Maybe the most important package for newbies: tidyverse

The tidyverse is a collection of popular R packages for data manipulation, visualization, and analysis. These packages include "dplyr" for data manipulation, "ggplot2" for visualization, and "tidyr" for tidying data. The tidyverse packages are designed to work together seamlessly, and they share a common set of functions and conventions for data manipulation.

One of the key features of the tidyverse is the use of the "pipe" operator, which is the "%>%|" symbol. The pipe operator allows you to chain together multiple functions, with the output of one function becoming the input of the next. This makes your code more readable and easier to write. For example, the following code uses the pipe operator to select certain rows of a data frame, then create a new column based on a calculation, and then create a histogram of the new column: Imagine something like "And then..."

mydata %>%

filter(x > 5) %>%

mutate(y = x + 1) %>%

ggplot(aes(y)) +

geom_histogram()

Another key feature of the tidyverse is the use of "verbs" for common data manipulation tasks. For example, the function filter() is used to select certain rows of a data frame, the function mutate() is used to create new columns in a data frame, and the function unite() is used to combine multiple columns into a single column. These functions make your code more readable and easier to understand. For example, the following code uses the filter() and mutate() functions to select certain rows and create a new column:

mydata %>%

filter(x > 5) %>%

mutate(y = x + 1)