How to make Shiny input $ var consumable for dplyr :: summary ()
I have the following Rmarkdown Shiny :
---
title: "My Title"
runtime: shiny
output:
flexdashboard::flex_dashboard:
vertical_layout: scroll
theme: bootstrap
orientation: rows
---
```{r setup, include=FALSE}
library(flexdashboard)
```
Rows {data-height=700}
-----------------------------------------------------------------------
### Mate-pair Mapping Distribution
```{r mate_pair_distribution, echo=FALSE}
library(ggplot2)
library(tidyverse)
sidebarPanel(
selectInput("col_id", label = "Features",
choices = c("carat", "depth","price"), selected = "price"),
selectInput("op_id", label = "Quality:",
choices = c("All", "Ideal","Premium","Good","Very Good"), selected = "Good"),
sliderInput("n_breaks", label = "Number of bins:",
min = 20, max = 50, value = 30, step = 1)
)
#renderText(input$op_id)
mainPanel(
renderPlot({
# Prepare for the data
dat <- diamonds %>% filter(cut == input$op_id)
if(input$op_id == "All") {
dat <- diamonds
}
# Plotting
ggplot(dat, aes(dat %>% select(.,contains(input$col_id)))) +
ggtitle(input$op_id, subtitle = input$col_id) +
geom_histogram(bins = input$n_breaks) +
scale_x_continuous() +
xlab(input$col_id) +
theme_light()
}, height=400, width=400),
br(),
br(),
renderPrint({
dat <- diamonds %>% filter(cut == input$op_id)
if(input$op_id == "All") {
dat <- diamonds
}
dat %>%
select(.,contains(input$col_id)) %>%
summarise(mean = mean(input$col_id), sd=sd(input$col_id), n=n())
})
)
```
That produce this conclusion
As you can see renderText()
show NA
in mean
and sd
values. This is caused by this line
dat %>%
select(.,contains(input$col_id)) %>%
summarise(mean = mean(input$col_id), sd=sd(input$col_id), n=n())
So how can I make a input$col_id
consumable for summarise()
? What is the correct way to do this?
Not a brilliant context:
> diamonds %>% filter(cut=="Good") %>% select(price) %>% summarise(mean = mean(price), sd=sd(price), n=n())
# A tibble: 1 × 3
mean sd n
<dbl> <dbl> <int>
1 3928.864 3681.59 4906
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Using development version dplyr
(v0.5.0.9002) you can turn your string into a character with rlang::sym()
and then use the unquote ( !!
or UQ
) operator to refer to the variable in dplyr verbs.
library(dplyr)
var1 <- "Good" # replace with input$op_id
var2 <- rlang::sym("price") # replace with input$col_id
diamonds %>%
filter(cut == var1) %>%
select_at(vars(!!var2)) %>%
summarise_at(vars(!!var2), funs(mean, sd, n()))
What gives:
## A tibble: 1 × 3
# mean sd n
# <dbl> <dbl> <int>
#1 3928.864 3681.59 4906
If you have multiple variables, use rlang::syms()
with the unquoted union operator ( !!!
or UQS
). For example:
var1 <- "Good"
var2 <- rlang::syms(c("price", "depth"))
diamonds %>%
filter(cut == var1) %>%
select_at(vars(UQS(var2))) %>%
summarise_at(vars(UQS(var2)), funs(mean, sd, n()))
What gives:
## A tibble: 1 × 6
# price_mean depth_mean price_sd depth_sd price_n depth_n
# <dbl> <dbl> <dbl> <dbl> <int> <int>
#1 3928.864 62.36588 3681.59 2.169374 4906 4906
For more information see the quasi-rotational section Programming with dplyr vignette
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