Loading the data and customizing the csv calls.
library(readr)
example_data_bad <- read_delim("https://raw.githubusercontent.com/ati-ozgur/course-r-programming/master/2021/Lab-2021-11-16-ImportData/example-data-bad.csv", delim = "\t",
col_types = cols(study_id = col_integer(),
patient_id = col_integer(), gender = col_factor(levels = c("F",
"M")), age_years = col_integer(),
age_months = col_integer(), x = col_skip()),
trim_ws = TRUE)## Warning: One or more parsing issues, see `problems()` for detailshead(example_data_bad)## # A tibble: 6 x 6
## study_id patient_id gender age_years age_months date_inclusion
## <int> <int> <fct> <int> <int> <date>
## 1 NA 4 F 2 27 2011-01-01
## 2 1 NA F 2 25 2011-01-01
## 3 1 1 <NA> 2 27 2011-01-01
## 4 1 2 M NA 61 2011-01-01
## 5 1 3 F 9 NA 2011-01-01
## 6 1 3 M 1 17 2011-01-01tibble::as_tibble(example_data_bad)## # A tibble: 12 x 6
## study_id patient_id gender age_years age_months date_inclusion
## <int> <int> <fct> <int> <int> <date>
## 1 NA 4 F 2 27 2011-01-01
## 2 1 NA F 2 25 2011-01-01
## 3 1 1 <NA> 2 27 2011-01-01
## 4 1 2 M NA 61 2011-01-01
## 5 1 3 F 9 NA 2011-01-01
## 6 1 3 M 1 17 2011-01-01
## 7 1 4 M 2 25 2011-01-01
## 8 2 1 M 200 32 2011-01-01
## 9 2 2 M 3 24 2011-01-01
## 10 2 3 F 7 90 2011-01-01
## 11 2 4 F 1 14 2011-01-01
## 12 2 5 F 2 25 NA