https://github.com/datastorm-open/shinymodules
This package provides shiny modules to build quickly an ergonomic tool to explore a table
https://github.com/datastorm-open/shinymodules
Last synced: 29 days ago
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This package provides shiny modules to build quickly an ergonomic tool to explore a table
- Host: GitHub
- URL: https://github.com/datastorm-open/shinymodules
- Owner: datastorm-open
- Created: 2021-01-25T08:36:18.000Z (over 4 years ago)
- Default Branch: master
- Last Pushed: 2023-11-23T14:01:21.000Z (over 1 year ago)
- Last Synced: 2024-08-03T22:20:04.157Z (10 months ago)
- Language: HTML
- Size: 2.23 MB
- Stars: 4
- Watchers: 5
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
# shinymodules
This package provides some useful shiny modules to build quickly an ergonomic tool to explore a table.
### Installation
You can install:
- the latest development version from GitHub with :
``` r
devtools::install_github("datastorm-open/shinymodules")
```
### Demo application
*online*
https://datastorm-demo.shinyapps.io/shinymodules/
*local*
``` r
if(!require(nycflights13)) install.packages("nycflights13")
if(!require(data.table)) install.packages("data.table")
if(!require(esquisse)) install.packages("esquisse")
if(!require(colourpicker)) install.packages("colourpicker")
runApp(system.file("demo_app", package = "shinymodules"))
```
## filter_data
``filter_data`` is a module used to filter a given data.table on chosen columns by the user. The server part returns a reactive value containing the filtered data.table.
```r
?shinymodules::filter_data
# ui.R
shinymodules::filter_data_UI(id = "filter_id"))
# server.R
full_data <- reactive({...})
output_filter <- shiny::callModule(module = shinymodules::filter_data,
id = "filter_id",
data = full_data,
columns_to_filter = "all")
# then, have fun with filter data !
your_filtered_table <- output_filter$data
```
## summary_data
Display an automatically generate dashboard that shows descriptive statistics with `shinymodules::summary_data` : for every columns from the table you selected. The statistics chosen depend on the column's type (character, factor, numeric, date).
```r
?shinymodules::summary_data
# ui.R
shinymodules::summary_data_UI(id = "stat_desc_id", titles = FALSE)
# server.R
data <- shiny::reactive({my_data})
shiny::callModule(module = shinymodules::summary_data,
id = "stat_desc_id",
data = shiny::reactive(data),
optional_stats = "all",
nb_modal2show = 6,
labels = list(title = "Descriptive statistics",
num_var = "Variables numériques",
date_var = "Variables dates",
factor_var = "Variables facteurs",
message = "Calcul des indicateurs en cours..."))
```
## show_DT
Show & export table using **DT** package
```r
?shinymodules::show_DT
# ui.R
shinymodules::show_DT_UI(
id = "iris_module",
export = c("csv", "html")
)
# server.R
shiny::callModule(module = show_DT,
id = "iris_module",
data = reactive(iris),
dt = reactive(DT::datatable(iris)),
file_name = paste0("Iris_export", format(Sys.time(), format = "%d%m%Y_%H%M%S"))
)
```
## monitoring_data
This module provides tools to monitor models. (Only quantitative regression at moment)
```r
## UI
shinymodules::monitoring_data_UI("my_id")
## SERVER
shiny::callModule(shinymodules::monitoring_data, "my_id", data = reactive(data),
col_obs = col_obs,
col_fit = col_fit,
col_date = col_date,
indicators = indicators)
```