When I need to filter a data.frame, i.e., extract rows that meet certain conditions, I prefer to use the `subset` function:

    subset(airquality, Month == 8 &amp; Temp &gt; 90)

Rather than the `[` function:

    airquality[airquality$Month == 8 &amp; airquality$Temp &gt; 90, ]

There are two main reasons for my preference:

 1. I find the code reads better, from left to right. Even people who know nothing about R could tell what the `subset` statement above is doing.

 2. Because columns can be referred to as variables in the `select` expression, I can save a few keystrokes. In my example above, I only had to type `airquality` once with `subset`, but three times with `[`.

So I was living happy, using `subset` everywhere because it is shorter and reads better, even advocating its beauty to my fellow R coders. But yesterday my world broke apart. While reading the `subset` documentation, I notice this section:

&gt;Warning
&gt;
&gt;This is a convenience function intended for use interactively. For programming it is better to use the standard subsetting functions like [, and in particular the non-standard evaluation of argument subset can have unanticipated consequences.

Could someone help clarify what the authors mean?

First, what do they mean by &quot;*for use interactively*&quot;? I know what an interactive session is, as opposed to a script run in BATCH mode but I don&#39;t see what difference it should make.

Then, could you please explain &quot;*the non-standard evaluation of argument subset*&quot; and why it is dangerous, maybe provide an example?


Why is `[` better than `subset`?

I have a large data set and I would like to read specific columns or drop all the others.

    data &lt;- read.dta(&quot;file.dta&quot;)

I select the columns that I&#39;m not interested in:

    var.out &lt;- names(data)[!names(data) %in% c(&quot;iden&quot;, &quot;name&quot;, &quot;x_serv&quot;, &quot;m_serv&quot;)]

and than I&#39;d like to do something like:

    for(i in 1:length(var.out)) {
       paste(&quot;data$&quot;, var.out[i], sep=&quot;&quot;) &lt;- NULL
    }

to drop all the unwanted columns. Is this the optimal solution?


How to drop columns by name in a data frame

A categorical variable V1 in a data frame D1 can have values represented by the letters from A to Z. I want to create a subset D2, which excludes some values, say, B, N and T. Basically, I want a command which is the opposite of `%in%`

    D2 = subset(D1, V1 %in% c(&quot;B&quot;, &quot;N&quot;, &quot;T&quot;))



Opposite of %in%: exclude rows with values specified in a vector

I want to create different methods for a class called [Multiset][1].

I have all the required methods, but I&#39;m unsure of how to write intersection, union, and subset methods.

For intersection and union, my code starts like this:

    def intersect(var)
      x = Multiset.new
    end

Here is an example:

    X = [1, 1, 2, 4]
    Y = [1, 2, 2, 2]

then the intersection of `X` and `Y` is `[1, 2]`. 

[1]: http://en.wikipedia.org/wiki/Multiset

How can I get the intersection, union, and subset of arrays in Ruby?

I want to filter rows from a `data.frame` based on a logical condition. Let&#39;s suppose that I have data frame like

       expr_value     cell_type
    1    5.345618 bj fibroblast
    2    5.195871 bj fibroblast
    3    5.247274 bj fibroblast
    4    5.929771          hesc
    5    5.873096          hesc
    6    5.665857          hesc
    7    6.791656          hips
    8    7.133673          hips
    9    7.574058          hips
    10   7.208041          hips
    11   7.402100          hips
    12   7.167792          hips
    13   7.156971          hips
    14   7.197543          hips
    15   7.035404          hips
    16   7.269474          hips
    17   6.715059          hips
    18   7.434339          hips
    19   6.997586          hips
    20   7.619770          hips
    21   7.490749          hips

What I want to is to get a new data frame which looks the same but only has the data for one cell_type. E.g. subset / select rows which contains the cell type &quot;hesc&quot;:

       expr_value     cell_type
    1    5.929771          hesc
    2    5.873096          hesc
    3    5.665857          hesc

Or either cell type &quot;bj fibroblast&quot; or &quot;hesc&quot;:

       expr_value     cell_type
    1    5.345618 bj fibroblast
    2    5.195871 bj fibroblast
    3    5.247274 bj fibroblast
    4    5.929771          hesc
    5    5.873096          hesc
    6    5.665857          hesc

Is there any easy way to do this?

I&#39;ve tried:

    expr[expr[2] == &#39;hesc&#39;]
    # [1] &quot;5.929771&quot; &quot;5.873096&quot; &quot;5.665857&quot; &quot;hesc&quot;     &quot;hesc&quot;     &quot;hesc&quot;    
    

if the original data frame is called &quot;expr&quot;, but it gives the results in wrong format as you can see.



Filter data.frame rows by a logical condition

Any idea on how to check whether that list is a subset of another?

Specifically, I have

    List&lt;double&gt; t1 = new List&lt;double&gt; { 1, 3, 5 };
    List&lt;double&gt; t2 = new List&lt;double&gt; { 1, 5 };

How to check that t2 is a subset of t1, using LINQ?

Check whether an array is a subset of another

![enter image description here][1]

I wish to filter a data frame based on conditions in several columns. For example, how can I delete rows if column A = B and Column E = 0.

  [1]: http://i.stack.imgur.com/iyJCo.png

Subset data frame based on multiple conditions

I&#39;m trying to write a custom filter method that takes an arbitrary number of *kwargs* and returns a list containing the elements of a database-like list that contain those *kwargs*.

For example, suppose `d1 = {&#39;a&#39;:&#39;2&#39;, &#39;b&#39;:&#39;3&#39;}` and `d2` = the same thing. `d1 == d2` results in True. But suppose `d2` = the same thing plus a bunch of other things. My method needs to be able to tell if **d1 in d2**, but Python can&#39;t do that with dictionaries.

Context:

I have a Word class, and each object has properties like `word`, `definition`, `part_of_speech`, and so on. I want to be able to call a filter method on the main list of these words, like `Word.objects.filter(word=&#39;jump&#39;, part_of_speech=&#39;verb-intransitive&#39;)`. I can&#39;t figure out how to manage these keys and values at the same time. But this could have larger functionality outside this context for other people.

How to check if one dictionary is a subset of another larger dictionary?

I want to select rows from a data frame based on partial match of a string in a column, e.g. column &#39;x&#39; contains the string &quot;hsa&quot;. Using `sqldf` - _if_ it had a `like` syntax - I would do something like:

`select * from &lt;&gt; where x like &#39;hsa&#39;`.

Unfortunately, `sqldf` does not support that syntax.

Or similarly:

    selectedRows &lt;- df[ , df$x %like% &quot;hsa-&quot;]

Which of course doesn&#39;t work.

Can somebody please help me with this? 



Selecting data frame rows based on partial string match in a column

I have a list of parameters like this:

    public class parameter
    {
        public string name {get; set;}
        public string paramtype {get; set;}
        public string source {get; set;}
    }

    IEnumerable&lt;Parameter&gt; parameters;

And a array of strings i want to check it against.

    string[] myStrings = new string[] { &quot;one&quot;, &quot;two&quot;};

I want to iterate over the parameter list and check if the source property is equal to any of the myStrings array. I can do this with nested foreach&#39;s but i would like to learn how to do it in a nicer way as i have been playing around with linq and like the extension methods on enumerable like where etc so nested foreachs just feel wrong. Is there a more elegant preferred linq/lambda/delegete way to do this. 

Thanks


Check if list&lt;t&gt; contains any of another list

We have a data frame from a CSV file. The data frame `DF` has columns that contain observed values and a column (`VaR2`) that contains the date at which a measurement has been taken. If the date was not recorded, the CSV file contains the value `NA`, for missing data.

    Var1  Var2 
    10    2010/01/01
    20    NA
    30    2010/03/01

We would like to use the subset command to define a new data frame `new_DF` such that it only contains rows that have an `NA&#39;` value from the column (`VaR2`). In the example given, only Row 2 will be contained in the new `DF`.

The command
```r
new_DF&lt;-subset(DF, DF$Var2==&quot;NA&quot;) 
```
does not work, the resulting data frame has no row entries.

If in the original CSV file the Value `NA` are exchanged with  `NULL`, the same command produces the desired result: 
```r
new_DF &lt;- subset(DF, DF$Var2==&quot;NULL&quot;)
``` 

How can I get this method working, if for the character string the value `NA` is provided in the original CSV file? 

Subset of rows containing NA (missing) values in a chosen column of a data frame

I have a list in R some 10,000 elements long. Say I want to select only elements, 5, 7, and 9. I&#39;m not sure how I would do that without a for loop.


I want to do something like `mylist[[c(5,7,9]]` but that doesn&#39;t work. I&#39;ve also tried the `lapply` function but haven&#39;t been able to get that working either.


Select multiple elements from a list

When I subset a matrix to a single column, the result is of class numeric, not matrix (i.e. myMatrix[ , 5 ] to subset to the fifth column).  Is there a compact way to subset to a single column, maintain the matrix format, and maintain the row/column names without doing something complicated like:

    matrix( myMatrix[ , 5 ] , dimnames = list( rownames( myMatrix ) , colnames( myMatrix )[ 5 ] )

How to subset matrix to one column, maintain matrix data type, maintain row/column names?

I have data similar to this:

    dt &lt;- structure(list(fct = structure(c(1L, 2L, 3L, 4L, 3L, 4L, 1L, 2L, 3L, 1L, 2L, 3L, 2L, 3L, 4L), .Label = c(&quot;a&quot;, &quot;b&quot;, &quot;c&quot;, &quot;d&quot;), class = &quot;factor&quot;), X = c(2L, 4L, 3L, 2L, 5L, 4L, 7L, 2L, 9L, 1L, 4L, 2L, 5L, 4L, 2L)), .Names = c(&quot;fct&quot;, &quot;X&quot;), class = &quot;data.frame&quot;, row.names = c(NA, -15L))


I want to select rows from this data frame based on the values in the `fct` variable. For example, if I wish to select rows containing either &quot;a&quot; or &quot;c&quot; I can do this:

    dt[dt$fct == &#39;a&#39; | dt$fct == &#39;c&#39;, ]

which yields 

    1    a 2
    3    c 3
    5    c 5
    7    a 7
    9    c 9
    10   a 1
    12   c 2
    14   c 4
as expected. But my actual data is more complex and I actually want to select rows based on the values in a vector such as

    vc &lt;- c(&#39;a&#39;, &#39;c&#39;)

So I tried

    dt[dt$fct == vc, ]

but of course that doesn&#39;t work. I know I could code something to loop through the vector and pull out the rows needed and append them to a new dataframe, but I was hoping there was a more elegant way.


So how can I filter/subset my data based on the contents of the vector `vc`?

Select rows from a data frame based on values in a vector

Given a data frame &quot;foo&quot;, how can I select only those rows from &quot;foo&quot; where e.g. `foo$location = &quot;there&quot;`?

    foo = data.frame(location = c(&quot;here&quot;, &quot;there&quot;, &quot;here&quot;, &quot;there&quot;, &quot;where&quot;), x = 1:5, y = 6:10)
    foo
    #   location x  y
    # 1     here 1  6
    # 2    there 2  7
    # 3     here 3  8
    # 4    there 4  9
    # 5    where 5 10

Desired result, &quot;bar&quot;:

    #   location x y
    # 2    there 2 7
    # 4    there 4 9

Subset / filter rows in a data frame based on a condition in a column

I have a data frame, `str(data)` to show more about my data frame the result is the following: 

    &gt; str(data)
    &#39;data.frame&#39;:   153 obs. of  6 variables:
    $ Ozone  : int  41 36 12 18 NA 28 23 19 8 NA ...
    $ Solar.R: int  190 118 149 313 NA NA 299 99 19 194 ...
    $ Wind   : num  7.4 8 12.6 11.5 14.3 14.9 8.6 13.8 20.1 8.6 ...
    $ Temp   : int  67 72 74 62 56 66 65 59 61 69 ...
    $ Month  : int  5 5 5 5 5 5 5 5 5 5 ...
    $ Day    : int  1 2 3 4 5 6 7 8 9 10 ...

However, for example, when I want to subset the amounts of `Ozone` above 14 I use the following code which gives me an error:

    &gt;  data[data$Ozone &gt; 14 ]

&gt; Error in `[.data.frame`(data, data$Ozone &gt; 14) : undefined columns selected

Undefined columns selected when subsetting data frame

Say I have a data.frame:

    df &lt;- data.frame(A=c(10,20,30),B=c(11,22,33), C=c(111,222,333))
      A  B  C
    1 10 11 111
    2 20 22 222
    3 30 33 333

If I select two (or more) columns I get a data.frame:

    x &lt;- df[,1:2]
       A  B
     1 10 11
     2 20 22
     3 30 33

This is what I want. However, if I select only one column I get a numeric vector:

    x &lt;- df[,1]
    [1] 1 2 3

I have tried to use as.data.frame(), which does not change the results for two or more columns. it does return a data.frame in the case of one column, but does not retain the column name:

    x &lt;- as.data.frame(df[,1])
         df[, 1]
    1       1
    2       2
    3       3

I don&#39;t understand why it behaves like this. In my mind it should not make a difference if I extract one or two or ten columns. IT should either always return a vector (or matrix) or always return a data.frame (with the correct names). what am I missing? thanks!

Note: This is not a duplicate of the question about matrices, as matrix and data.frame are fundamentally different data types in R, and can work differently with dplyr. There are several answers that work with data.frame but not matrix. 

How do I extract a single column from a data.frame as a data.frame?

Is there a way for me to subset data based on column names starting with a particular string? I have some columns which are like `ABC_1 ABC_2 ABC_3` and some like `XYZ_1, XYZ_2,XYZ_3` let&#39;s say.

How can I subset my `df` based only on columns containing the above portions of text (lets say, `ABC` or `XYZ`)? I can use indices, but the columns are too scattered in data and it becomes too much of hard coding.

Also, I want to only include rows from each of these columns where any of their value is `&gt;0` so if either of the `6` columns above has a `1` in the row, it makes a cut into my final data frame.

Subset data to contain only columns whose names match a condition

I have a set of objects in a Vector from which I&#39;d like to select a random subset (e.g. 100 items coming back; pick 5 randomly). In my first (very hasty) pass I did an extremely simple and perhaps overly clever solution:

    Vector itemsVector = getItems();
    
    Collections.shuffle(itemsVector);
    itemsVector.setSize(5);

While this has the advantage of being nice and simple, I suspect it&#39;s not going to scale very well, i.e. Collections.shuffle() must be O(n) at least. My less clever alternative is

    Vector itemsVector = getItems();
    
    Random rand = new Random(System.currentTimeMillis()); // would make this static to the class    
        
    List subsetList = new ArrayList(5);
    for (int i = 0; i &lt; 5; i++) {
         // be sure to use Vector.remove() or you may get the same item twice
         subsetList.add(itemsVector.remove(rand.nextInt(itemsVector.size())));
    }

Any suggestions on better ways to draw out a random subset from a Collection?

best way to pick a random subset from a collection?

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 problem to plot a subset of a data frame with ggplot2. My df is like:

```r
df = data.frame(ID = c(&#39;P1&#39;, &#39;P1&#39;, &#39;P2&#39;, &#39;P2&#39;, &#39;P3&#39;, &#39;P3&#39;),
                Value1 = c(100, 120, 300, 400, 130, 140),
                Value2 = c(12, 13, 11, 16, 15, 12))
```

How can I now plot `Value1` vs `Value2` only for `ID`s `&#39;P1&#39;` and `&#39;P3&#39;`?
For example I tried:

```r
ggplot(subset(df,ID==&quot;P1 &amp; P3&quot;) +
  geom_line(aes(Value1, Value2, group=ID, colour=ID)))
```

but I always receive an error.

Subset and ggplot2

I am transitioning from R to Python. I just began using Pandas. I have an R code that subsets nicely:

    k1 &lt;- subset(data, Product = p.id &amp; Month &lt; mn &amp; Year == yr, select = c(Time, Product))


Now, I want to do similar stuff in Python. this is what I have got so far:

    import pandas as pd
    data = pd.read_csv(&quot;../data/monthly_prod_sales.csv&quot;)


    #first, index the dataset by Product. And, get all that matches a given &#39;p.id&#39; and time.
     data.set_index(&#39;Product&#39;)
     k = data.ix[[p.id, &#39;Time&#39;]]
    
    # then, index this subset with Time and do more subsetting..

I am beginning to feel that I am doing this the wrong way. perhaps, there is an elegant solution. Can anyone help? I need to extract month and year from the timestamp I have and do subsetting. Perhaps there is a one-liner that will accomplish all this:

    k1 &lt;- subset(data, Product = p.id &amp; Time &gt;= start_time &amp; Time &lt; end_time, select = c(Time, Product))



thanks.

 

subsetting a Python DataFrame

&gt; **Possible Duplicate:**  
&gt; [Standard way to remove multiple elements from a dataframe](https://stackoverflow.com/questions/7494848/standard-way-to-remove-multiple-elements-from-a-dataframe)  

&lt;!-- End of automatically inserted text --&gt;

I know in R that if you are searching for a subset of another group or matching based on id you&#39;d use something like

    subset(df1, df1$id %in% idNums1)

My question is how to do the opposite or choose items NOT matching a vector of ids.

I tried using `!` but get the error message

    subset(df1, df1$id !%in% idNums1)

I think my backup is to do sometime like this:

    matches &lt;- subset(df1, df1$id %in% idNums1)
    nonMatches &lt;- df1[(-matches[,1]),]

but I&#39;m hoping there&#39;s something a bit more efficient.


R Not in subset

I&#39;m familiar with being able to extract columns from an R data frame (or matrix) like so:

    df.2 &lt;- df[, c(&quot;name1&quot;, &quot;name2&quot;, &quot;name3&quot;)]

But can one use a `!` or other tool to select *all but those listed columns*?

For background, I have a data frame with quite a few column vectors and I&#39;d like to avoid:

- Typing out the majority of the names when I could just remove a minority
- Using the much shorter `df.2 &lt;- df[, c(1,3,5)]` because when my .csv file changes, my code goes to heck since the numbering isn&#39;t the same anymore. I&#39;m new to R and think I&#39;ve learned the hard way not to use number vectors for larger df&#39;s that might change.

I tried:

    df.2 &lt;- df[, !c(&quot;name1&quot;, &quot;name2&quot;, &quot;name3&quot;)]
    df.2 &lt;- df[, !=c(&quot;name1&quot;, &quot;name2&quot;, &quot;name3&quot;)]

And just as I was typing this, found out that this works:

    df.2 &lt;- df[, !names(df) %in% c(&quot;name1&quot;, &quot;name2&quot;, &quot;name3&quot;)]

Is there a better way than this last one?

Selecting columns in R data frame based on those *not* in a vector

I need to get all possible subsets of an array.

Say I have this:

    [1, 2, 3]

How do I get this?

    [], [1], [2], [3], [1, 2], [2, 3], [1, 3], [1, 2, 3]

I am interested in all subsets. For subsets of specific length, refer to the following questions:

  * Finding subsets of size n: [1][1], [2][2]
  * Finding subsets of size &gt; 1: [1][3]


  [1]: https://stackoverflow.com/questions/5752002/find-all-possible-subset-combos-in-an-array
  [2]: https://stackoverflow.com/questions/37892738/generate-subsets-of-length-n
  [3]: https://stackoverflow.com/questions/24556889/subsets-of-an-arrays-with-n-elements-javascript

How to find all subsets of a set in JavaScript? (Powerset of array)

Is it possible to get a matrix column by name from a matrix?

I tried various approaches such as `myMatrix[&quot;test&quot;, ]` but nothing seems to work.

Extract matrix column values by matrix column name

I have two data sets that are supposed to be the same size but aren&#39;t. I need to trim the values from A that are not in B and vice versa in order to eliminate noise from a graph that&#39;s going into a report. (Don&#39;t worry, this data isn&#39;t being permanently deleted!)

I have read the following:

 - https://stackoverflow.com/questions/12208090/selecting-columns-in-r-data-frame-based-on-those-not-in-a-vector
 - http://www.ats.ucla.edu/stat/r/faq/subset_R.htm
 - https://stackoverflow.com/questions/4935479/how-to-combine-multiple-conditions-to-subset-a-data-frame-using-or

But I&#39;m still not able to get this to work right. Here&#39;s my code:

    bg2011missingFromBeg &lt;- setdiff(x=eg2011$ID, y=bg2011$ID)
    #attempt 1
    eg2011cleaned &lt;- subset(eg2011, ID != bg2011missingFromBeg)
    #attempt 2
    eg2011cleaned &lt;- eg2011[!eg2011$ID %in% bg2011missingFromBeg]

The first try just eliminates the first value in the resulting setdiff vector. The second try yields and unwieldy error:

    Error in `[.data.frame`(eg2012, !eg2012$ID %in% bg2012missingFromBeg) 
    :  undefined columns selected


Subset rows in a data frame based on a vector of values

I&#39;m a bit confused between subarray, subsequence &amp; subset

if I have `{1,2,3,4}`

then 

subsequence can be `{1,2,4}` OR `{2,4}` etc. So basically I can omit some elements but keep the order. 
    
subarray would be( say subarray of size 3) 
    
    {1,2,3}
    {2,3,4} 
    
Then what would be the subset? 

I&#39;m  bit confused between these 3.  

All Subset Solutions on Gang of Coders

Total of 28 Subset Solutions