epi_clean_replace_value: Replace values with string in a column

In AntonioJBT/episcout: Quickly Clean, Explore and Visualise Large Epidemiological Datasets

Replace values with string in a column

Description

Uses stringr to match string pattern provided and replace value in column with string provided. Useful for partial matching for dates and replacing with NA for example. Uses stringr::str_detect().

Usage

epi_clean_replace_value(df = NULL, col_id = "", pattern = "", replace_str = NA)

Arguments

df	data frame object with string values in column to match and replace
col_id	Column ID passed as vector, can be index or column name
pattern	String pattern to look for (passed to str_detect pattern parameter)
replace_str	String that will replace value if pattern matches in the column passed

Value

The column passed as a vector

Author(s)

Antonio Berlanga-Taylor <\url{https://github.com/AntonioJBT/episcout}>

See Also

epi_clean_add_rep_num, epi_clean_add_colname_suffix, str_detect.

Examples

## Not run: 
df_factor <- df <- data.frame(
var_id = rep(1:(n / 2), each = 2),
var_to_rep = rep(c('Pre', 'Post'), n / 2),
x = rnorm(n),
y = rbinom(n, 1, 0.50),
z = rpois(n, 2)
)
df_factor$date_col <- seq(as.Date("2018/1/1"), by = "year", length.out = 5)
# Convert to character first:
df_factor$date_col <- as.character(df_factor$date_col)
lapply(df_factor, class)
patterns <- c('2018', '2022')
# match values starting with string
pattern <- pattern <- sprintf('^%s', patterns[1])
epi_clean_replace_value(df_factor, 'date_col', pattern, NA)
df_factor$date_col
# In a loop:
for (i in seq_along(df_factor)) {
  for (p in patterns) {
    # match values starting with string:
    pattern <- sprintf('^%s', p)
    df_factor[[i]] <- epi_clean_replace_value(df_factor, i, pattern, NA)
  }
}
df_factor$date_col

## End(Not run)

AntonioJBT/episcout documentation built on June 8, 2024, 7:47 a.m.