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Fix up date columns in R
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df_messy_dates <- tribble( | |
~col1_dt, ~col2_dt, ~other_data, | |
"2019-01-01", "2019-01-02", "a", | |
"2019-01-03", "1/4/2019", "b", | |
"01/05/2019", "2019-01-06", "c" | |
) | |
# A tibble: 3 x 3 | |
# col1_dt col2_dt other_data | |
# <chr> <chr> <chr> | |
# 1 2019-01-01 2019-01-02 a | |
# 2 2019-01-03 1/4/2019 b | |
# 3 01/05/2019 2019-01-06 c | |
fn_date_fixer <- function(col) { | |
output <- c() | |
for(cell in col) { | |
if(is.na(cell) || cell == "") { | |
# "" will cause `lubridate` to fail, so replace with NA | |
output <- c(output, NA) | |
} | |
else if(typeof(cell) == "character") { | |
parsed <- readr::parse_date(cell, format="%Y-%m-%d") | |
if(is.na(parsed)) { | |
parsed <- readr::parse_date(cell, format="%m/%d/%Y") | |
} | |
if(is.na(parsed)) { | |
stop(str_interp("Could not parse ${cell}")) | |
} | |
output <- c(output, parsed) | |
} | |
else { | |
output <- c(output, cell) | |
} | |
} | |
return(lubridate::as_date(output)) | |
} | |
df_clean_dates <- df_messy_dates %>% | |
mutate_at( | |
vars(ends_with("_dt")), | |
list( | |
~ fn_date_fixer(.) | |
) | |
) | |
df_clean_dates | |
# A tibble: 3 x 3 | |
# col1_dt col2_dt other_data | |
# <date> <date> <chr> | |
# 1 2019-01-01 2019-01-02 a | |
# 2 2019-01-03 2019-04-01 b | |
# 3 2019-05-01 2019-01-06 c |
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