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rlang dependency, new fungi

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dr. M.S. (Matthijs) Berends
2019-02-28 13:56:28 +01:00
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vignettes/AMR.Rmd
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@ -315,7 +315,7 @@ data_1st %>%
## Resistance percentages
The functions `portion_R`, `portion_RI`, `portion_I`, `portion_IS` and `portion_S` can be used to determine the portion of a specific antimicrobial outcome. They can be used on their own:
The functions `portion_R()`, `portion_RI()`, `portion_I()`, `portion_IS()` and `portion_S()` can be used to determine the portion of a specific antimicrobial outcome. They can be used on their own:
```{r}
data_1st %>% portion_IR(amox)
@ -351,21 +351,21 @@ data_1st %>%
knitr::kable(align = "c", big.mark = ",")
```
These functions can also be used to get the portion of multiple antibiotics, to calculate co-resistance very easily:
These functions can also be used to get the portion of multiple antibiotics, to calculate empiric susceptibility of combination therapies very easily:
```{r, eval = FALSE}
data_1st %>%
group_by(genus) %>%
summarise(amoxicillin = portion_S(amcl),
summarise(amoxiclav = portion_S(amcl),
gentamicin = portion_S(gent),
"amox + gent" = portion_S(amcl, gent))
amoxiclav_genta = portion_S(amcl, gent))
```
```{r, echo = FALSE}
data_1st %>%
group_by(genus) %>%
summarise(amoxicillin = portion_S(amcl),
summarise(amoxiclav = portion_S(amcl),
gentamicin = portion_S(gent),
"amox + gent" = portion_S(amcl, gent)) %>%
amoxiclav_genta = portion_S(amcl, gent)) %>%
knitr::kable(align = "c", big.mark = ",")
```
@ -374,9 +374,9 @@ To make a transition to the next part, let's see how this difference could be pl
```{r plot 1}
data_1st %>%
group_by(genus) %>%
summarise("1. Amoxicillin" = portion_S(amcl),
summarise("1. Amoxi/clav" = portion_S(amcl),
"2. Gentamicin" = portion_S(gent),
"3. Amox + gent" = portion_S(amcl, gent)) %>%
"3. Amoxi/clav + gent" = portion_S(amcl, gent)) %>%
tidyr::gather("Antibiotic", "S", -genus) %>%
ggplot(aes(x = genus,
y = S,
@ -397,9 +397,9 @@ ggplot(data = a_data_set,
x = "My X axis",
y = "My Y axis")
ggplot(a_data_set,
aes(year, value) +
geom_bar()
# or as short as:
ggplot(a_data_set) +
geom_bar(aes(year))
```
The `AMR` package contains functions to extend this `ggplot2` package, for example `geom_rsi()`. It automatically transforms data with `count_df()` or `portion_df()` and show results in stacked bars. Its simplest and shortest example: