tbl_df

0th

Percentile

Create a data frame tbl.

Forwards the argument to as_data_frame, see tibble-package for more details.

Usage
tbl_df(data)
Arguments
data

a data frame

Aliases
  • tbl_df
Examples
library(dplyr) ds <- tbl_df(mtcars) ds as.data.frame(ds) if (require("Lahman") && packageVersion("Lahman") >= "3.0.1") { batting <- tbl_df(Batting) dim(batting) colnames(batting) head(batting) # Data manipulation verbs --------------------------------------------------- filter(batting, yearID > 2005, G > 130) select(batting, playerID:lgID) arrange(batting, playerID, desc(yearID)) summarise(batting, G = mean(G), n = n()) mutate(batting, rbi2 = if(is.null(AB)) 1.0 * R / AB else 0) # Group by operations ------------------------------------------------------- # To perform operations by group, create a grouped object with group_by players <- group_by(batting, playerID) head(group_size(players), 100) summarise(players, mean_g = mean(G), best_ab = max(AB)) best_year <- filter(players, AB == max(AB) | G == max(G)) progress <- mutate(players, cyear = yearID - min(yearID) + 1, rank(desc(AB)), cumsum(AB)) # When you group by multiple level, each summarise peels off one level per_year <- group_by(batting, playerID, yearID) stints <- summarise(per_year, stints = max(stint)) filter(stints, stints > 3) summarise(stints, max(stints)) mutate(stints, cumsum(stints)) # Joins --------------------------------------------------------------------- player_info <- select(tbl_df(Master), playerID, birthYear) hof <- select(filter(tbl_df(HallOfFame), inducted == "Y"), playerID, votedBy, category) # Match players and their hall of fame data inner_join(player_info, hof) # Keep all players, match hof data where available left_join(player_info, hof) # Find only players in hof semi_join(player_info, hof) # Find players not in hof anti_join(player_info, hof) }
Documentation reproduced from package dplyr, version 0.5.0, License: MIT + file LICENSE

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