Quoting Joe Cheng from [this shiny-discuss post](https://groups.google.com/d/msg/shiny-discuss/rU3vwGMZexQ/zeKhiYXrtEQJ)

&gt; By default, Shiny limits file uploads to 5MB per file. You can modify this limit by using the shiny.maxRequestSize option. For example, adding options(shiny.maxRequestSize=30*1024^2) to the top of server.R would increase the limit to 30MB.

What are the differences between `ng-pristine` and `ng-dirty`? It seems you can have both to be `true`:

    $scope.myForm.$pristine = true; // after editing the form



In AngularJS, what&#39;s the difference between ng-pristine and ng-dirty?

I&#39;d like to store a lot of words in a list. Many of these words are very similar. For example I have word `afrykanerskojęzyczny` and many of words like `afrykanerskojęzycznym`, `afrykanerskojęzyczni`, `nieafrykanerskojęzyczni`. What is the effective (fast and giving small diff size) solution to find difference between two strings and restore second string from the first one and diff?

Python - difference between two strings

I&#39;ve recently learned that R Shiny programs impose a maximum size restriction for file uploads by default (I don&#39;t know what the size is exactly, but I&#39;m guessing it&#39;s 5,000 KB). I&#39;d like to remove this restriction. How can I do so, and what is there a general rule of thumb for the size of user uploads?

In addition, this is on another note, but related: how can I save fie inputs by the user BY session? For example, there would be a file prompt in the application, in which the user can upload a file. Then, when the user chooses the file to display, he can pick among the files he has uploaded. If he exits the session, the list clears.

How to change &#39;Maximum upload size exceeded&#39; restriction in Shiny and save user file inputs?

<p>I've recently learned that R Shiny programs impose a maximum size restriction for file uploads by default (I don't know what the size is exactly, but I'm guessing it's 5,000 KB). I'd like to remove this restriction. How can I do so, and what is there a general rule of thumb for the size of user uploads?</p>
<p>In addition, this is on another note, but related: how can I save fie inputs by the user BY session? For example, there would be a file prompt in the application, in which the user can upload a file. Then, when the user chooses the file to display, he can pick among the files he has uploaded. If he exits the session, the list clears.</p>


I&#39;m creating a facetted plot to view predicted vs. actual values side by side with a plot of  predicted value vs. residuals. I&#39;ll be using `shiny` to help explore the results of modeling efforts using different training parameters. I train the model with 85% of the data, test on the remaining 15%, and repeat this 5 times, collecting actual/predicted values each time. After calculating the residuals, my `data.frame` looks like this:

    head(results)
           act     pred       resid
    2 52.81000 52.86750 -0.05750133
    3 44.46000 42.76825  1.69175252
    4 54.58667 49.00482  5.58184181
    5 36.23333 35.52386  0.70947731
    6 53.22667 48.79429  4.43237981
    7 41.72333 41.57504  0.14829173

What I want:

- Side by side plot of `pred` vs. `act` and `pred` vs. `resid`
- The x/y range/limits for `pred` vs. `act` to be the same, ideally from `min(min(results$act), min(results$pred))` to `max(max(results$act), max(results$pred))`
- The x/y range/limits for `pred` vs. `resid` *not* to be affected by what I do to the actual vs. predicted plot. Plotting for `x` over only the predicted values and `y` over only the residual range is fine.

In order to view both plots side by side, I melt the data:

    library(reshape2)
    plot &lt;- melt(results, id.vars = &quot;pred&quot;)

Now plot:

    library(ggplot2)
    p &lt;- ggplot(plot, aes(x = pred, y = value)) + geom_point(size = 2.5) + theme_bw()
    p &lt;- p + facet_wrap(~variable, scales = &quot;free&quot;)
    
    print(p)

That&#39;s pretty close to what I want:

![enter image description here][1]

What I&#39;d like is for the x and y ranges for actual vs. predicted to be the same, but I&#39;m not sure how to specify that, and I *don&#39;t* need that done for the predicted vs. residual plot since the ranges are completely different.

I tried adding something like this for both `scale_x_continous` and `scale_y_continuous`:
    
    min_xy &lt;- min(min(plot$pred), min(plot$value))
    max_xy &lt;- max(max(plot$pred), max(plot$value))

    p &lt;- ggplot(plot, aes(x = pred, y = value)) + geom_point(size = 2.5) + theme_bw()
    p &lt;- p + facet_wrap(~variable, scales = &quot;free&quot;)
    p &lt;- p + scale_x_continuous(limits = c(min_xy, max_xy))
    p &lt;- p + scale_y_continuous(limits = c(min_xy, max_xy))

    print(p)

But that picks up the `min()` of the residual values.

![enter image description here][2]

One last idea I had is to store the value of the minimum `act` and `pred` variables *before* melting, and then add them to the melted data frame in order to dictate in which facet they appear:

    head(results)
           act     pred       resid
    2 52.81000 52.86750 -0.05750133
    3 44.46000 42.76825  1.69175252
    4 54.58667 49.00482  5.58184181
    5 36.23333 35.52386  0.70947731

    min_xy &lt;- min(min(results$act), min(results$pred))
    max_xy &lt;- max(max(results$act), max(results$pred))
    
    plot &lt;- melt(results, id.vars = &quot;pred&quot;)

    plot &lt;- rbind(plot, data.frame(pred = c(min_xy, max_xy),
      variable = c(&quot;act&quot;, &quot;act&quot;), value = c(max_xy, min_xy)))

    p &lt;- ggplot(plot, aes(x = pred, y = value)) + geom_point(size = 2.5) + theme_bw()
    p &lt;- p + facet_wrap(~variable, scales = &quot;free&quot;)

    print(p)

That does what I want, with the exception that the points show up, too:

![enter image description here][3]

Any suggestions for doing something like this?

---

I saw [this idea](https://stackoverflow.com/questions/17400790/facet-wrap-how-to-add-y-axis-to-every-individual-graph-when-scales-free-x) to add `geom_blank()`, but I&#39;m not sure how to specify the `aes()` bit and have it work properly, or what the `geom_point()` equivalent is to the histogram use of `aes(y = max(..count..))`.

---

Here&#39;s data to play with (my actual, predicted, and residual values prior to melting):

    &gt; dput(results)
    structure(list(act = c(52.81, 44.46, 54.5866666666667, 36.2333333333333, 
    53.2266666666667, 41.7233333333333, 35.2966666666667, 30.6833333333333, 
    39.25, 35.8866666666667, 25.1, 29.0466666666667, 23.2766666666667, 
    56.3866666666667, 42.92, 41.57, 27.92, 23.16, 38.0166666666667, 
    61.8966666666667, 37.41, 41.6333333333333, 35.9466666666667, 
    48.9933333333333, 30.5666666666667, 32.08, 40.3633333333333, 
    53.2266666666667, 64.6066666666667, 38.5366666666667, 41.7233333333333, 
    25.78, 33.4066666666667, 27.8033333333333, 39.3266666666667, 
    48.9933333333333, 25.2433333333333, 32.67, 55.17, 42.92, 54.5866666666667, 
    23.16, 64.6066666666667, 40.7966666666667, 39.0166666666667, 
    41.6333333333333, 35.8866666666667, 25.1, 23.2766666666667, 44.46, 
    34.2166666666667, 40.8033333333333, 24.5766666666667, 35.73, 
    61.8966666666667, 62.1833333333333, 74.6466666666667, 39.4366666666667, 
    36.6, 27.1333333333333), pred = c(52.8675013282404, 42.7682474758679, 
    49.0048248585123, 35.5238560262515, 48.7942868566949, 41.5750416040131, 
    33.9548164913007, 29.9787449128663, 37.6443975781139, 36.7196211666685, 
    27.6043278172077, 27.0615724310721, 31.2073056885252, 55.0886903524179, 
    43.0895814712768, 43.0895814712768, 32.3549865881578, 26.2428426737583, 
    36.6926037128343, 56.7987490221996, 45.0370788180147, 41.8231642271826, 
    38.3297859332601, 49.5343916620086, 30.8535641206809, 29.0117492750411, 
    36.9767968381391, 49.0826677983065, 54.4678549541069, 35.5059204731218, 
    41.5333417555995, 27.6069075391361, 31.2404889715121, 27.8920960978598, 
    37.8505531149324, 49.2616631533957, 30.366837650159, 31.1623492639066, 
    55.0456078770405, 42.772538591063, 49.2419293590535, 26.1963523976241, 
    54.4080781796616, 44.9796700541254, 34.6996927469131, 41.6227713664027, 
    36.8449646519306, 27.5318686661673, 31.6641793552795, 42.8198894266632, 
    40.5769177148146, 40.5769177148146, 29.3807781312816, 36.8579132935989, 
    55.5617033901752, 55.8097119335638, 55.1041728261666, 43.6094641699075, 
    37.0674887276681, 27.3876960746536), resid = c(-0.0575013282403773, 
    1.69175252413213, 5.58184180815435, 0.709477307081826, 4.43237980997177, 
    0.148291729320228, 1.34185017536599, 0.704588420467079, 1.60560242188613, 
    -0.832954500001826, -2.50432781720766, 1.98509423559461, -7.93063902185855, 
    1.29797631424874, -0.169581471276786, -1.51958147127679, -4.43498658815778, 
    -3.08284267375831, 1.32406295383237, 5.09791764446704, -7.62707881801468, 
    -0.189830893849219, -2.38311926659339, -0.541058328675241, -0.286897454014273, 
    3.06825072495888, 3.38653649519422, 4.14399886836018, 10.1388117125598, 
    3.03074619354486, 0.189991577733821, -1.82690753913609, 2.16617769515461, 
    -0.088762764526507, 1.47611355173427, -0.268329820062384, -5.12350431682565, 
    1.5076507360934, 0.124392122959534, 0.147461408936991, 5.34473730761318, 
    -3.03635239762411, 10.1985884870051, -4.18300338745873, 4.31697391975358, 
    0.0105619669306023, -0.958297985263961, -2.43186866616734, -8.38751268861282, 
    1.64011057333683, -6.36025104814794, 0.226415618518729, -4.80411146461488, 
    -1.1279132935989, 6.33496327649151, 6.37362139976954, 19.5424938405001, 
    -4.17279750324084, -0.467488727668119, -0.254362741320246)), .Names = c(&quot;act&quot;, 
    &quot;pred&quot;, &quot;resid&quot;), row.names = c(2L, 3L, 4L, 5L, 6L, 7L, 8L, 9L, 
    10L, 11L, 12L, 13L, 15L, 16L, 17L, 18L, 19L, 20L, 21L, 22L, 23L, 
    24L, 25L, 26L, 28L, 29L, 30L, 31L, 32L, 33L, 34L, 35L, 36L, 37L, 
    38L, 39L, 41L, 42L, 43L, 44L, 45L, 46L, 47L, 48L, 49L, 50L, 51L, 
    52L, 54L, 55L, 56L, 57L, 58L, 59L, 60L, 61L, 62L, 63L, 64L, 65L
    ), class = &quot;data.frame&quot;)


  [1]: http://i.stack.imgur.com/WV8LQ.png
  [2]: http://i.stack.imgur.com/wlbEI.png
  [3]: http://i.stack.imgur.com/rlTMH.png

Setting individual axis limits with facet_wrap and scales = &quot;free&quot; in ggplot2

My version output is:

    &gt; version
                   _                            
    platform       x86_64-w64-mingw32           
    arch           x86_64                       
    os             mingw32                      
    system         x86_64, mingw32              
    status                                      
    major          2                            
    minor          15.2                         
    year           2012                         
    month          10                           
    day            26                           
    svn rev        61015                        
    language       R                            
    version.string R version 2.15.2 (2012-10-26)
    nickname       Trick or Treat    

where os is mingw32. Does that mean I&#39;m using only 32 bits? How can I change that?



How can I know if R is running on 64 bits versus 32?

For example if I have this:

   

    n = c(2, 3, 5) 
    s = c(&quot;aa&quot;, &quot;bb&quot;, &quot;cc&quot;) 
    b = c(TRUE, FALSE, TRUE) 
    df = data.frame(n, s, b)

      n  s     b
    1 2 aa  TRUE
    2 3 bb FALSE
    3 5 cc  TRUE

Then how do I combine the two columns `n` and `s` into a new column named `x` such that it looks like this:

      n  s     b     x
    1 2 aa  TRUE  2 aa
    2 3 bb FALSE  3 bb
    3 5 cc  TRUE  5 cc



Combine two or more columns in a dataframe into a new column with a new name

I tried to replace `NaN` values with zeros using the following script: 

    rapply( data123, f=function(x) ifelse(is.nan(x),0,x), how=&quot;replace&quot; )
    # [31]   0.00000000  -0.67994832   0.50287454   0.63979527   1.48410571  -2.90402836

The NaN value was showing to be zero but when I typed in the name of the data frame and tried to review it, the value was still remaining NaN.

    data123$contri_us
    # [31]          NaN  -0.67994832   0.50287454   0.63979527   1.48410571  -2.90402836

I am not sure whether the `rapply` command was actually applying the adjustment in the data frame, or just replaced the value as per shown.

Any idea how to actually change the `NaN` value to zero?

How to replace NaN value with zero in a huge data frame?

I have a script that reads in data from a CSV file into a `data.table` and then splits the text in one column into several new columns. I am currently using the `lapply` and `strsplit` functions to do this. Here&#39;s an example:

    library(&quot;data.table&quot;)
    df = data.table(PREFIX = c(&quot;A_B&quot;,&quot;A_C&quot;,&quot;A_D&quot;,&quot;B_A&quot;,&quot;B_C&quot;,&quot;B_D&quot;),
                    VALUE  = 1:6)
    dt = as.data.table(df)

    # split PREFIX into new columns
    dt$PX = as.character(lapply(strsplit(as.character(dt$PREFIX), split=&quot;_&quot;), &quot;[&quot;, 1))
    dt$PY = as.character(lapply(strsplit(as.character(dt$PREFIX), split=&quot;_&quot;), &quot;[&quot;, 2))

    dt 
    #    PREFIX VALUE PX PY
    # 1:    A_B     1  A  B
    # 2:    A_C     2  A  C
    # 3:    A_D     3  A  D
    # 4:    B_A     4  B  A
    # 5:    B_C     5  B  C
    # 6:    B_D     6  B  D 

In the example above the column `PREFIX` is split into two new columns `PX` and `PY` on the &quot;_&quot; character.

Even though this works just fine, I was wondering if there is a better (more efficient) way to do this using `data.table`. My real datasets have  &gt;=10M+ rows, so time/memory efficiency becomes really important.

---

### UPDATE:

Following @Frank&#39;s suggestion I created a larger test case and used the suggested commands, but the `stringr::str_split_fixed` takes a lot longer than the original method.

    library(&quot;data.table&quot;)
    library(&quot;stringr&quot;)
    system.time ({
        df = data.table(PREFIX = rep(c(&quot;A_B&quot;,&quot;A_C&quot;,&quot;A_D&quot;,&quot;B_A&quot;,&quot;B_C&quot;,&quot;B_D&quot;), 1000000),
                        VALUE  = rep(1:6, 1000000))
        dt = data.table(df)
    })
    #   user  system elapsed 
    #  0.682   0.075   0.758 

    system.time({ dt[, c(&quot;PX&quot;,&quot;PY&quot;) := data.table(str_split_fixed(PREFIX,&quot;_&quot;,2))] })
    #    user  system elapsed 
    # 738.283   3.103 741.674 

    rm(dt)
    system.time ( {
        df = data.table(PREFIX = rep(c(&quot;A_B&quot;,&quot;A_C&quot;,&quot;A_D&quot;,&quot;B_A&quot;,&quot;B_C&quot;,&quot;B_D&quot;), 1000000),
                         VALUE = rep(1:6, 1000000) )
        dt = as.data.table(df)
    })
    #    user  system elapsed 
    #   0.123   0.000   0.123 

    # split PREFIX into new columns
    system.time ({
        dt$PX = as.character(lapply(strsplit(as.character(dt$PREFIX), split=&quot;_&quot;), &quot;[&quot;, 1))
        dt$PY = as.character(lapply(strsplit(as.character(dt$PREFIX), split=&quot;_&quot;), &quot;[&quot;, 2))
    })
    #    user  system elapsed 
    #  33.185   0.000  33.191 

So the `str_split_fixed` method takes about 20X times longer.



Split text string in a data.table columns

I&#39;m writing a Shiny app for visualizing insurance benefit plans at my company. Here is what I&#39;d like to happen:

- I&#39;ll have a `selectInput` or `sliderInput` where the user will choose the number of individuals on their medical plan
- A matching number of double sided sliders will appear (one for each member)
- They can then input their estimates for best/worst case medical expenses for each member on their plan
- I have code that will take those estimates and create side by side plots illustrating the forecast cost on the three plan offerings so they can decide which one is least expensive based on their estimates

Here&#39;s my current `ui.R` file with hard coded inputs, simulating a family of four:

    shinyUI(pageWithSidebar(
      
      headerPanel(&quot;Side by side comparison&quot;),
      
      sidebarPanel(
        
        selectInput(inputId = &quot;class&quot;, label = &quot;Choose plan type:&quot;,
                    list(&quot;Employee only&quot; = &quot;emp&quot;, &quot;Employee and spouse&quot; = &quot;emp_spouse&quot;,
                         &quot;Employee and child&quot; = &quot;emp_child&quot;, &quot;Employee and family&quot; = &quot;emp_fam&quot;)),
        
        sliderInput(inputId = &quot;ind1&quot;, label = &quot;Individual 1&quot;,
                    min = 0, max = 20000, value = c(0, 2500), step = 250),
        
        sliderInput(inputId = &quot;ind2&quot;, label = &quot;Individual 2&quot;,
                    min = 0, max = 20000, value = c(0, 2500), step = 250),
        
        sliderInput(inputId = &quot;ind3&quot;, label = &quot;Individual 3&quot;,
                    min = 0, max = 20000, value = c(0, 2500), step = 250),
        
        sliderInput(inputId = &quot;ind4&quot;, label = &quot;Individual 4&quot;,
                    min = 0, max = 20000, value = c(0, 2500), step = 250)
        ),
      
      mainPanel(
        tabsetPanel(  
        tabPanel(&quot;Side by Side&quot;, plotOutput(outputId = &quot;main_plot&quot;, width = &quot;100%&quot;)),
        tabPanel(&quot;Summary&quot;, tableOutput(outputId = &quot;summary&quot;))
      )
    )))


Here&#39;s what it looks like (the transparent end sections are the result of HSA contributions from two of the plans. I thought it was a nice way to show both the premiums and medical expenses while showing the impact of the company HSA contribution. Thus, you&#39;d just compare the length of the solid colors).

![shiny-example][1]

I&#39;ve seen examples [like this](https://gist.github.com/wch/4211337) where the UI input itself is fixed (in this case, one `checkboxGroupInput` exists, but its contents are tailored based on the choice from another UI input), but I&#39;ve not seen examples of tailoring *the number* (or, say, type) of input elements spawned as the result of another UI input&#39;s contents.

Any suggestions on this (is it even possible)?

---

My last resort will be to create, say, 15 input sliders and initialize them to zero. My code will work just fine, but I&#39;d like to clean up the interface by not having to create that many sliders just for the occasional user who has a very large family.

---

**Update based on Kevin Ushay&#39;s answer**

I tried to go the `server.R` route and have this:

    shinyServer(function(input, output) {
      
      output$sliders &lt;- renderUI({
        members &lt;- as.integer(input$members) # default 2
        max_pred &lt;- as.integer(input$max_pred) # default 5000
        lapply(1:members, function(i) {
          sliderInput(inputId = paste0(&quot;ind&quot;, i), label = paste(&quot;Individual&quot;, i),
                      min = 0, max = max_pred, value = c(0, 500), step = 100)
        })
        
      })
    
    })

Immediately afterwards, I try and extract the values out of `input` for each individual&#39;s expenses:

    expenses &lt;- reactive({
        members &lt;- as.numeric(input$members)
        
        mins &lt;- sapply(1:members, function(i) {
          as.numeric(input[[paste0(&quot;ind&quot;, i)]])[1]
        })
        
        maxs &lt;- sapply(1:members, function(i) {
          as.numeric(input[[paste0(&quot;ind&quot;, i)]])[2]
        })
        
        expenses &lt;- as.data.frame(cbind(mins, maxs))
    })

Lastly, I have two functions that create objects to store a data frame for plotting based on the low and high medical expense estimates. They&#39;re called `best_case` and `worst_case` and both need the `expenses` object to work, so I call it as my first line as I learned from [this question](https://stackoverflow.com/questions/17683933/set-global-object-in-shiny)

    best_case &lt;- reactive({
        
        expenses &lt;- expenses()
    
        ...
    
    )}

I got some errors, so I used `browser()` to step through the `expenses` bit and noticed peculiar things like `input$ind1` not seeming to exist from within the `expenses` function.

I also played around with various `print()` statements in it to see what was happening. The most striking is when I do `print(names(input))` as the very first line in the function:

    [1] &quot;class&quot;    &quot;max_pred&quot; &quot;members&quot; 

    [1] &quot;class&quot;    &quot;ind1&quot;     &quot;ind2&quot;     &quot;max_pred&quot; &quot;members&quot; 

I get *two* outputs, which I believe is due to the defining of `expenses` and subsequent calling of it. Strangely... I don&#39;t get a third when `worst_case` uses the exact same `expenses &lt;- expense()` line.

If I do something like `print(expenses)` inside of my `expenses` function, I also get duplicates:

    # the first
      mins maxs
    1   NA   NA
    2   NA   NA

    # the second
      mins maxs
    1    0  500
    2    0  500

Any tips on why my `input` elements for `ind1` and `ind2` wouldn&#39;t show up until `expenses` is called the second time and thus prevent the data frame from being created correctly?

  [1]: http://i.stack.imgur.com/ZRhRS.png

Create dynamic number of input elements with R/Shiny

I&#39;ve got a shiny server version 0.4.0 and I want to have 4 small textInput boxes to look like this:

    x-min x-max y-min y-max
    [...] [...] [...] [...]

They now look like this:

    x-min 
    [...................]
    x-max
    [...................]
    y-min 
    [...................]
    y-max 
    [...................]

With this code:

    textInput(inputId=&quot;xlimitsmin&quot;, label=&quot;x-min&quot;, value = 0.0),
    textInput(inputId=&quot;xlimitsmax&quot;, label=&quot;x-max&quot;, value = 0.5),
    textInput(inputId=&quot;ylimitsmin&quot;, label=&quot;y-min&quot;, value = 0.5),
    textInput(inputId=&quot;ylimitsmax&quot;, label=&quot;y-max&quot;, value = 1.0),


Any ideas how to achieve this?

EDITED: I&#39;ve successfully changed things like this elsewhere in the code:

    &lt;style type=&quot;text/css&quot;&gt;select#yaxis4 { height: 280px; width: 500px; }&lt;/style&gt;
    [... which links to this later on in the page...]
              &lt;label class=&quot;control-label&quot; for=&quot;yaxis4&quot;&gt;Y-Axis&lt;/label&gt;
              &lt;select id=&quot;yaxis4&quot; multiple=&quot;multiple&quot;&gt;

And this is what it looks like for the ones that don&#39;t work:

    &lt;style type=&quot;text/css&quot;&gt;select#xlimitsmax { display: inline-block; max-width: 50px; }&lt;/style&gt;
    [... which links to...]
              &lt;label&gt;x-max&lt;/label&gt;
              &lt;input id=&quot;xlimitsmax&quot; type=&quot;text&quot; value=&quot;0.5&quot;/&gt;

EDITED:

Here is a self contained example `ui.R` that doesn&#39;t work:

    library(shiny)
    shinyUI(
    pageWithSidebar(
      # application title
      headerPanel(&quot;test01&quot;),
      sidebarPanel(
        tags$head(
          tags$style(type=&quot;text/css&quot;, &quot;select { max-width: 360px; }&quot;),
          tags$style(type=&quot;text/css&quot;, &quot;.span4 { max-width: 360px; }&quot;),
          tags$style(type=&quot;text/css&quot;,  &quot;.well { max-width: 360px; }&quot;)
                  ),
        wellPanel(
          p(strong(&quot;Side Panel:&quot;))
                 )
       ),
      mainPanel(
        textInput(inputId=&quot;xlimitsmin&quot;, label=&quot;x-min&quot;, value = 0.0),
        tags$head(tags$style(type=&quot;text/css&quot;, &quot;select#xlimitsmin { max-width: 50px }&quot;)),
        textInput(inputId=&quot;xlimitsmax&quot;, label=&quot;x-max&quot;, value = 0.5),
        tags$head(tags$style(type=&quot;text/css&quot;, &quot;select#xlimitsmax { display: inline-block; max-width: 50px; }&quot;))
        )
    ))

Resulting page:

![enter image description here][1]


  [1]: http://i.stack.imgur.com/vXOaO.png

shiny 4 small textInput boxes side-by-side

In a shiny app (by RStudio), on the _server_ side, I have a reactive that returns a list of variables by parsing the content of a `textInput`. The list of variables is then used in `selectInput` and/or `updateSelectInput`.

I can&#39;t make it work. Any suggestions?

I have made two attempts. The first approach is to use the reactive `outVar` directly into `selectInput`. The second approach is to use the reactive `outVar` in `updateSelectInput`. Neither works.

### server.R

    shinyServer(
      function(input, output, session) {
    
        outVar &lt;- reactive({
            vars &lt;- all.vars(parse(text=input$inBody))
            vars &lt;- as.list(vars)
            return(vars)
        })
    
        output$inBody &lt;- renderUI({
            textInput(inputId = &quot;inBody&quot;, label = h4(&quot;Enter a function:&quot;), value = &quot;a+b+c&quot;)
        })
    
        output$inVar &lt;- renderUI({  ## works but the choices are non-reactive
            selectInput(inputId = &quot;inVar&quot;, label = h4(&quot;Select variables:&quot;), choices =  list(&quot;a&quot;,&quot;b&quot;))
        })
    
        observe({  ## doesn&#39;t work
            choices &lt;- outVar()
            updateSelectInput(session = session, inputId = &quot;inVar&quot;, choices = choices)
        })

    })


### ui.R

    shinyUI(
      basicPage(
        uiOutput(&quot;inBody&quot;),
        uiOutput(&quot;inVar&quot;)
      )
    )

A short while ago, I posted the same question at shiny-discuss, but it has generated little interest, so I&#39;m asking again, with apologies, https://groups.google.com/forum/#!topic/shiny-discuss/e0MgmMskfWo


__Edit 1__

@Ramnath has kindly posted a solution that appears to work, denoted _Edit 2_ by him. But that solution does not address the problem because the `textinput` is on the `ui` side instead of on the `server` side as it is in my problem. If I move the `textinput` of Ramnath&#39;s second edit to the `server` side, the problem crops up again, namely: nothing shows and RStudio crashes. I found that wrapping `input$text` in `as.character` makes the problem disappear.

__Edit 2__

In further discussion, Ramnath has shown me that the problem arises when the server attempts to apply the dynamic function `outVar` before its arguments have been returned by `textinput`. The solution is to first check whether `is.null(input$inBody)` exists.

_**Checking for existence of arguments is a crucial aspect of building a shiny app**_, so why did I not think of it? Well, I did, but I must have done something wrong! Considering the amount of time I spent on the problem, it&#39;s a bitter experience. I show after the code how to check for existence.

Below is Ramnath&#39;s code with `textinput` moved to the `server` side. It crashes RStudio so don&#39;t try it at home. (I have used his notation)

    library(shiny)
    runApp(list(
      ui = bootstrapPage(
        uiOutput(&#39;textbox&#39;),  ## moving Ramnath&#39;s textinput to the server side
        uiOutput(&#39;variables&#39;)
      ),
      server = function(input, output){
        outVar &lt;- reactive({
          vars &lt;- all.vars(parse(text = input$text))  ## existence check needed here to prevent a crash
          vars &lt;- as.list(vars)
          return(vars)
        })
    
        output$textbox = renderUI({
          textInput(&quot;text&quot;, &quot;Enter Formula&quot;, &quot;a=b+c&quot;)
        })
    
        output$variables = renderUI({
          selectInput(&#39;variables2&#39;, &#39;Variables&#39;, outVar())
        })
      }
    ))

The way I usually check for existence is like this:

    if (is.null(input$text) || is.na(input$text)){
      return()
    } else {
      vars &lt;- all.vars(parse(text = input$text))
      return(vars)
    }

Ramnath&#39;s code is shorter:

    if (!is.null(mytext)){
      mytext = input$text
      vars &lt;- all.vars(parse(text = mytext))
      return(vars)
    }

Both seem to work, but I&#39;ll be doing it Ramnath&#39;s way from now on: maybe an unbalanced bracket in my construct had earlier prevented me to make the check work? Ramnath&#39;s check is more direct.

Lastly, I&#39;d like to note a couple of things about my various attempts to debug. 

In my debugging quest, I discovered that there is an option to &quot;rank&quot; the priority of &quot;outputs&quot; on the server side, which I explored in an attempt to solve my problem, but didn&#39;t work since the problem was elsewhere. Still, it&#39;s interesting to know and seems not very well known at this time:

    outputOptions(output, &quot;textbox&quot;, priority = 1)
    outputOptions(output, &quot;variables&quot;, priority = 2)

In that quest, I also _tried_ `try`:

    try(vars &lt;- all.vars(parse(text = input$text)))

That was pretty close, but still did not fix it.

The first solution I stumbled upon was: 

    vars &lt;- all.vars(parse(text = as.character(input$text)))

I suppose it would be interesting to know why it worked: is it because it slows things down enough? is it because `as.character` &quot;waits&quot; for `input$text` to be non-null?

Whatever the case may be, I am extremely grateful to Ramnath for his effort, patience and guidance.

R shiny passing reactive to selectInput choices

I&#39;ve been working on a shiny app and would like to include a logo in the upper right corner of the app. How can I easily embed an image using shiny and r?

Thanks!
K

Embedding Image in Shiny App

I want to output multiple lines of text using one `renderText()` command. However, this does not seem possible. For example, from the [shiny tutorial][1] we have truncated code in `server.R`:

    shinyServer(
      function(input, output) {
        output$text1 &lt;- renderText({paste(&quot;You have selected&quot;, input$var)
        output$text2 &lt;- renderText({paste(&quot;You have chosen a range that goes from&quot;,
          input$range[1], &quot;to&quot;, input$range[2])})
      }
    )

and code in `ui.R`:

    shinyUI(pageWithSidebar(
            
      mainPanel(textOutput(&quot;text1&quot;),
                textOutput(&quot;text2&quot;))
    ))

which essentially prints two lines:

    You have selected example
    You have chosen a range that goes from example range.

Is it possible to combine the two lines `output$text1` and `output$text2` into one block of code? My efforts so far have failed, e.g.

    output$text = renderText({paste(&quot;You have selected &quot;, input$var, &quot;\n&quot;, &quot;You have chosen a range that goes from&quot;, input$range[1], &quot;to&quot;, input$range[2])})

Anyone have any ideas?



  [1]: http://www.rstudio.com/shiny/lessons/Lesson-4/

Content Type	Original Author	Original Content on Stackoverflow
Question	jeffrey	View Question on Stackoverflow
Solution 1 - R	GSee	View Answer on Stackoverflow

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