Matti -
Since you are asking about looping through a column, not looping across
columns, it is simply the following:
# Note: data.frame() turns strings into factors by default.
myDF <- data.frame(type = c("a", "j", "a", "a", "j"),
weight = c(12.3, 6.8, 10.5, NA, "5.5"))
myDF$type # ... is a vector of factors
for(type in myDF$type) {
print(type)
}
# or (less explicit in the code and will break if the order of columns
# ever changes):
for(type in myDF[ , 1]) {
print(type)
}
# In a matrix, all elemnts have to be of the same type. Let's make a
# matrix of characters:
myMat <- matrix(cbind(as.character(myDF$type),
c("red", "green", "red", "red", "green")),
ncol = 2)
for(type in myMat[ , 1]) {
print(type)
}
As others have remarked, for added efficiency with large datasets we often use
functions from the apply() family, rather than for-loops.
I hope this helps,
Boris
PS: don't call your data frames "df" since df() is a function and this may make
your code hard to read.
> On Nov 6, 2017, at 2:49 PM, Rui Barradas <[email protected]> wrote:
>
> Hello,
>
> If you want to loop through the columns of a data.frame you can do
>
> for(i in names(df)){
> [code]
> }
>
> Another way would be
>
> lapply(names(df), function(somecol) class(df[[somecol]]))
>
> where class(df[[somecol]]) is just an example, you would use whatever fits
> your needs.
>
> When you say that the column in question holds "levels" do you mean it's a
> factor? (factors are R's categorical variables.)
>
> Hope this helps,
>
> Rui Barradas
>
>
> Em 06-11-2017 19:26, Matti Viljamaa escreveu:
>> It’s sometimes faster to ask from someone who has already learnt the syntax.
>> In this case one has to do e.g.
>>
>> names(data$somecol)
>>
>> To get the collection and then iteration through it is almost like in Python:
>>
>> for(i in names(data$somecol)) {
>> # do something
>> }
>>
>>> Bert Gunter <[email protected]> kirjoitti 6.11.2017 kello 19.55:
>>>
>>> Time to go through a tutorial or two! -- This forum cannot replace such
>>> self study.
>>>
>>> Your query evidences some basic confusion, but ?tapply or the equivalent
>>> lapply(split(...)) construct are most likely relevant.
>>>
>>> Cheers,
>>> Bert
>>>
>>>
>>>
>>> Bert Gunter
>>>
>>> "The trouble with having an open mind is that people keep coming along and
>>> sticking things into it."
>>> -- Opus (aka Berkeley Breathed in his "Bloom County" comic strip )
>>>
>>> On Mon, Nov 6, 2017 at 9:40 AM, mviljamaa <[email protected]
>>> <mailto:[email protected]>> wrote:
>>> How can I do a for loop that does to a data.frame column what:
>>>
>>> for x in xs:
>>>
>>> does in Python?
>>>
>>> Obviously the data.frame column in question holds "levels". What if the
>>> data.frame is in matrix form?
>>>
>>> BR, Matti
>>>
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>>
>>
>> [[alternative HTML version deleted]]
>>
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>> and provide commented, minimal, self-contained, reproducible code.
>>
>
> ______________________________________________
> [email protected] mailing list -- To UNSUBSCRIBE and more, see
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> and provide commented, minimal, self-contained, reproducible code.
______________________________________________
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