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Code for the Data menu in Radiant

Home Page: https://radiant-rstats.github.io/radiant.data

License: Other

R 43.27% JavaScript 1.50% CSS 0.35% Python 0.04% HTML 54.85%

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radiant.data's Issues

The best way to "pre-feed" datasets from postgress

Thank you very much for the very nice app. I am new to R but was tasked to tune up use of radiant so whenever we start the app, we have a dropdown list of datasets prepopulated with the data from our postgres server.

We figured to change 'radiant.init.data' option to reference names of the datasets of interest.

What would be the best way to make the datasets get populated before starting the radiant?
Would it be possible to dynamically establish loading of data from the postgres DB after choosing a specific name of a dataset?

Thank you in advance for any hints you could share.

Cheers,
PS might be of interest to @ypkoshka

r_info vs r_data

Dear Dr @vnijs ,
I am trying to understand the reason to include r_info reactive value with r_data.
Currently I doubt to use r_data or r_info in radiant.data extension. Mostly when i read in init.rfile:

...
r_info <- reactiveValues()
for (i in r_info_elements) {
r_info[[i]] <- r_data[[i]]
}
...

some clarification on the difference between r_data and r_info and the motivation to create r_info are welcome.
Many Thanks,
Karim

stop message could be dynamic

Dear Dr. @vnijs

define in global.R file of each extension

running_package <- "radiant.data"

stop_radiant <- function(rmd = FALSE, _running_package_) {
  ## quit R, unless you are running an interactive session
  if (interactive()) {
    ## flush input and r_data into Rgui or Rstudio
    isolate({
      toList(input) %>%
        {.$nav_radiant <- r_data$nav_radiant; .} %>%
        assign("r_state", ., envir = .GlobalEnv)

      assign("r_data", toList(r_data), envir = .GlobalEnv)

      stop_message <- paste0("\nStopped", _running_package_, ". State available as r_state and r_data.\n", sep="")

      lib <- if ("radiant" %in% installed.packages()) "radiant" else "radiant.data"

      if (!is_empty(input$rmd_report)) {
        rmd_report <-
          paste0("```{r echo = FALSE}\nknitr::opts_chunk$set(comment=NA, echo = FALSE, cache=FALSE, dpi = 96, message=FALSE, warning=FALSE)\nsuppressWarnings(suppressMessages(library(", lib, ")))\n#loadr('~/radiant.sessions/r_data.rda')\n```\n\n") %>%
          paste0(., input$rmd_report) %>% gsub("\\\\\\\\","\\\\",.) %>%
          cleanout(.)
        if (!rmd) {
          os_type <- Sys.info()["sysname"]
          if (os_type == 'Windows') {
            cat(rmd_report, file = "clipboard")
            stop_message %<>% paste0(., "Report content was copied to the clipboard.\n")
          } else if (os_type == "Darwin") {
            out <- pipe("pbcopy")
            cat(rmd_report, file = out)
            close(out)
            stop_message %<>% paste0(., "Report content was copied to the clipboard.\n")
          }
        }
}

Thanks
Karim

Remove calls to `$(window).unload`

Heads up that the next version of Shiny will upgrade jQuery from 1.x to 3.x. Unfortunately, this is not going to be an entirely painless upgrade; there are quite a few small but breaking changes in jQuery 1->2 and 2->3.

I noticed when testing Radiant that $(window).unload was being called, this method has been removed in jQuery 3.

From https://api.jquery.com/unload/:

Note: This API has been removed in jQuery 3.0; please use .on( "unload", handler ) instead of .unload( handler ) and .trigger( "unload" ) instead of .unload().

Sorry for the inconvenience!

Flexibility for radiant.data extension

Hi Dr Vincent,
If we want to change themes or add author in helps for extension it is necessary to recode radiant.data source.
For example in help_and_report function we needs to recode the name of author.
It will more flexible if we add un other argument like

help_and_report <- function(modal_title, fun_name, help_file, _author_) {

}

or have the option to change the themes. using different themes and logo colors for extensions seems intuitive.

options(radiant.nav_ui =
  list(windowTitle = "Radiant" ,__theme= shinythemes::shinytheme("cerulean")__ , id = "nav_radiant", inverse = TRUE, collapsible = TRUE, tabPanel("Data", withMathJax(), uiOutput("ui_data"))))

Thanks

license question: what exactly counts as help files?

The help files are under CC-NC-BY, which means that free software distributions cannot include them. I would like to package radiant.data for GNU Guix.

What exactly are the files that are under the CC-NC-BY license? Is it just the markdown files under inst/app/tools/help or does the license also apply to other files?

table similar to rpivotTable with rows selected in radiant.data

I am trying to replicate a pivot table that I created using rpivotTable using radiant.data. The pivot table and the data are found here.

This is the rpivotTable code:

rpivotTable(policy, rows = "Region", cols = "Product Category", aggregatorName = "Sum", vals = "Premium ($)")

This is my attempt at replicating the code using radiant.data:

pivotr("policy", cvars = "c("Region", Product Category)", nvar = "Premium ($)", fun = "sum", normalize = "total")$tab

Is there any way to replicate the pivot table created with rpivotTable regarding the selection of the rows, the columns to display, and the numeric value columns?

Thank you.

load example data: external data

Dear @vnijs,
I am having strange data when I load examples.
In radiant.dose package / folders I do not have these data.
The workspace is empty.
I try with new session and outside the project.
Any suggestion of how radiant.data imports examples and the possibility to imports other object around?
Thanks,
Karim

error message

Warning in data(list = item, package = exdat[i, "Package"], envir = environment()) :
  data set ‘BJsales.lead (BJsales)’ not found
Warning: Error in get: object 'BJsales.lead (BJsales)' not found
Stack trace (innermost first):
    74: get
    73: function_list[[k]]
    72: withVisible
    71: freduce
    70: _fseq
    69: eval
    68: eval
    67: withVisible
    66: %>%
    65: observeEventHandler [/Library/Frameworks/R.framework/Versions/3.3/Resources/library/radiant.data/app/tools/data/manage_ui.R#355]
     1: runApp

dataset

 $ AirPassengers    : Time-Series [1:144] from 1949 to 1961: 112 118 132 129 121 135 148 148 136 119 ...
 $ avengers         :'data.frame':  7 obs. of  4 variables:
  ..$ name     : chr [1:7] "Thor" "Iron Man" "Hulk" "Hawkeye" ...
  ..$ alignment: chr [1:7] "good" "good" "good" "good" ...
  ..$ gender   : chr [1:7] "male" "male" "male" "male" ...
  ..$ publisher: chr [1:7] "Marvel" "Marvel" "Marvel" "Marvel" ...
  ..- attr(*, "description")= chr "## Avengers\n\n### Variables\n\n- name = super hero name\n- alignment = good or bad character\n- gender = male or female\n- pub"| __truncated__
 $ avengers_descr   : chr "## Avengers\n\n### Variables\n\n- name = super hero name\n- alignment = good or bad character\n- gender = male or female\n- pub"| __truncated__
 $ BJsales          : Time-Series [1:150] from 1 to 150: 200 200 199 199 199 ...
 $ datasetlist      : chr [1:28] "BJsales" "AirPassengers" "txhousing" "seals" ...
 $ diamonds         :Classes ‘tbl_df’, ‘tbl’ and 'data.frame':  53940 obs. of  10 variables:
  ..$ carat  : num [1:53940] 0.23 0.21 0.23 0.29 0.31 0.24 0.24 0.26 0.22 0.23 ...
  ..$ cut    : Ord.factor w/ 5 levels "Fair"<"Good"<..: 5 4 2 4 2 3 3 3 1 3 ...
  ..$ color  : Ord.factor w/ 7 levels "D"<"E"<"F"<"G"<..: 2 2 2 6 7 7 6 5 2 5 ...
  ..$ clarity: Ord.factor w/ 8 levels "I1"<"SI2"<"SI1"<..: 2 3 5 4 2 6 7 3 4 5 ...
  ..$ depth  : num [1:53940] 61.5 59.8 56.9 62.4 63.3 62.8 62.3 61.9 65.1 59.4 ...
  ..$ table  : num [1:53940] 55 61 65 58 58 57 57 55 61 61 ...
  ..$ price  : int [1:53940] 326 326 327 334 335 336 336 337 337 338 ...
  ..$ x      : num [1:53940] 3.95 3.89 4.05 4.2 4.34 3.94 3.95 4.07 3.87 4 ...
  ..$ y      : num [1:53940] 3.98 3.84 4.07 4.23 4.35 3.96 3.98 4.11 3.78 4.05 ...
  ..$ z      : num [1:53940] 2.43 2.31 2.31 2.63 2.75 2.48 2.47 2.53 2.49 2.39 ...
 $ economics        :Classes ‘tbl_df’, ‘tbl’ and 'data.frame':  574 obs. of  6 variables:
  ..$ date    : Date[1:574], format: "1967-07-01" "1967-08-01" "1967-09-01" "1967-10-01" ...
  ..$ pce     : num [1:574] 507 510 516 513 518 ...
  ..$ pop     : int [1:574] 198712 198911 199113 199311 199498 199657 199808 199920 200056 200208 ...
  ..$ psavert : num [1:574] 12.5 12.5 11.7 12.5 12.5 12.1 11.7 12.2 11.6 12.2 ...
  ..$ uempmed : num [1:574] 4.5 4.7 4.6 4.9 4.7 4.8 5.1 4.5 4.1 4.6 ...
  ..$ unemploy: int [1:574] 2944 2945 2958 3143 3066 3018 2878 3001 2877 2709 ...
 $ economics_long   :Classes ‘grouped_df’, ‘tbl_df’, ‘tbl’ and 'data.frame':    2870 obs. of  4 variables:
  ..$ date    : Date[1:2870], format: "1967-07-01" "1967-08-01" "1967-09-01" "1967-10-01" ...
  ..$ variable: Factor w/ 5 levels "pce","pop","psavert",..: 1 1 1 1 1 1 1 1 1 1 ...
  ..$ value   : num [1:2870] 507 510 516 513 518 ...
  ..$ value01 : num [1:2870] 0 0.000266 0.000764 0.000472 0.000918 ...
  ..- attr(*, "vars")=List of 1
  .. ..$ : symbol variable
  ..- attr(*, "labels")='data.frame':   5 obs. of  1 variable:
  .. ..$ variable: Factor w/ 5 levels "pce","pop","psavert",..: 1 2 3 4 5
  .. ..- attr(*, "vars")=List of 1
  .. .. ..$ : symbol variable
  ..- attr(*, "indices")=List of 5
  .. ..$ : int [1:574] 0 1 2 3 4 5 6 7 8 9 ...
  .. ..$ : int [1:574] 574 575 576 577 578 579 580 581 582 583 ...
  .. ..$ : int [1:574] 1148 1149 1150 1151 1152 1153 1154 1155 1156 1157 ...
  .. ..$ : int [1:574] 1722 1723 1724 1725 1726 1727 1728 1729 1730 1731 ...
  .. ..$ : int [1:574] 2296 2297 2298 2299 2300 2301 2302 2303 2304 2305 ...
 $ faithfuld        :Classes ‘tbl_df’, ‘tbl’ and 'data.frame':  5625 obs. of  3 variables:
  ..$ eruptions: num [1:5625] 1.6 1.65 1.69 1.74 1.79 ...
  ..$ waiting  : num [1:5625] 43 43 43 43 43 43 43 43 43 43 ...
  ..$ density  : num [1:5625] 0.00322 0.00384 0.00444 0.00498 0.00542 ...
 $ filter_error     : chr ""
 $ lakers           :'data.frame':  34624 obs. of  13 variables:
  ..$ date     : int [1:34624] 20081028 20081028 20081028 20081028 20081028 20081028 20081028 20081028 20081028 20081028 ...
  ..$ opponent : chr [1:34624] "POR" "POR" "POR" "POR" ...
  ..$ game_type: chr [1:34624] "home" "home" "home" "home" ...
  ..$ time     : chr [1:34624] "12:00" "11:39" "11:37" "11:25" ...
  ..$ period   : int [1:34624] 1 1 1 1 1 1 1 1 1 1 ...
  ..$ etype    : chr [1:34624] "jump ball" "shot" "rebound" "shot" ...
  ..$ team     : chr [1:34624] "OFF" "LAL" "LAL" "LAL" ...
  ..$ player   : chr [1:34624] "" "Pau Gasol" "Vladimir Radmanovic" "Derek Fisher" ...
  ..$ result   : chr [1:34624] "" "missed" "" "missed" ...
  ..$ points   : int [1:34624] 0 0 0 0 0 2 0 1 0 2 ...
  ..$ type     : chr [1:34624] "" "hook" "off" "layup" ...
  ..$ x        : int [1:34624] NA 23 NA 25 NA 25 NA NA NA 36 ...
  ..$ y        : int [1:34624] NA 13 NA 6 NA 10 NA NA NA 21 ...
 $ luv_colours      :'data.frame':  657 obs. of  4 variables:
  ..$ L  : num [1:657] 9342 9101 8810 8935 8452 ...
  ..$ u  : num [1:657] -0.00000000000337 -474.91704355627468 1008.86477035531948 1065.69835296267433 1014.91062955050199 ...
  ..$ v  : num [1:657] 0 -635 1668 1675 1610 ...
  ..$ col: chr [1:657] "white" "aliceblue" "antiquewhite" "antiquewhite1" ...
 $ midwest          :Classes ‘tbl_df’, ‘tbl’ and 'data.frame':  437 obs. of  28 variables:
  ..$ PID                 : int [1:437] 561 562 563 564 565 566 567 568 569 570 ...
  ..$ county              : chr [1:437] "ADAMS" "ALEXANDER" "BOND" "BOONE" ...
  ..$ state               : chr [1:437] "IL" "IL" "IL" "IL" ...
  ..$ area                : num [1:437] 0.052 0.014 0.022 0.017 0.018 0.05 0.017 0.027 0.024 0.058 ...
  ..$ poptotal            : int [1:437] 66090 10626 14991 30806 5836 35688 5322 16805 13437 173025 ...
  ..$ popdensity          : num [1:437] 1271 759 681 1812 324 ...
  ..$ popwhite            : int [1:437] 63917 7054 14477 29344 5264 35157 5298 16519 13384 146506 ...
  ..$ popblack            : int [1:437] 1702 3496 429 127 547 50 1 111 16 16559 ...
  ..$ popamerindian       : int [1:437] 98 19 35 46 14 65 8 30 8 331 ...
  ..$ popasian            : int [1:437] 249 48 16 150 5 195 15 61 23 8033 ...
  ..$ popother            : int [1:437] 124 9 34 1139 6 221 0 84 6 1596 ...
  ..$ percwhite           : num [1:437] 96.7 66.4 96.6 95.3 90.2 ...
  ..$ percblack           : num [1:437] 2.575 32.9 2.862 0.412 9.373 ...
  ..$ percamerindan       : num [1:437] 0.148 0.179 0.233 0.149 0.24 ...
  ..$ percasian           : num [1:437] 0.3768 0.4517 0.1067 0.4869 0.0857 ...
  ..$ percother           : num [1:437] 0.1876 0.0847 0.2268 3.6973 0.1028 ...
  ..$ popadults           : int [1:437] 43298 6724 9669 19272 3979 23444 3583 11323 8825 95971 ...
  ..$ perchsd             : num [1:437] 75.1 59.7 69.3 75.5 68.9 ...
  ..$ percollege          : num [1:437] 19.6 11.2 17 17.3 14.5 ...
  ..$ percprof            : num [1:437] 4.36 2.87 4.49 4.2 3.37 ...
  ..$ poppovertyknown     : int [1:437] 63628 10529 14235 30337 4815 35107 5241 16455 13081 154934 ...
  ..$ percpovertyknown    : num [1:437] 96.3 99.1 95 98.5 82.5 ...
  ..$ percbelowpoverty    : num [1:437] 13.15 32.24 12.07 7.21 13.52 ...
  ..$ percchildbelowpovert: num [1:437] 18 45.8 14 11.2 13 ...
  ..$ percadultpoverty    : num [1:437] 11.01 27.39 10.85 5.54 11.14 ...
  ..$ percelderlypoverty  : num [1:437] 12.44 25.23 12.7 6.22 19.2 ...
  ..$ inmetro             : int [1:437] 0 0 0 1 0 0 0 0 0 1 ...
  ..$ category            : chr [1:437] "AAR" "LHR" "AAR" "ALU" ...
 $ mpg              :Classes ‘tbl_df’, ‘tbl’ and 'data.frame':  234 obs. of  11 variables:
  ..$ manufacturer: chr [1:234] "audi" "audi" "audi" "audi" ...
  ..$ model       : chr [1:234] "a4" "a4" "a4" "a4" ...
  ..$ displ       : num [1:234] 1.8 1.8 2 2 2.8 2.8 3.1 1.8 1.8 2 ...
  ..$ year        : int [1:234] 1999 1999 2008 2008 1999 1999 2008 1999 1999 2008 ...
  ..$ cyl         : int [1:234] 4 4 4 4 6 6 6 4 4 4 ...
  ..$ trans       : chr [1:234] "auto(l5)" "manual(m5)" "manual(m6)" "auto(av)" ...
  ..$ drv         : chr [1:234] "f" "f" "f" "f" ...
  ..$ cty         : int [1:234] 18 21 20 21 16 18 18 18 16 20 ...
  ..$ hwy         : int [1:234] 29 29 31 30 26 26 27 26 25 28 ...
  ..$ fl          : chr [1:234] "p" "p" "p" "p" ...
  ..$ class       : chr [1:234] "compact" "compact" "compact" "compact" ...
 $ msleep           :Classes ‘tbl_df’, ‘tbl’ and 'data.frame':  83 obs. of  11 variables:
  ..$ name        : chr [1:83] "Cheetah" "Owl monkey" "Mountain beaver" "Greater short-tailed shrew" ...
  ..$ genus       : chr [1:83] "Acinonyx" "Aotus" "Aplodontia" "Blarina" ...
  ..$ vore        : chr [1:83] "carni" "omni" "herbi" "omni" ...
  ..$ order       : chr [1:83] "Carnivora" "Primates" "Rodentia" "Soricomorpha" ...
  ..$ conservation: chr [1:83] "lc" NA "nt" "lc" ...
  ..$ sleep_total : num [1:83] 12.1 17 14.4 14.9 4 14.4 8.7 7 10.1 3 ...
  ..$ sleep_rem   : num [1:83] NA 1.8 2.4 2.3 0.7 2.2 1.4 NA 2.9 NA ...
  ..$ sleep_cycle : num [1:83] NA NA NA 0.133 0.667 ...
  ..$ awake       : num [1:83] 11.9 7 9.6 9.1 20 9.6 15.3 17 13.9 21 ...
  ..$ brainwt     : num [1:83] NA 0.0155 NA 0.00029 0.423 NA NA NA 0.07 0.0982 ...
  ..$ bodywt      : num [1:83] 50 0.48 1.35 0.019 600 ...
 $ nasa             :List of 2
  ..$ mets:List of 7
  .. ..$ cloudhigh  : num [1:24, 1:24, 1:12, 1:6] 26 20 16 13 7.5 8 14.5 19.5 22.5 21 ...
  .. ..$ cloudlow   : num [1:24, 1:24, 1:12, 1:6] 7.5 11.5 16.5 20.5 26 30 29.5 26.5 27.5 26 ...
  .. ..$ cloudmid   : num [1:24, 1:24, 1:12, 1:6] 34.5 32.5 26 14.5 10.5 9.5 11 17.5 18.5 16.5 ...
  .. ..$ ozone      : num [1:24, 1:24, 1:12, 1:6] 304 304 298 276 274 264 258 252 250 250 ...
  .. ..$ pressure   : num [1:24, 1:24, 1:12, 1:6] 835 940 960 990 1000 1000 1000 1000 1000 1000 ...
  .. ..$ surftemp   : num [1:24, 1:24, 1:12, 1:6] 273 280 285 289 292 ...
  .. ..$ temperature: num [1:24, 1:24, 1:12, 1:6] 272 282 285 291 293 ...
  ..$ dims:List of 4
  .. ..$ lat  : num [1:24] 36.2 33.7 31.2 28.7 26.2 ...
  .. ..$ long : num [1:24] -114 -111 -109 -106 -104 ...
  .. ..$ month: int [1:12] 1 2 3 4 5 6 7 8 9 10 ...
  .. ..$ year : int [1:6] 1995 1996 1997 1998 1999 2000
  ..- attr(*, "class")= chr "tbl_cube"
 $ nav_radiant      : chr "View state"
 $ plot_height      : num 600
 $ plot_width       : num 600
 $ population       :Classes ‘tbl_df’, ‘tbl’ and 'data.frame':  4060 obs. of  3 variables:
  ..$ country   : chr [1:4060] "Afghanistan" "Afghanistan" "Afghanistan" "Afghanistan" ...
  ..$ year      : int [1:4060] 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 ...
  ..$ population: int [1:4060] 17586073 18415307 19021226 19496836 19987071 20595360 21347782 22202806 23116142 24018682 ...
 $ presidential     :Classes ‘tbl_df’, ‘tbl’ and 'data.frame':  11 obs. of  4 variables:
  ..$ name : chr [1:11] "Eisenhower" "Kennedy" "Johnson" "Nixon" ...
  ..$ start: Date[1:11], format: "1953-01-20" "1961-01-20" "1963-11-22" "1969-01-20" ...
  ..$ end  : Date[1:11], format: "1961-01-20" "1963-11-22" "1969-01-20" "1974-08-09" ...
  ..$ party: chr [1:11] "Republican" "Democratic" "Democratic" "Republican" ...
 $ publishers       :'data.frame':  3 obs. of  2 variables:
  ..$ publisher : chr [1:3] "DC" "Marvel" "Image"
  ..$ yr_founded: int [1:3] 1934 1939 1992
  ..- attr(*, "description")= chr "## Comic publishers\n\n### Variables\n\n- publisher = name of the publisher\n- yr_founded = year the publisher was founded\n\n<"| __truncated__
 $ publishers_descr : chr "## Comic publishers\n\n### Variables\n\n- publisher = name of the publisher\n- yr_founded = year the publisher was founded\n\n<"| __truncated__
 $ seals            :Classes ‘tbl_df’, ‘tbl’ and 'data.frame':  1155 obs. of  4 variables:
  ..$ lat       : num [1:1155] 29.7 30.7 31.7 32.7 33.7 34.7 35.7 36.7 37.7 38.7 ...
  ..$ long      : num [1:1155] -173 -173 -173 -173 -173 ...
  ..$ delta_long: num [1:1155] -0.915 -0.867 -0.819 -0.771 -0.723 ...
  ..$ delta_lat : num [1:1155] 0.1435 0.1284 0.1132 0.098 0.0828 ...
 $ smiths           :Classes ‘tbl_df’, ‘tbl’ and 'data.frame':  2 obs. of  5 variables:
  ..$ subject: chr [1:2] "John Smith" "Mary Smith"
  ..$ time   : num [1:2] 1 1
  ..$ age    : num [1:2] 33 NA
  ..$ weight : num [1:2] 90 NA
  ..$ height : num [1:2] 1.87 1.54
 $ superheroes      :'data.frame':  7 obs. of  4 variables:
  ..$ name     : chr [1:7] "Magneto" "Storm" "Mystique" "Batman" ...
  ..$ alignment: chr [1:7] "bad" "good" "bad" "good" ...
  ..$ gender   : chr [1:7] "male" "female" "female" "male" ...
  ..$ publisher: chr [1:7] "Marvel" "Marvel" "Marvel" "DC" ...
  ..- attr(*, "description")= chr "## Super heroes\n\n### Variables\n\n- name = super hero name\n- alignment = good or bad character\n- gender = male or female\n-"| __truncated__
 $ superheroes_descr: chr "## Super heroes\n\n### Variables\n\n- name = super hero name\n- alignment = good or bad character\n- gender = male or female\n-"| __truncated__
 $ table1           :Classes ‘tbl_df’, ‘tbl’ and 'data.frame':  6 obs. of  4 variables:
  ..$ country   : chr [1:6] "Afghanistan" "Afghanistan" "Brazil" "Brazil" ...
  ..$ year      : int [1:6] 1999 2000 1999 2000 1999 2000
  ..$ cases     : int [1:6] 745 2666 37737 80488 212258 213766
  ..$ population: int [1:6] 19987071 20595360 172006362 174504898 1272915272 1280428583
 $ table2           :Classes ‘tbl_df’, ‘tbl’ and 'data.frame':  12 obs. of  4 variables:
  ..$ country: chr [1:12] "Afghanistan" "Afghanistan" "Afghanistan" "Afghanistan" ...
  ..$ year   : int [1:12] 1999 1999 2000 2000 1999 1999 2000 2000 1999 1999 ...
  ..$ type   : chr [1:12] "cases" "population" "cases" "population" ...
  ..$ count  : int [1:12] 745 19987071 2666 20595360 37737 172006362 80488 174504898 212258 1272915272 ...
 $ table3           :Classes ‘tbl_df’, ‘tbl’ and 'data.frame':  6 obs. of  3 variables:
  ..$ country: chr [1:6] "Afghanistan" "Afghanistan" "Brazil" "Brazil" ...
  ..$ year   : int [1:6] 1999 2000 1999 2000 1999 2000
  ..$ rate   : chr [1:6] "745/19987071" "2666/20595360" "37737/172006362" "80488/174504898" ...
 $ table4a          :Classes ‘tbl_df’, ‘tbl’ and 'data.frame':  3 obs. of  3 variables:
  ..$ country: chr [1:3] "Afghanistan" "Brazil" "China"
  ..$ 1999   : int [1:3] 745 37737 212258
  ..$ 2000   : int [1:3] 2666 80488 213766
 $ table4b          :Classes ‘tbl_df’, ‘tbl’ and 'data.frame':  3 obs. of  3 variables:
  ..$ country: chr [1:3] "Afghanistan" "Brazil" "China"
  ..$ 1999   : int [1:3] 19987071 172006362 1272915272
  ..$ 2000   : int [1:3] 20595360 174504898 1280428583
 $ table5           :Classes ‘tbl_df’, ‘tbl’ and 'data.frame':  6 obs. of  4 variables:
  ..$ country: chr [1:6] "Afghanistan" "Afghanistan" "Brazil" "Brazil" ...
  ..$ century: chr [1:6] "19" "20" "19" "20" ...
  ..$ year   : chr [1:6] "99" "00" "99" "00" ...
  ..$ rate   : chr [1:6] "745/19987071" "2666/20595360" "37737/172006362" "80488/174504898" ...
 $ titanic          :'data.frame':  1043 obs. of  10 variables:
  ..$ pclass  : Factor w/ 3 levels "1st","2nd","3rd": 1 1 1 1 1 1 1 1 1 1 ...
  ..$ survived: Factor w/ 2 levels "Yes","No": 1 1 2 2 2 1 1 2 1 2 ...
  ..$ sex     : Factor w/ 2 levels "female","male": 1 2 1 2 1 2 1 2 1 2 ...
  ..$ age     : num [1:1043] 29 0.917 2 30 25 ...
  ..$ sibsp   : num [1:1043] 0 1 1 1 1 0 1 0 2 0 ...
  ..$ parch   : num [1:1043] 0 2 2 2 2 0 0 0 0 0 ...
  ..$ fare    : num [1:1043] 211 152 152 152 152 ...
  ..$ name    : chr [1:1043] "Allen, Miss. Elisabeth Walton" "Allison, Master. Hudson Trevor" "Allison, Miss. Helen Loraine" "Allison, Mr. Hudson Joshua Crei" ...
  ..$ cabin   : chr [1:1043] "B5" "C22 C26" "C22 C26" "C22 C26" ...
  ..$ embarked: Factor w/ 3 levels "Cherbourg","Queenstown",..: 3 3 3 3 3 3 3 3 3 1 ...
  ..- attr(*, "description")= chr "## Titanic\n\nThis dataset describes the survival status of individual passengers on the Titanic. The titanic data frame does n"| __truncated__
 $ titanic_descr    : chr "## Titanic\n\nThis dataset describes the survival status of individual passengers on the Titanic. The titanic data frame does n"| __truncated__
 $ txhousing        :Classes ‘tbl_df’, ‘tbl’ and 'data.frame':  8602 obs. of  9 variables:
  ..$ city     : chr [1:8602] "Abilene" "Abilene" "Abilene" "Abilene" ...
  ..$ year     : int [1:8602] 2000 2000 2000 2000 2000 2000 2000 2000 2000 2000 ...
  ..$ month    : int [1:8602] 1 2 3 4 5 6 7 8 9 10 ...
  ..$ sales    : num [1:8602] 72 98 130 98 141 156 152 131 104 101 ...
  ..$ volume   : num [1:8602] 5380000 6505000 9285000 9730000 10590000 ...
  ..$ median   : num [1:8602] 71400 58700 58100 68600 67300 66900 73500 75000 64500 59300 ...
  ..$ listings : num [1:8602] 701 746 784 785 794 780 742 765 771 764 ...
  ..$ inventory: num [1:8602] 6.3 6.6 6.8 6.9 6.8 6.6 6.2 6.4 6.5 6.6 ...
  ..$ date     : num [1:8602] 2000 2000 2000 2000 2000 ...
 $ who              :Classes ‘tbl_df’, ‘tbl’ and 'data.frame':  7240 obs. of  60 variables:
  ..$ country     : chr [1:7240] "Afghanistan" "Afghanistan" "Afghanistan" "Afghanistan" ...
  ..$ iso2        : chr [1:7240] "AF" "AF" "AF" "AF" ...
  ..$ iso3        : chr [1:7240] "AFG" "AFG" "AFG" "AFG" ...
  ..$ year        : int [1:7240] 1980 1981 1982 1983 1984 1985 1986 1987 1988 1989 ...
  ..$ new_sp_m014 : int [1:7240] NA NA NA NA NA NA NA NA NA NA ...
  ..$ new_sp_m1524: int [1:7240] NA NA NA NA NA NA NA NA NA NA ...
  ..$ new_sp_m2534: int [1:7240] NA NA NA NA NA NA NA NA NA NA ...
  ..$ new_sp_m3544: int [1:7240] NA NA NA NA NA NA NA NA NA NA ...
  ..$ new_sp_m4554: int [1:7240] NA NA NA NA NA NA NA NA NA NA ...
  ..$ new_sp_m5564: int [1:7240] NA NA NA NA NA NA NA NA NA NA ...
  ..$ new_sp_m65  : int [1:7240] NA NA NA NA NA NA NA NA NA NA ...
  ..$ new_sp_f014 : int [1:7240] NA NA NA NA NA NA NA NA NA NA ...
  ..$ new_sp_f1524: int [1:7240] NA NA NA NA NA NA NA NA NA NA ...
  ..$ new_sp_f2534: int [1:7240] NA NA NA NA NA NA NA NA NA NA ...
  ..$ new_sp_f3544: int [1:7240] NA NA NA NA NA NA NA NA NA NA ...
  ..$ new_sp_f4554: int [1:7240] NA NA NA NA NA NA NA NA NA NA ...
  ..$ new_sp_f5564: int [1:7240] NA NA NA NA NA NA NA NA NA NA ...
  ..$ new_sp_f65  : int [1:7240] NA NA NA NA NA NA NA NA NA NA ...
  ..$ new_sn_m014 : int [1:7240] NA NA NA NA NA NA NA NA NA NA ...
  ..$ new_sn_m1524: int [1:7240] NA NA NA NA NA NA NA NA NA NA ...
  ..$ new_sn_m2534: int [1:7240] NA NA NA NA NA NA NA NA NA NA ...
  ..$ new_sn_m3544: int [1:7240] NA NA NA NA NA NA NA NA NA NA ...
  ..$ new_sn_m4554: int [1:7240] NA NA NA NA NA NA NA NA NA NA ...
  ..$ new_sn_m5564: int [1:7240] NA NA NA NA NA NA NA NA NA NA ...
  ..$ new_sn_m65  : int [1:7240] NA NA NA NA NA NA NA NA NA NA ...
  ..$ new_sn_f014 : int [1:7240] NA NA NA NA NA NA NA NA NA NA ...
  ..$ new_sn_f1524: int [1:7240] NA NA NA NA NA NA NA NA NA NA ...
  ..$ new_sn_f2534: int [1:7240] NA NA NA NA NA NA NA NA NA NA ...
  ..$ new_sn_f3544: int [1:7240] NA NA NA NA NA NA NA NA NA NA ...
  ..$ new_sn_f4554: int [1:7240] NA NA NA NA NA NA NA NA NA NA ...
  ..$ new_sn_f5564: int [1:7240] NA NA NA NA NA NA NA NA NA NA ...
  ..$ new_sn_f65  : int [1:7240] NA NA NA NA NA NA NA NA NA NA ...
  ..$ new_ep_m014 : int [1:7240] NA NA NA NA NA NA NA NA NA NA ...
  ..$ new_ep_m1524: int [1:7240] NA NA NA NA NA NA NA NA NA NA ...
  ..$ new_ep_m2534: int [1:7240] NA NA NA NA NA NA NA NA NA NA ...
  ..$ new_ep_m3544: int [1:7240] NA NA NA NA NA NA NA NA NA NA ...
  ..$ new_ep_m4554: int [1:7240] NA NA NA NA NA NA NA NA NA NA ...
  ..$ new_ep_m5564: int [1:7240] NA NA NA NA NA NA NA NA NA NA ...
  ..$ new_ep_m65  : int [1:7240] NA NA NA NA NA NA NA NA NA NA ...
  ..$ new_ep_f014 : int [1:7240] NA NA NA NA NA NA NA NA NA NA ...
  ..$ new_ep_f1524: int [1:7240] NA NA NA NA NA NA NA NA NA NA ...
  ..$ new_ep_f2534: int [1:7240] NA NA NA NA NA NA NA NA NA NA ...
  ..$ new_ep_f3544: int [1:7240] NA NA NA NA NA NA NA NA NA NA ...
  ..$ new_ep_f4554: int [1:7240] NA NA NA NA NA NA NA NA NA NA ...
  ..$ new_ep_f5564: int [1:7240] NA NA NA NA NA NA NA NA NA NA ...
  ..$ new_ep_f65  : int [1:7240] NA NA NA NA NA NA NA NA NA NA ...
  ..$ newrel_m014 : int [1:7240] NA NA NA NA NA NA NA NA NA NA ...
  ..$ newrel_m1524: int [1:7240] NA NA NA NA NA NA NA NA NA NA ...
  ..$ newrel_m2534: int [1:7240] NA NA NA NA NA NA NA NA NA NA ...
  ..$ newrel_m3544: int [1:7240] NA NA NA NA NA NA NA NA NA NA ...
  ..$ newrel_m4554: int [1:7240] NA NA NA NA NA NA NA NA NA NA ...
  ..$ newrel_m5564: int [1:7240] NA NA NA NA NA NA NA NA NA NA ...
  ..$ newrel_m65  : int [1:7240] NA NA NA NA NA NA NA NA NA NA ...
  ..$ newrel_f014 : int [1:7240] NA NA NA NA NA NA NA NA NA NA ...
  ..$ newrel_f1524: int [1:7240] NA NA NA NA NA NA NA NA NA NA ...
  ..$ newrel_f2534: int [1:7240] NA NA NA NA NA NA NA NA NA NA ...
  ..$ newrel_f3544: int [1:7240] NA NA NA NA NA NA NA NA NA NA ...
  ..$ newrel_f4554: int [1:7240] NA NA NA NA NA NA NA NA NA NA ...
  ..$ newrel_f5564: int [1:7240] NA NA NA NA NA NA NA NA NA NA ...
  ..$ newrel_f65  : int [1:7240] NA NA

save report: doc and pdf does not appear when radiant.data is run from desktop icon

@vnijs ,
I tried to run radiant.data from icon. I create file

#!/usr/local/bin/Rscript
library("radiant.data")
radiant.data()

chmod +x radiant_file

when I use icon

rstudioapi::isAvailable() # is FALSE

when I run radiant.data() (rstudio consol)

rstudioapi::isAvailable() # is TRUE

It seems that I can't save report with doc/pdf format without running rstudio.

We can run Rstudio from icon_file. In this case radiant.data() doesn't launched.

open -a RStudio
library("radiant.data")
radiant.data()

Any idea?
Thanks

download plot when the checkbox of Pause Plotting is TRUE

Dear Dr @vnijs,
it is not common to do this but maybe we can loose a part of the session.
If we check Pause Plotting, we can not download the last plot.
Karim

FILE NOT FOUND
Firefox can’t find the file at http://127.0.0.1:5475/session/d4a6b1f2a77e25af083cb56f2a2c7029/download/dl_.visualize?w=.

    Check the file name for capitalization or other typing errors.
    Check to see if the file was moved, renamed or deleted.

radiant.data incorrectly cannot load a file with the extension ".Rdata" created with save()

Seems like the logic for deciding the file format only depends on the extension given and not the actual contents. Also, it assumes (incorrectly) that all Operating Systems limit the user to a 3 character extension, thus a file named foo.Rdata created by save() won't load (with the error given below), but renaming it to foo.Rda works.

Error obtained while loading foo.Rdata

The filename extension (rdata) does not match the specified file-type (rda). Please specify the file type you are trying to upload (i.e., csv or rda)

The problem in radiant.data seems to be in:

radiant.data/inst/app/tools/data/manage.R

Line 65 in 0f1a10a

if (fext == "rda" && ext == "rds") ext <- "rda"

A quick workaround would be to use in that line:

if (fext %in% c("rda", "rdata") && ext == "rds") ext <- "rda"

FYI, the Rdata file format is described at the Library of Congress resource: https://www.loc.gov/preservation/digital/formats/fdd/fdd000470.shtml

diff: getdata(dataset), .getdata(dataset), getdata(input$dataset)

Dear Dr Vincent,
It is not really an issue. It is just for better understanding the code.

getdata(datasat,...): Get data for analysis functions

.getdata(dataset): get active dataset and apply data-filter if available

In Manageand View tabs, radiant uses active datasets by .getdata()or getdata(input$dataset). But in the other tabs Visualize, Pivotr, explore radiant uses getdata(dataset, ....)

In my mind it is enough to use active dataset bygetdata(input$dataset, vars=..,...)for all tabs.

What is the interest of all these options?
Karim
Thanks

radiant.data: object 'plot_annotation' is not exported by 'namespace:patchwork'

Ran

options(repos = c(RSM = "https://radiant-rstats.github.io/minicran", CRAN = "https://cloud.r-project.org"))
install.packages("radiant")

followed by

library(radiant)

produces:

Loading required package: radiant.data
Loading required package: magrittr
Loading required package: ggplot2
Loading required package: lubridate

Attaching package: 'lubridate'

The following objects are masked from 'package:base':

    date, intersect, setdiff, union

Loading required package: tidyr

Attaching package: 'tidyr'

The following object is masked from 'package:magrittr':

    extract

Loading required package: dplyr

Attaching package: 'dplyr'

The following objects are masked from 'package:stats':

    filter, lag

The following objects are masked from 'package:base':

    intersect, setdiff, setequal, union

Error: package or namespace load failed for 'radiant.data':
 object 'plot_annotation' is not exported by 'namespace:patchwork'
Error: package 'radiant.data' could not be loaded

So I restarted my R session and only loaded radiant.data giving me this:

Loading required package: magrittr
Loading required package: ggplot2
Loading required package: lubridate

Attaching package: 'lubridate'

The following objects are masked from 'package:base':

    date, intersect, setdiff, union

Loading required package: tidyr

Attaching package: 'tidyr'

The following object is masked from 'package:magrittr':

    extract

Loading required package: dplyr

Attaching package: 'dplyr'

The following objects are masked from 'package:stats':

    filter, lag

The following objects are masked from 'package:base':

    intersect, setdiff, setequal, union



Welcome to patchwork.


Version: 2.4


If this is your first time running patchwork you should visit the
homepage at (http://patchwork.r-forge.r-project.org/) or see ?patchwork.readme
or the README file found at the install location of patchwork/inst/README


Remember to keep patchwork up to date: update.packages(repos="http://R-Forge.R-project.org")
Error: package or namespace load failed for 'radiant.data':
 object 'plot_annotation' is not exported by 'namespace:patchwork'

I am running on Windows 11 Pro; error pops up in 4.0.5 and 4.1.2.patched in RStudio 2021.09.372 as welll as on R-4.0.5 --vanilla in a Terminal.

R-4.0.5 Session-Info:

R version 4.0.5 (2021-03-31)
Platform: x86_64-w64-mingw32/x64 (64-bit)
Running under: Windows 10 x64 (build 22000)

Matrix products: default

locale:
[1] LC_COLLATE=English_United Kingdom.1252
[2] LC_CTYPE=English_United Kingdom.1252
[3] LC_MONETARY=English_United Kingdom.1252
[4] LC_NUMERIC=C
[5] LC_TIME=English_United Kingdom.1252
system code page: 65001

attached base packages:
[1] stats     graphics  grDevices utils     datasets  methods   base

other attached packages:
[1] dplyr_1.0.7     tidyr_1.1.4     lubridate_1.8.0 ggplot2_3.3.5
[5] magrittr_2.0.1

loaded via a namespace (and not attached):
 [1] jsonlite_1.7.2       carData_3.0-5        RcppParallel_5.1.4
 [4] StanHeaders_2.21.0-7 shiny_1.7.1          assertthat_0.2.1
 [7] stats4_4.0.5         cellranger_1.1.0     pillar_1.6.4
[10] backports_1.4.1      glue_1.6.0           digest_0.6.29
[13] promises_1.2.0.1     colorspace_2.0-2     htmltools_0.5.2
[16] httpuv_1.6.4         pkgconfig_2.0.3      rstan_2.21.3
[19] broom_0.7.10         haven_2.4.3          purrr_0.3.4
[22] xtable_1.8-6         patchwork_2.4        scales_1.1.1
[25] processx_3.5.2       openxlsx_4.2.5       later_1.3.0
[28] rio_0.5.29           tibble_3.1.6         generics_0.1.1
[31] car_3.0-12           ellipsis_0.3.2       withr_2.4.3
[34] cli_3.1.0            crayon_1.4.2         readxl_1.3.1
[37] mime_0.12            ps_1.6.0             fansi_0.5.0
[40] MASS_7.3-54          forcats_0.5.1        foreign_0.8-81
[43] pkgbuild_1.3.1       tools_4.0.5          loo_2.4.1
[46] data.table_1.14.2    prettyunits_1.1.1    hms_1.1.1
[49] lifecycle_1.0.1      matrixStats_0.61.0   munsell_0.5.0
[52] zip_2.2.0            callr_3.7.0          compiler_4.0.5
[55] rlang_0.4.12         grid_4.0.5           base64enc_0.1-4
[58] gtable_0.3.0         codetools_0.2-18     inline_0.3.19
[61] abind_1.4-7          DBI_1.1.2            curl_4.3.2
[64] markdown_1.1.1       R6_2.5.1             gridExtra_2.3
[67] knitr_1.37           fastmap_1.1.0        utf8_1.2.2
[70] stringi_1.7.6        parallel_4.0.5       Rcpp_1.0.7
[73] import_1.2.0         vctrs_0.3.8          tidyselect_1.1.1

Variable names including "-" character raise "not found" error in View and Visualize tabs

Hello,

Radiant.data raise a Error : 'energy' object no found when importing data with dash "-" in the name:
openfoodfacts dataset imported through readr::read_delim provides variable names including (among others)

[57] "energy-from-fat_100g"                       "fat_100g"                                  
[59] "saturated-fat_100g"                         "caprylic-acid_100g"                        
[61] "capric-acid_100g"                           "lauric-acid_100g"                          
[63] "myristic-acid_100g"                         "palmitic-acid_100g"                        
[65] "stearic-acid_100g"                          "arachidic-acid_100g"                       
[67] "behenic-acid_100g"                          "montanic-acid_100g"

It would be nice to have radiant.data robust to this kind of variable names
Congratulation for the amazing job done so far in Radiant. I love it.
Best Regards,
Christophe

Feature - option to export R code for performed manipulations?

I have been using radiant for quite a while and it never fails to amaze. One thing I wanted to know/understand is the possibility of exporting the R code for corresponding actions performed? I understand that when we click on the Knit report, the performed actions are shown as R code in the report, however, I was wondering if I can export it like a regular input for me to save and apply it in the future. Is this already there?

request entity too large

I have a dataset of 27759 obs. and 14 variables which I'm unable to load into a Radiant app deployed on a Shiny-server. The only place I see a limit is if the file is greater than 10 mb... is there some other limit in place?

I've tried loading as RDS or csv, and I also tried another "large" dataset just to ensure the problem wasn't some weird dataset specific issue.

radiant.0.8.7.1 versus R.3.4.1

Dear Dr @vnijs
here my session info

R version 3.4.1 (2017-06-30)
Platform: x86_64-pc-linux-gnu (64-bit)
Running under: Ubuntu 16.04.2 LTS

Matrix products: default
BLAS: /usr/lib/libblas/libblas.so.3.6.0
LAPACK: /usr/lib/lapack/liblapack.so.3.6.0

locale:
 [1] LC_CTYPE=pt_PT.UTF-8       LC_NUMERIC=C               LC_TIME=pt_PT.UTF-8        LC_COLLATE=en_US.UTF-8     LC_MONETARY=pt_PT.UTF-8    LC_MESSAGES=en_US.UTF-8    LC_PAPER=pt_PT.UTF-8       LC_NAME=C                  LC_ADDRESS=C              
[10] LC_TELEPHONE=C             LC_MEASUREMENT=pt_PT.UTF-8 LC_IDENTIFICATION=C       

attached base packages:
[1] stats     graphics  grDevices utils     datasets  methods   base     

other attached packages:
[1] bindrcpp_0.2         plotly_4.7.0         shiny_1.0.3.9001     radiant.data_0.8.7.1 dplyr_0.7.1          tidyr_0.6.3          lubridate_1.6.0      ggplot2_2.2.1        magrittr_1.5        

loaded via a namespace (and not attached):
 [1] httr_1.2.1         jsonlite_1.5       viridisLite_0.2.0  splines_3.4.1      assertthat_0.2.0   yaml_2.1.14        backports_1.1.0    lattice_0.20-35    quantreg_5.33      glue_1.1.1         digest_0.6.12      pryr_0.1.2        
[13] minqa_1.2.4        colorspace_1.3-2   htmltools_0.3.6    httpuv_1.3.5       Matrix_1.2-10      plyr_1.8.4         psych_1.7.5        pkgconfig_2.0.1    broom_0.4.2        SparseM_1.77       purrr_0.2.2.2      xtable_1.8-2      
[25] scales_0.4.1       lme4_1.1-13        MatrixModels_0.4-1 tibble_1.3.3       mgcv_1.8-17        car_2.1-5          DT_0.2             nnet_7.3-12        lazyeval_0.2.0     pbkrtest_0.4-7     mnormt_1.5-5       mime_0.5          
[37] evaluate_0.10.1    nlme_3.1-131       MASS_7.3-47        foreign_0.8-69     tools_3.4.1        data.table_1.10.4  hms_0.3            stringr_1.2.0      munsell_0.4.3      shinyAce_0.2.1     compiler_3.4.1     rlang_0.1.1       
[49] grid_3.4.1         nloptr_1.0.4       rstudioapi_0.6     htmlwidgets_0.9    base64enc_0.1-3    rmarkdown_1.6      gtable_0.2.0       codetools_0.2-15   curl_2.7           markdown_0.8       reshape2_1.4.2     R6_2.2.2          
[61] gridExtra_2.2.1    knitr_1.16         bindr_0.1          rprojroot_1.2      readr_1.1.1        stringi_1.1.5      parallel_3.4.1     Rcpp_0.12.11       import_1.1.0

After running radiant.data I get a different sidebar menu in manage panel (screen-shot ) and I can't display tables in the others tabs.

Thanks,
Karim

error

I am new to radiant. I installed on my PC with current versions of R and R studio. I was able to upload my data, but when I chose "Visualize" I received this error msg: unused arguments (fragment.only = TRUE, stylesheet = "")

Exporting is_empty

Installed radiant on my Mac laptop. Tried to start it and received the following error.

Warning: Error in : 'is_empty' is not an exported object from 'namespace:radiant.data'

weighted.sd: unexpected implementation of na.rm

Hello.

I just found some unexpected behavior when using the function weighted.sd(x, wt). The parameter na.rm removes NAs seperately for the input vectors x and wt.

radiant.data/R/transform.R

Lines 440 to 448 in 64ec908

 weighted.sd <- function(x, wt, na.rm = TRUE) { 

 if (na.rm) { 

 x <- na.omit(x) 

 wt <- na.omit(wt) 

 } 

 wt <- wt / sum(wt) 

 wm <- weighted.mean(x, wt) 

 sqrt(sum(wt * (x - wm) ^ 2)) 

 }

I think it would make more sense to omit all entries where either x or wt is missing,

if (na.rm) {
  x <- x[!is.na(x) & !is.na(wt)]
  wt <- wt[!is.na(x) & !is.na(wt)]  
}

This way, the standard deviation can be calculated even if the the vectors have different amounts of NAs. The current implementation lead to an error for one of my colleagues because x contained a missing value and wt did not.

library(radiant.data)
x  <- mtcars$am
wt <- mtcars$wt

weighted.sd(x, wt)
#> [1] 0.4601711

x[1] <- NA
weighted.sd(x, wt)
#> Error in weighted.mean.default(x, wt): 'x' and 'w' must have the same length

report.R file: save report with Rmd

Dear Dr. Vincent,
line 278
replace library(radiant) by library(radiant.data)

knitr::opts_chunk$set(comment=NA, echo=FALSE, error = TRUE, cache=FALSE, message=FALSE, warning=FALSE)
options(width = 250)
suppressWarnings(suppressMessages(library(radiant)))
load("r_data.rda")

add sparklyr sources for "Load Data of Type"

Is it possible to add sparklyr connection sources in the Load Data Types ?
This would make Radiant a impressive spark business analytics tool.
Some related usability feature, like the "Sample Size" slider input could be seen in http://sparkdemo.rstudio.com/dashboards/diamonds-explorer/ or any other http://spark.rstudio.com/examples.html.
Thanks a lot
Best regards,
Christophe

radiant extension: setting image size re-init select vars to last session and not actual state vars

Dear Dr. @vnijs ,
I am working on an other tab with plotting functions which I can not dowith Visualize tab.
I am using selected = state_multiple("id", vars) in selectInput(...) arguments.
When I change the width or the height of plot, The selected vars change to last opened session and not state in actual one.
here a screenshot for the issue.
https://github.com/kmezhoud/radiant.dose/blob/master/stateMultipleDemo.gif

Any suggestion is welcome.
Thanks,
Karim

radiant extension: Adapt helps of radiant.data to extension field

Dear Dr. @vnijs ,
For radiant extension, developer needs to adapt the examples of helps depending on package field and default data set used in the extension. In my case, I replaced diamonds.rda by other data set from cancer genomics.
The issue is when I go to data_ui from radiant.data and I explore helps, the example seems to be out of area (diamonds).
for example to change explore_ui help, developer can edit data_ui.R of radiant.data and add help_modal() function BEFORE uiOutput("ui_Explore) , like this:

conditionalPanel("input.tabs_data == 'Explore'",
                         ## needed to modify radiant helps
                         help_modal("Explore","explore_help",author = "Karim Mezhoud",
                                    inclMD(file.path(getOption("radiant.path.bioCancer"),"app/tools/help/Statistics.md"))),
                         uiOutput("ui_Explore"))

data_ui.R

statistics.md

Dataset description

Thank you so much for your guidance on how to connect to Postgres database and upload the data (#30 (comment)). Here is a follow-up question: would it be possible to upload the dataset description along with the dataset? I know one can manually enter the description once the data is uploaded but I wonder whether it would be possible to have automatically populated when the data is being uploaded? If so, where would it be stored? Should it be stored in the dataset as a separate field? Could you please point to the R code which deals with the data description storage / upload?

Pivot: factor and date in catagorical variable

@vnijs
I can't reproduce the issue using diamonds data set. I am using dosimetry.rda.
Case study:
I would like to visualize the cumulative doses (sum) of 4 samples of each person. 4 samples means I have 4 sampling dates.
Categorical variables: Name (factor) + Date (date)
numeric variable: DCE (numeric)
apply function: sum

If I invert the order of categorical variable: Date (date) + Name (factor), the error is avoided.

error

Warning: Error in eval: found duplicated column name: Date
Stack trace (innermost first):
    119: <Anonymous>
    118: stop
    117: mutate_impl
    116: mutate_.tbl_df
    115: mutate_
    114: mutate_each_
    113: function_list[[k]]
    112: withVisible
    111: freduce
    110: _fseq
    109: eval
    108: eval
    107: withVisible
    106: %>%
    105: <Anonymous>
    104: do.call
    103: withCallingHandlers
    102: suppressMessages
    101: withCallingHandlers
    100: suppressWarnings
     99: sshhr
     98: eval [tools/data/pivotr_ui.R#168]
     97: eval
     96: withProgress
     95: <reactive:.pivotr> [tools/data/pivotr_ui.R#167]
     84: .pivotr
     83: exprFunc [tools/data/pivotr_ui.R#182]
     82: widgetFunc
     81: func
     80: origRenderFunc
     79: renderFunc
     78: origRenderFunc
     77: output$pivotr
      2: runApp
      1: radiant.data

radiant extension: modify output$ui_data

Dear Dr. @vnijs ,
I would like to add or rearrange ui_datatabs following comments and recommendations from reviewers.
For example,
1- I have to re-group all Visualization function into the same tab. In this case I need to add to Visualize tab, other network interaction generated by DiagrammeR and VisNetwork packages.
2- Also I would like to edit directly data from View tab. Something better than this https://github.com/kmezhoud/radiant.dose/blob/master/eData.gif

After sourcing ui from radiant.data package
server.R

# source data & app tools from radiant.data
  for (file in list.files(c(file.path(getOption("radiant.path.data"),"app/tools/app"),
                            file.path(getOption("radiant.path.data"),"app/tools/data")
                            ),
                          pattern="\\.(r|R)$", full.names = TRUE))
    source(file, encoding = getOption("radiant.encoding"), local = TRUE)

I added in server.R

source(file.path(getOption("radiant.path.bioCancer"),"app/tools/bioCancer/data_ui.R"),
       encoding = getOption("radiant.encoding"), local = TRUE)

with data_ui.R file from radiant.datapackage yet without modifications.

I received error

> runApp('inst/app')

Listening on http://127.0.0.1:6639
Warning: Error in returnTextAreaInput: unused argument (placeholder = "Provide a filter (e.g., price >  5000) and press return")
Stack trace (innermost first):
    99: tag
    98: tags$div
    97: div
    96: conditionalPanel
    95: tag
    94: tags$div
    93: div
    92: conditionalPanel
    91: tag
    90: tags$div
    89: div
    88: wellPanel
    87: tag
    86: tags$form
    85: tag
    84: tags$div
    83: div
    82: sidebarPanel
    81: sidebarLayout
    80: tagList
    79: renderUI [tools/bioCancer/data_ui.R#7]
    78: func
    77: origRenderFunc
    76: output$ui_data
     1: runApp

Any suggestion to modify output$data_uiis welcome.
Thanks,
Karim

	weighted.sd <- function(x, wt, na.rm = TRUE) {
	if (na.rm) {
	x <- na.omit(x)
	wt <- na.omit(wt)
	}
	wt <- wt / sum(wt)
	wm <- weighted.mean(x, wt)
	sqrt(sum(wt * (x - wm) ^ 2))
	}

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