maditr (version 0.6.3)

maditr: maditr: Pipe-Style Interface for 'data.table'

Description

Package provides pipe-style interface for data.table. It preserves all data.table features without significant impact on performance. 'let' and 'take' functions are simplified interfaces for most common data manipulation tasks.

• To select rows from data: take_if(mtcars, am==0)

• To select columns from data: take(mtcars, am, vs, mpg)

• To aggregate data: take(mtcars, mean_mpg = mean(mpg), by = am)

• To aggregate all non-grouping columns: take(mtcars, fun = mean, by = am)

• To aggregate several columns with one summary: take(mtcars, mpg, hp, fun = mean, by = am)

• To get total summary skip 'by' argument: take(mtcars, fun = mean)

• Use magrittr pipe '%>%' to chain several operations:

       mtcars %>%
          let(mpg_hp = mpg/hp) %>%
          take(mean(mpg_hp), by = am)
  

• To modify variables or add new variables:

        mtcars %>%
           let(new_var = 42,
               new_var2 = new_var*hp) %>%
            head()

• To drop variable assign NULL: let(mtcars, am = NULL) %>% head()

• For parametric assignment use ':=':

       new_var = "my_var"
       old_var = "mpg"
       mtcars %>%
           let((new_var) := get(old_var)*2) %>%
           head()

• For more sophisticated operations see 'query'/'query_if': these functions translates its arguments one-to-one to '[.data.table' method. Additionally there are some conveniences such as automatic 'data.frame' conversion to 'data.table'.

Examples

# NOT RUN {
# examples form 'dplyr' package
data(mtcars)

# Newly created variables are available immediately
mtcars %>%
    let(
        cyl2 = cyl * 2,
        cyl4 = cyl2 * 2
    ) %>% head()

# You can also use let() to remove variables and
# modify existing variables
mtcars %>%
    let(
        mpg = NULL,
        disp = disp * 0.0163871 # convert to litres
    ) %>% head()


# window functions are useful for grouped computations
mtcars %>%
    let(rank = rank(-mpg, ties.method = "min"),
        by = cyl) %>%
    head()

# You can drop variables by setting them to NULL
mtcars %>%
    let(cyl = NULL) %>%
    head()

# keeps all existing variables
mtcars %>%
    let(displ_l = disp / 61.0237) %>%
    head()

# keeps only the variables you create
mtcars %>%
    take(displ_l = disp / 61.0237)


# can refer to both contextual variables and variable names:
var = 100
mtcars %>%
    let(cyl = cyl * var) %>%
    head()

# filter by condition
mtcars %>%
    take_if(am==0)

# filter by compound condition
mtcars %>%
    take_if(am==0 & mpg>mean(mpg))


# A 'take' with summary functions applied without 'by' argument returns an aggregated data
mtcars %>%
    take(mean = mean(disp), n = .N)

# Usually, you'll want to group first
mtcars %>%
    take(mean = mean(disp), n = .N, by = am)

# grouping by multiple variables
mtcars %>%
    take(mean = mean(disp), n = .N, by = list(am, vs))

# parametric evaluation:
var = quote(mean(cyl))
take(mtcars, eval(var))


# You can group by expressions:
mtcars %>%
    take(
        fun = mean,
        by = list(vsam = vs + am)
    )

# }