`reshape2` let Hadley make a rebooted `reshape` that was way, way faster, while avoiding busting up people&#39;s dependencies and habits.

https://stat.ethz.ch/pipermail/r-packages/2010/001169.html

&gt; Reshape2 is a reboot of the reshape package. It&#39;s been over five years
&gt; since the first release of the package, and in that time I&#39;ve learned
&gt; a tremendous amount about R programming, and how to work with data in
&gt; R. Reshape2 uses that knowledge to make a new package for reshaping
&gt; data that is much more focussed and much much faster.
&gt; 
&gt; This version improves speed at the cost of functionality, so I have
&gt; renamed it to `reshape2` to avoid causing problems for existing users.
&gt; Based on user feedback I may reintroduce some of these features.
&gt; 
&gt; What&#39;s new in `reshape2`:
&gt; 
&gt;  * considerably faster and more memory efficient thanks to a much
&gt; better    underlying algorithm that uses the power and speed of
&gt; subsetting to the    fullest extent, in most cases only making a
&gt; single copy of the data.
&gt; 
&gt;  * cast is replaced by two functions depending on the output type:
&gt; `dcast`    produces data frames, and `acast` produces matrices/arrays.
&gt; 
&gt;  * multidimensional margins are now possible: `grand_row` and
&gt; `grand_col` have    been dropped: now the name of the margin refers to
&gt; the variable that has    its value set to (all).
&gt; 
&gt;  * some features have been removed such as the `|` cast operator, and
&gt; the    ability to return multiple values from an aggregation function.
&gt; I&#39;m    reasonably sure both these operations are better performed by
&gt; plyr.
&gt; 
&gt;  * a new cast syntax which allows you to reshape based on functions   
&gt; of variables (based on the same underlying syntax as plyr):
&gt; 
&gt;  * better development practices like namespaces and tests.

PHP DOMnode objects contain a [textContent](http://at.php.net/manual/en/class.domnode.php#domnode.props.textcontent) and [nodeValue](http://at.php.net/manual/en/class.domnode.php#domnode.props.nodevalue) attributes which both seem to be the innerHTML of the node.

&gt; nodeValue: The value of this node, depending on its type
&gt;
&gt; textContent: This attribute returns the text content of this node and its descendants.

What is the difference between these two properties? When is it proper to use one instead of the other?


PHP DOM textContent vs nodeValue?

Is there a &quot;typeof&quot; like function in Java that returns the type of a primitive data type (PDT) variable or an expression of operands PDTs?

`instanceof` seems to work for class types only.




How to determine the primitive type of a primitive variable?

I am attempting to understand why development had shifted from `reshape` to `reshape2` package. They seem to be functionally the same, however, I am unable to upgrade to `reshape2` currently due to an older version of R running on the server.  I am concerned about the possibility of a major bug that would have shifted development to a whole new package instead of simply continuing development of `reshape`.  Does anyone know if there is a major flaw in the `reshape` package?

reshape vs. reshape2 in R

<p>I am attempting to understand why development had shifted from <code>reshape</code> to <code>reshape2</code> package. They seem to be functionally the same, however, I am unable to upgrade to <code>reshape2</code> currently due to an older version of R running on the server.  I am concerned about the possibility of a major bug that would have shifted development to a whole new package instead of simply continuing development of <code>reshape</code>.  Does anyone know if there is a major flaw in the <code>reshape</code> package?</p>


The code:

    a &lt;- structure(list(`X$Days` = c(&quot;10&quot;, &quot;38&quot;, &quot;66&quot;, &quot;101&quot;, &quot;129&quot;, &quot;185&quot;, &quot;283&quot;, 
                                     &quot;374&quot;)), .Names = &quot;X$Days&quot;)

Then `a` is like

    $`X$Days`
    [1] &quot;10&quot;  &quot;38&quot;  &quot;66&quot;  &quot;101&quot; &quot;129&quot; &quot;185&quot; &quot;283&quot; &quot;374&quot;

I would like to coerce `a` to an array of numeric values, but coercing functions return me

    Error: (list) object cannot be coerced to type &#39;double&#39;

Thanks,



How to coerce a list object to type &#39;double&#39;

How do you refer to variables in a `data.table` if the variable names are stored in a character vector? For instance, this works for a `data.frame`:


    df &lt;- data.frame(col1 = 1:3)
    colname &lt;- &quot;col1&quot;
    df[colname] &lt;- 4:6
    df
    #   col1
    # 1    4
    # 2    5
    # 3    6

&lt;/pre&gt;

How can I perform this same operation for a data.table, either with or without `:=` notation? The obvious thing of `dt[ , list(colname)]` doesn&#39;t work (nor did I expect it to).   

Select / assign to data.table when variable names are stored in a character vector

I would like to associate sample size values with points on a plot.  I can use `geom_text` to position the numbers near the points, but this is messy.  It would be much cleaner to line them up along the outside edge of the plot.

For instance, I have:

    df=data.frame(y=c(&quot;cat1&quot;,&quot;cat2&quot;,&quot;cat3&quot;),x=c(12,10,14),n=c(5,15,20))

    ggplot(df,aes(x=x,y=y,label=n))+geom_point()+geom_text(size=8,hjust=-0.5)

Which produces this plot:
![enter image description here][1]

I would prefer something more like this:
![enter image description here][2]

I know I can create a second plot and use `grid.arrange` (a la [this post][3]) but it would be tedious to determine the spacing of the textGrobs to line up with the y-axis. Is there an easier way to do this?  Thanks!


  [1]: http://i.stack.imgur.com/QMnHc.jpg
  [2]: http://i.stack.imgur.com/wKDTK.jpg
  [3]: https://stackoverflow.com/questions/10525957/how-to-draw-lines-outside-of-plot-area-in-ggplot2

ggplot2 - annotate outside of plot

I&#39;m creating a plot in ggplot from a 2 x 2 study design and would like to use 2 colors and 2 symbols to classify my 4 different treatment combinations.  Currently I have 2 legends, one for the colors and one for the two shapes.  How can I combine them into a single legend so I have one blue circle, one red circle, one blue triangle, and one read triangle?

Some data:

    state1 &lt;- c(rep(c(rep(&quot;N&quot;, 7), rep(&quot;Y&quot;, 7)), 2))
    year &lt;- rep(c(2003:2009), 4)
    group1 &lt;- c(rep(&quot;C&quot;, 14), rep(&quot;E&quot;, 14))
    group2 &lt;- paste(state1, group1, sep = &quot;&quot;)
    beta &lt;- c(0.16,0.15,0.08,0.08,0.18,0.48,0.14,0.19,0.00,0.00,0.04,0.08,0.27,0.03,0.11,0.12,0.09,0.09,0.10,0.19,0.16,0.00,0.11,0.07,0.08,0.09,0.19,0.10)
        lcl &lt;- c(0.13,0.12,0.05,0.05,0.12,0.35,0.06,0.13,0.00,0.00,0.01,0.04,0.20,0.00,0.09,0.09,0.06,0.06,0.07,0.15,0.11,0.00,0.07,0.03,0.05,0.06,0.15,0.06)
        ucl &lt;- c(0.20,0.20,0.13,0.14,0.27,0.61,0.28,0.27,0.00,1.00,0.16,0.16,0.36,0.82,0.14,0.15,0.13,0.13,0.15,0.23,0.21,0.00,0.15,0.14,0.12,0.12,0.23,0.16)
    data &lt;- data.frame(state1,year,group1,group2,beta,lcl,ucl)


Plot:

    library(ggplot2)
    pd &lt;- position_dodge(.65)
    ggplot(data = data, aes(x = year, y = beta, colour = state1, group = group2, shape = group1)) +
      geom_point(position = pd, size = 4) +
      geom_errorbar(aes(ymin = lcl, ymax = ucl),colour = &quot;black&quot;, width = 0.5, position = pd) +
      scale_colour_hue(name = &quot;Treatment &amp; State&quot;,  #Legend label, use darker colors
                       labels = c(&quot;Control&quot;, &quot;Exclosure&quot;),
                       l = 40) +
      scale_shape(name = &quot;State&quot;, labels = c(&quot;Non-F&quot;, &quot;Flwr&quot;))

[![enter image description here][1]][1]


  [1]: https://i.stack.imgur.com/Kitw2.png

Combine legends for color and shape into a single legend

I have a data.frame in which certain variables contain a text string.  I wish to count the number of occurrences of a given character in each individual string.

Example:

    q.data&lt;-data.frame(number=1:3, string=c(&quot;greatgreat&quot;, &quot;magic&quot;, &quot;not&quot;))

I wish to create a new column for q.data with the number of occurence of &quot;a&quot; in string (ie. c(2,1,0)).


The only convoluted approach I have managed is:

    string.counter&lt;-function(strings, pattern){  
      counts&lt;-NULL
      for(i in 1:length(strings)){
        counts[i]&lt;-length(attr(gregexpr(pattern,strings[i])[[1]], &quot;match.length&quot;)[attr(gregexpr(pattern,strings[i])[[1]], &quot;match.length&quot;)&gt;0])
      }
    return(counts)
    }

    string.counter(strings=q.data$string, pattern=&quot;a&quot;)

     number     string number.of.a
    1      1 greatgreat           2
    2      2      magic           1
    3      3        not           0

How to calculate the number of occurrence of a given character in each row of a column of strings?

I have a dataframe in a wide format, with repeated measurements taken within different date ranges. In my example there are three different periods, all with their corresponding values. E.g. the first measurement (`Value1`) was measured in the period from `DateRange1Start` to `DateRange1End`: 

    ID DateRange1Start DateRange1End Value1 DateRange2Start DateRange2End Value2 DateRange3Start DateRange3End Value3
    1 1/1/90 3/1/90 4.4 4/5/91 6/7/91 6.2 5/5/95 6/6/96 3.3 

I&#39;m looking to reshape the data to a long format such that the DateRangeXStart and DateRangeXEnd columns are grouped,. Thus, what was 1 row in the original table becomes 3 rows in the new table:

    ID DateRangeStart DateRangeEnd Value
    1 1/1/90 3/1/90 4.4
    1 4/5/91 6/7/91 6.2
    1 5/5/95 6/6/96 3.3

I know there must be a way to do this with `reshape2`/`melt`/`recast`/`tidyr`, but I can&#39;t seem to figure it out how to map the multiple sets of measure variables into single sets of value columns in this particular way.


Reshaping multiple sets of measurement columns (wide format) into single columns (long format)

I&#39;ve been encountering what I think is a bug.  It&#39;s not a big deal, but I&#39;m curious if anyone else has seen this.  Unfortunately, my data is confidential, so I have to make up an example, and it&#39;s not going to be very helpful.

When subsetting my data, I occassionally get mysterious NA rows that aren&#39;t in my original data frame.  Even the rownames are NA.  EG:

    example &lt;- data.frame(&quot;var1&quot;=c(&quot;A&quot;, &quot;B&quot;, &quot;A&quot;), &quot;var2&quot;=c(&quot;X&quot;, &quot;Y&quot;, &quot;Z&quot;))
    example

      var1 var2
    1    A    X
    2    B    Y
    3    A    Z

then I run:

    example[example$var1==&quot;A&quot;,]

      var1 var2
    1    A    X
    3    A    Z
    NA&lt;NA&gt; &lt;NA&gt;

Of course, the example above does not actually give you this mysterious NA row; I am adding it here to illustrate the problem I&#39;m having with my data.

Maybe it has to do with the fact that I&#39;m importing my original data set using &lt;a href=&quot;http://cran.r-project.org/web/packages/xlsx/xlsx.pdf&quot;&gt;Google&#39;s read.xlsx package &lt;/a&gt; and then executing wide to long reshape before subsetting.

Thanks

Subsetting R data frame results in mysterious NA rows

I have a data frame as follow:

    +-----+-------+
    |  V1 |  V2   |
    +-----+-------+
    |  1  | a,b,c |
    |  2  | a,c   |
    |  3  | b,d   |
    |  4  | e,f   |
    |  .  | .     |
    +-----+-------+

Each of the alphabet is a character separated by comma. I would like to split V2 on each comma and insert the split strings as new rows. For instance, the desired output will be:

    +----+----+
    | V1 | V2 |
    +----+----+
    |  1 |  a |
    |  1 |  b |
    |  1 |  c |
    |  2 |  a |
    |  2 |  c |
    |  3 |  b |
    |  3 |  d |
    |  4 |  e |
    |  4 |  f |
    +----+----+

I am trying to use `strsplit()` to spit V2 first, then cast the list into a data frame. It didn&#39;t work. Any help will be appreciated.

Split delimited strings in a column and insert as new rows

I have a survey file in which row are observation and column question.

Here are some [fake data][1] they look like:

    People,Food,Music,People
    P1,Very Bad,Bad,Good
    P2,Good,Good,Very Bad
    P3,Good,Bad,Good
    P4,Good,Very Bad,Very Good
    P5,Bad,Good,Very Good
    P6,Bad,Good,Very Good


My aim is to create this kind of plot with `ggplot2`. 

 - I absolutely **don&#39;t care of the colors, design, etc.**
 - The plot doesn&#39;t correspond to the fake data

![enter image description here][2]


Here are my fake data:

    raw &lt;- read.csv(&quot;http://pastebin.com/raw.php?i=L8cEKcxS&quot;,sep=&quot;,&quot;)
    raw[,2]&lt;-factor(raw[,2],levels=c(&quot;Very Bad&quot;,&quot;Bad&quot;,&quot;Good&quot;,&quot;Very Good&quot;),ordered=FALSE)
    raw[,3]&lt;-factor(raw[,3],levels=c(&quot;Very Bad&quot;,&quot;Bad&quot;,&quot;Good&quot;,&quot;Very Good&quot;),ordered=FALSE)
    raw[,4]&lt;-factor(raw[,4],levels=c(&quot;Very Bad&quot;,&quot;Bad&quot;,&quot;Good&quot;,&quot;Very Good&quot;),ordered=FALSE)


But if I choose Y as count then I&#39;m facing an issue about choosing the X and the Group values... I don&#39;t know if I can succeed without using `reshape2`... I&#39;ve also tired to use reshape with melt function. But I don&#39;t understand how to use it...


  [1]: http://pastebin.com/raw.php?i=L8cEKcxS
  [2]: http://i.stack.imgur.com/yCWRc.png

Grouped bar plot in ggplot

A numpy matrix can be reshaped into a vector using reshape function with parameter -1. But I don&#39;t know what -1 means here.

For example: 

    a = numpy.matrix([[1, 2, 3, 4], [5, 6, 7, 8]])
    b = numpy.reshape(a, -1)

The result of `b` is: `matrix([[1, 2, 3, 4, 5, 6, 7, 8]])`

Does anyone know what -1 means here?
And it seems python assign -1 several meanings, such as: `array[-1]` means the last element. Can you give an explanation?



What does -1 mean in numpy reshape?

I get the following warning when I use min or max in the dcast function from the reshape2 package. What is it telling me? I can&#39;t find anything that explains the warning message and I&#39;m a bit confused about why I get it when I use max but not when I use mean or other aggregate functions.

&gt; Warning message:&lt;br&gt;In .fun(.value[0], ...) : no non-missing arguments to min; returning Inf

Here&#39;s a reproducible example:


    data(iris)
    
    library(reshape2)
    
    molten.iris &lt;- melt(iris,id.var=&quot;Species&quot;)
    summary(molten.iris)
    str(molten.iris)
    #------------------------------------------------------------
    # Both return warning:
    dcast(data=molten.iris,Species~variable,value.var=&quot;value&quot;,fun.aggregate=min)
    dcast(data=molten.iris,Species~variable,value.var=&quot;value&quot;,fun.aggregate=max)
    
    # Length looks fine though
    dcast(data=molten.iris,Species~variable,value.var=&quot;value&quot;,fun.aggregate=length)
    
    #------------------------------------------------------------
    # No warning messages here:
    aggregate(value ~ Species + variable, FUN=min, data=molten.iris)
    aggregate(value ~ Species + variable, FUN=max, data=molten.iris)
    #------------------------------------------------------------
    # Or here:
    library(plyr)
    
    ddply(molten.iris,c(&quot;Species&quot;,&quot;variable&quot;),function(df){
      data.frame(
        &quot;min&quot;=min(df$value),
        &quot;max&quot;=max(df$value)
        )
    })
    #------------------------------------------------------------

No non-missing arguments warning when using min or max in reshape2

I have the following dummy data: 

    library(dplyr)
    library(tidyr)
    library(reshape2)
    dt &lt;- expand.grid(Year = 1990:2014, Product=LETTERS[1:8], Country = paste0(LETTERS, &quot;I&quot;)) %&gt;%   select(Product, Country, Year)
    dt$value &lt;- rnorm(nrow(dt))

I pick two product-country combinations
   
    sdt &lt;- dt %&gt;% filter((Product == &quot;A&quot; &amp; Country == &quot;AI&quot;) | (Product == &quot;B&quot; &amp; Country ==&quot;EI&quot;))

and I want to see the values side by side for each combination. I can do this with `dcast`:
  
    sdt %&gt;% dcast(Year ~ Product + Country)

Is it possible to do this with `spread` from the package **tidyr**?


Is it possible to use spread on multiple columns in tidyr similar to dcast?

I&#39;m using `melt` and encounter the following warning message:  
`attributes are not identical across measure variables; they will be dropped`

After looking around people have mentioned it is because the variables are different classes; however, that is not the case with my dataset. 

Here is the dataset: 

    test &lt;- structure(list(park = structure(c(1L, 1L, 1L, 1L, 1L, 1L, 1L, 
    1L, 1L, 1L), .Label = c(&quot;miss&quot;, &quot;piro&quot;, &quot;sacn&quot;, &quot;slbe&quot;), class = &quot;factor&quot;), 
        a1.one = structure(c(3L, 1L, 3L, 3L, 3L, 3L, 1L, 3L, 3L, 
        3L), .Label = c(&quot;agriculture&quot;, &quot;beaver&quot;, &quot;development&quot;, &quot;flooding&quot;, 
        &quot;forest_pathogen&quot;, &quot;harvest_00_20&quot;, &quot;harvest_30_60&quot;, &quot;harvest_70_90&quot;, 
        &quot;none&quot;), class = &quot;factor&quot;), a2.one = structure(c(6L, 6L, 
        6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L), .Label = c(&quot;development&quot;, 
        &quot;forest_pathogen&quot;, &quot;harvest_00_20&quot;, &quot;harvest_30_60&quot;, &quot;harvest_70_90&quot;, 
        &quot;none&quot;), class = &quot;factor&quot;), a3.one = structure(c(3L, 3L, 
        3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L), .Label = c(&quot;forest_pathogen&quot;, 
        &quot;harvest_00_20&quot;, &quot;none&quot;), class = &quot;factor&quot;), a1.two = structure(c(3L, 
        3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L), .Label = c(&quot;agriculture&quot;, 
        &quot;beaver&quot;, &quot;development&quot;, &quot;flooding&quot;, &quot;forest_pathogen&quot;, &quot;harvest_00_20&quot;, 
        &quot;harvest_30_60&quot;, &quot;harvest_70_90&quot;, &quot;none&quot;), class = &quot;factor&quot;), 
        a2.two = structure(c(6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 
        6L), .Label = c(&quot;development&quot;, &quot;forest_pathogen&quot;, &quot;harvest_00_20&quot;, 
        &quot;harvest_30_60&quot;, &quot;harvest_70_90&quot;, &quot;none&quot;), class = &quot;factor&quot;), 
        a3.two = structure(c(3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 
        3L), .Label = c(&quot;forest_pathogen&quot;, &quot;harvest_00_20&quot;, &quot;none&quot;
        ), class = &quot;factor&quot;)), .Names = c(&quot;park&quot;, &quot;a1.one&quot;, &quot;a2.one&quot;, 
    &quot;a3.one&quot;, &quot;a1.two&quot;, &quot;a2.two&quot;, &quot;a3.two&quot;), row.names = c(NA, 10L
    ), class = &quot;data.frame&quot;)

And here is the structure:

    str(test)
    &#39;data.frame&#39;:	10 obs. of  7 variables:
     $ park  : Factor w/ 4 levels &quot;miss&quot;,&quot;piro&quot;,..: 1 1 1 1 1 1 1 1 1 1
     $ a1.one: Factor w/ 9 levels &quot;agriculture&quot;,..: 3 1 3 3 3 3 1 3 3 3
     $ a2.one: Factor w/ 6 levels &quot;development&quot;,..: 6 6 6 6 6 6 6 6 6 6
     $ a3.one: Factor w/ 3 levels &quot;forest_pathogen&quot;,..: 3 3 3 3 3 3 3 3 3 3
     $ a1.two: Factor w/ 9 levels &quot;agriculture&quot;,..: 3 3 3 3 3 3 3 3 3 3
     $ a2.two: Factor w/ 6 levels &quot;development&quot;,..: 6 6 6 6 6 6 6 6 6 6
     $ a3.two: Factor w/ 3 levels &quot;forest_pathogen&quot;,..: 3 3 3 3 3 3 3 3 3 3

Is it because the number of levels are different for each variable? So, can I just ignore the warning message in this case?

To generate the warning message:

    library(reshape2)
    test.m &lt;- melt (test,id.vars=c(&#39;park&#39;))
    Warning message:
    attributes are not identical across measure variables; they will be dropped

Thanks.


Content Type	Original Author	Original Content on Stackoverflow
Question	Alex	View Question on Stackoverflow
Solution 1 - R	Matt Parker	View Answer on Stackoverflow

reshape vs. reshape2 in R

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How to determine the primitive type of a primitive variable?

PHP DOM textContent vs nodeValue?

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