utils_na_zero {metan}

Utilities for handling with NA and zero values

Description

NAs and zeros can increase the noise in multi-environment trial analysis. This collection of functions will make it easier to deal with them.

• fill_na(): Fills NA in selected columns using the next or previous entry.

• ⁠has_na(), has_zero()⁠: Check for NAs and ⁠0s⁠ in the data and return a logical value.

• prop_na() returns the proportion of NAs in each column of a data frame.

• random_na(): Generate random NA values in a two-way table based on a desired proportion.

• remove_cols_na(), remove_rows_na(): Remove columns and rows that contains at least one NA value.

• remove_cols_all_na(), remove_rows_all_na(): Remove columns and rows where all values are NAs.

• remove_cols_zero(), remove_rows_zero(): Remove columns and rows that contains at least one 0 value, respectively.

• ⁠select_cols_na(), select_cols_zero()⁠: Select columns with NAs and ⁠0s⁠, respectively.

• ⁠select_rows_na(), select_rows_zero()⁠: Select rows with NAs and ⁠0s⁠, respectively.

• ⁠replace_na(), replace_zero()⁠: Replace NAs and ⁠0s⁠, respectively, with a replacement value.

Usage

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

has_na(.data)

prop_na(.data, ...)

remove_rows_na(.data, verbose = TRUE)

remove_rows_all_na(.data, verbose = TRUE)

remove_cols_na(.data, verbose = TRUE)

remove_cols_all_na(.data, verbose = TRUE)

select_cols_na(.data, verbose = TRUE)

select_rows_na(.data, verbose = TRUE)

replace_na(.data, ..., replacement = 0)

random_na(.data, prop)

has_zero(.data)

remove_rows_zero(.data, verbose = TRUE)

remove_cols_zero(.data, verbose = TRUE)

select_cols_zero(.data, verbose = TRUE)

select_rows_zero(.data, verbose = TRUE)

replace_zero(.data, ..., replacement = NA)

Arguments

.data

A data frame.

...

Variables to fill NAs in fill_na(), replace NAs in replace_na() or zeros in replace_zero(). If ... is null then all variables in .data will be evaluated. It must be a single variable name or a comma-separated list of unquoted variables names. Select helpers are also allowed.

direction

Direction in which to fill missing values. Currently either "down" (the default), "up", "downup" (i.e. first down and then up) or "updown" (first up and then down).

verbose

Logical argument. If TRUE (default) shows in console the rows or columns deleted.

replacement

The value used for replacement. Defaults to 0. Other possible values are Use "colmean", "colmin", and "colmax" to replace missing values with column mean, minimum and maximum values, respectively.

prop

The proportion (percentage) of NA values to generate in .data.

Value

A data frame with rows or columns with NA values deleted.

Author(s)

Tiago Olivoto [e-mail]

Examples

library(metan)
data_naz <- iris %>%
              group_by(Species) %>%
              doo(~head(., n = 3)) %>%
              as_character(Species)
data_naz
data_naz[c(2:3, 6, 8), c(1:2, 4, 5)] <- NA
data_naz[c(2, 7, 9), c(2, 3, 4)] <- 0
has_na(data_naz)
has_zero(data_naz)

# Fill NA values of column GEN
fill_na(data_naz, Species)

# Remove columns
remove_cols_na(data_naz)
remove_cols_zero(data_naz)
remove_rows_na(data_naz)
remove_rows_zero(data_naz)

# Select columns
select_cols_na(data_naz)
select_cols_zero(data_naz)
select_rows_na(data_naz)
select_rows_zero(data_naz)

# Replace values
replace_na(data_naz)
replace_zero(data_naz)