: Rank in Ascending Order library(dplyr) df <- data.frame( Age = c(20, 21, 19, 22, 23, 20, 21), Gender = c(“Male”, “Female”, “Male”, “Female”, “Male”, “Female”, … Read more
To recode values using dplyr in R, you can “use the recode() function from the dplyr package.” The recode() function from the dplyr package is a handy tool to change or replace values in a column. Syntax df %>% mutate(column_name = recode(column_name, old_value1 = new_value1, old_value2 = new_value2, …)) Example 1: Recode a Single Column … Read more
To calculate relative frequencies using the dplyr package in R, you typically follow these steps: Count the number of occurrences of each value or group. Calculate the sum of all counts to get the total. Divide each count by the total to get the relative frequency. Example 1: Calculating the Relative Frequency of One Variable … Read more