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(v1.4.0.9044) mo tibble printing, mo_shortname() fix

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dr. M.S. (Matthijs) Berends
2020-12-24 23:29:10 +01:00
parent 128ebcfd62
commit df37584189
96 changed files with 1039 additions and 2847 deletions
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vignettes/MDR.Rmd
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@ -81,34 +81,27 @@ example_isolates %>%
For another example, I will create a data set to determine multi-drug resistant TB:
```{r}
# a helper function to get a random vector with values S, I and R
# with the probabilities 50% - 10% - 40%
sample_rsi <- function() {
sample(c("S", "I", "R"),
size = 5000,
prob = c(0.5, 0.1, 0.4),
replace = TRUE)
}
my_TB_data <- data.frame(rifampicin = sample_rsi(),
isoniazid = sample_rsi(),
gatifloxacin = sample_rsi(),
ethambutol = sample_rsi(),
pyrazinamide = sample_rsi(),
moxifloxacin = sample_rsi(),
kanamycin = sample_rsi())
# random_rsi() is a helper function to generate
# a random vector with values S, I and R
my_TB_data <- data.frame(rifampicin = random_rsi(5000),
isoniazid = random_rsi(5000),
gatifloxacin = random_rsi(5000),
ethambutol = random_rsi(5000),
pyrazinamide = random_rsi(5000),
moxifloxacin = random_rsi(5000),
kanamycin = random_rsi(5000))
```
Because all column names are automatically verified for valid drug names or codes, this would have worked exactly the same:
```{r, eval = FALSE}
my_TB_data <- data.frame(RIF = sample_rsi(),
INH = sample_rsi(),
GAT = sample_rsi(),
ETH = sample_rsi(),
PZA = sample_rsi(),
MFX = sample_rsi(),
KAN = sample_rsi())
my_TB_data <- data.frame(RIF = random_rsi(5000),
INH = random_rsi(5000),
GAT = random_rsi(5000),
ETH = random_rsi(5000),
PZA = random_rsi(5000),
MFX = random_rsi(5000),
KAN = random_rsi(5000))
```
The data set now looks like this: