Finds columns containing date and year data

This function takes a data frame as argument and returns the column names (or indices) of all columns containing dates and the most likely column containing year information, if any. It can be used to automate the search of date and year columns in data frames.

Usage

find_timecol(x, return_index = FALSE, allow_NA = TRUE, sample_size = 1000)

Arguments

x

A data frame object

return_index

A logical value indicating whether the function should return the index of time columns instead of the column names. Default is FALSE, column names are returned.

allow_NA

Logical value indicating whether to allow time columns to contain NA values. Default is allow_NA=FALSE, the function will not return time column containing NA values.

sample_size

Either NA or a numeric value indicating the sample size used for evaluating columns. Default is 1000. If NA is passed, the function will evaluate the full table. The minimum accepted value is 100 (i.e. 100 randomly sampled rows are used to evaluate the columns). This parameter can be tuned to speed up computation on long datasets. Taking a sample could result in inexact identification of key columns, accuracy improves with larger samples.

Value

Returns a vector of names (return_index=FALSE) or indices (return_index=TRUE) of columns containing date or year information. Only the most likely year column is returned.

See also

is_date, find_countrycol

Examples

find_timecol(x=data.frame(a=1970:2020, year=1970:2020, b=rep("2020-01-01",51),c=sample(1:1000,51)))
#> [1] "year" "b"