The data frame is a key data structure in statistics and in R.The dplyr package is designed to explore the functionality of Data frames.One important contribution of the dplyr package is that it provides a “grammar” (in particular, verbs) for data manipulation and for operating on data frames.
dplyr Grammar
Some of the key “verbs” provided by the dplyr package are
• select: return a subset of the columns of a data frame, using a flexible notation
• filter: extract a subset of rows from a data frame based on logical conditions
• arrange: reorder rows of a data frame
• rename: rename variables in a data frame
• mutate: add new variables/columns or transform existing variables
• summarise / summarize: generate summary statistics of different variables in the data frame,
possibly within strata
• %>%: the “pipe” operator is used to connect multiple verb actions together into a pipeline
to Install package
> install.packages("dplyr")
After installing the package it is important that you load it into your R session with the library()
function.
> library(dplyr)
dplyr Grammar
Some of the key “verbs” provided by the dplyr package are
• select: return a subset of the columns of a data frame, using a flexible notation
• filter: extract a subset of rows from a data frame based on logical conditions
• arrange: reorder rows of a data frame
• rename: rename variables in a data frame
• mutate: add new variables/columns or transform existing variables
• summarise / summarize: generate summary statistics of different variables in the data frame,
possibly within strata
• %>%: the “pipe” operator is used to connect multiple verb actions together into a pipeline
to Install package
> install.packages("dplyr")
After installing the package it is important that you load it into your R session with the library()
function.
> library(dplyr)
