DAA_11_Dplyr-Tidyr

A package with easy tools for the most common data manipulation tasks.

The package includes some commands named as verbs that coincide with the most common actions over data:

select(): subset columns.

filter(): subset rows on conditions.

mutate(): create new columns by using information from other columns.

group_by() and summarize(): create summary statisitcs on grouped data.

arrange(): order rows.

• ggplot2

• dplyr

• tidyr

• magrittr

A package with the functions to convert from long to wide format and viceversa: pivot_longer() and pivot_wider()

• ggplot2

• dplyr

• tidyr

• magrittr

The next code:

iris %>%

group_by(Species) %>%

summarise(Mean.Petal.Length = mean(Petal.Length))

• Is using the Tidyverse notation.

• Will create a vector with the species of iris.

• Do not need any library from R.

• Gives an error.

The next code:

iris %>%

group_by(Species) %>%

summarise(Mean.Petal.Length = mean(Petal.Length))

• Creates a matrix

• Will create a dataframe with three rows.

• Do not need any library from R.

• Gives an error.

The next code will give:

iris %>%

pivot_longer(-Species)

• A tibble dataframe with two columns.

• A tibble dataframe with three columns.

• A tibble dataframe with four columns.

• A tibble dataframe with five columns.