tidyfst: missing – R documentation

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missing

Dump, replace and fill missing values in data.frame

Description

A set of tools to deal with missing values in data.frames. It can dump, replace, fill (with next or previous observation) or delete entries according to their missing values.

Usage

drop_na_dt(.data, ...)

replace_na_dt(.data, ..., to)

delete_na_cols(.data, prop = NULL, n = NULL)

delete_na_rows(.data, prop = NULL, n = NULL)

fill_na_dt(.data, ..., direction = "down")

shift_fill(x, direction = "down")

Arguments

`.data`	data.frame
`...`	Colunms to be replaced or filled. If not specified, use all columns.
`to`	What value should NA replace by?
`prop`	If proportion of NAs is larger than or equal to "prop", would be deleted.
`n`	If number of NAs is larger than or equal to "n", would be deleted.
`direction`	Direction in which to fill missing values. Currently either "down" (the default) or "up".
`x`	A vector with missing values to be filled.

Details

drop_na_dt drops the entries with NAs in specific columns. fill_na_dt fill NAs with observations ahead ("down") or below ("up"), which is also known as last observation carried forward (LOCF) and next observation carried backward(NOCB).

delete_na_cols could drop the columns with NA proportion larger than or equal to "prop" or NA number larger than or equal to "n", delete_na_rows works alike but deals with rows.

shift_fill could fill a vector with missing values.

Value

data.table

References

https://stackoverflow.com/questions/23597140/how-to-find-the-percentage-of-nas-in-a-data-frame

https://stackoverflow.com/questions/2643939/remove-columns-from-dataframe-where-all-values-are-na

https://stackoverflow.com/questions/7235657/fastest-way-to-replace-nas-in-a-large-data-table

Examples

df <- data.table(x = c(1, 2, NA), y = c("a", NA, "b"))
 df %>% drop_na_dt()
 df %>% drop_na_dt(x)
 df %>% drop_na_dt(y)
 df %>% drop_na_dt(x,y)

 df %>% replace_na_dt(to = 0)
 df %>% replace_na_dt(x,to = 0)
 df %>% replace_na_dt(y,to = 0)
 df %>% replace_na_dt(x,y,to = 0)

 df %>% fill_na_dt(x)
 df %>% fill_na_dt() # not specified, fill all columns
 df %>% fill_na_dt(y,direction = "up")

x = data.frame(x = c(1, 2, NA, 3), y = c(NA, NA, 4, 5),z = rep(NA,4))
x
x %>% delete_na_cols()
x %>% delete_na_cols(prop = 0.75)
x %>% delete_na_cols(prop = 0.5)
x %>% delete_na_cols(prop = 0.24)
x %>% delete_na_cols(n = 2)

x %>% delete_na_rows(prop = 0.6)
x %>% delete_na_rows(n = 2)

# shift_fill
y = c("a",NA,"b",NA,"c")

shift_fill(y) # equals to
shift_fill(y,"down")

shift_fill(y,"up")

tidyfst

Tidy Verbs for Fast Data Manipulation

v0.9.9

MIT + file LICENSE

Authors

Tian-Yuan Huang [aut, cre] (<https://orcid.org/0000-0002-3591-4203>)

Initial release