inspect {metan} | R Documentation |
Check for common errors in multi-environment trial data
Description
inspect()
scans a data.frame
object for errors that may affect the use
of functions in metan
. By default, all variables are checked regarding
the class (numeric or factor), missing values, and presence of possible
outliers. The function will return a warning if the data looks like
unbalanced, has missing values or possible outliers.
Usage
inspect(.data, ..., plot = FALSE, threshold = 15, verbose = TRUE)
Arguments
.data |
The data to be analyzed |
... |
The variables in |
plot |
Create a plot to show the check? Defaults to |
threshold |
Maximum number of levels allowed in a character / factor column to produce a plot. Defaults to 15. |
verbose |
Logical argument. If |
Value
A tibble with the following variables:
-
Variable The name of variable
-
Class The class of the variable
-
Missing Contains missing values?
-
Levels The number of levels of a factor variable
-
Valid_n Number of valid n (omit NAs)
-
Outlier Contains possible outliers?
Author(s)
Tiago Olivoto tiagoolivoto@gmail.com
Examples
library(metan)
inspect(data_ge)
# Create a toy example with messy data
df <- data_ge2[-c(2, 30, 45, 134), c(1:5)] %>% as.data.frame()
df[c(1, 20, 50), 5] <- NA
df[40, 4] <- "2..814"
inspect(df)