[R] fast way to find most common value across columns dataframe

[Luigi Marongiu]

Thank you. The problem was not finding the mode but applying it the R
way (I have the tendency to loop into each line of the dataframes,
which I believe is NOT the R way).
I'll try them.
Best regards
Luigi

On Sat, Oct 31, 2020 at 5:40 PM Bert Gunter <bgunter.4567 using gmail.com> wrote:
>
> As usual, a web search ("find statistical mode in R") brought up something that is possibly useful -- Did you try this before posting? If not, please do so in future and let us know what your results were if you subsequently post here.
>
> Here's what SO suggested:
>
> Mode <- function(x) {
>    ux <- unique(x)
>    ux[which.max(tabulate(match(x, ux)))]
> }
>
> # ergo:
> apply(as.matrix(df),1,Mode)
>
> Note that all the functionality in Mode is via .Internal functions.  So you can determine whether this is faster than Jim's code for your use case, but I'm pretty sure it will be faster than yours. However, note that this gives only the value of the *first* mode if there is more than one, while Jim's code alerts you to multiple modes.
>
> 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 Sat, Oct 31, 2020 at 2:29 AM Jim Lemon <drjimlemon using gmail.com> wrote:
>>
>> Hi Luigi,
>> If I understand your request:
>>
>> library(prettyR)
>> apply(as.matrix(df),1,Mode)
>> [1] "C"       "B"       "D"       ">1 mode" ">1 mode" ">1 mode" "D"
>> [8] "C"       "B"       ">1 mode"
>>
>> Jim
>>
>> On Sat, Oct 31, 2020 at 7:56 PM Luigi Marongiu <marongiu.luigi using gmail.com>
>> wrote:
>>
>> > Hello,
>> > I have a large dataframe (1 000 000 rows, 1000 columns) where the
>> > columns contain a character. I would like to determine the most common
>> > character for each row.
>> > In the example below, I can parse one row at the time and find the
>> > most common character (apart for ties...). But I think this will be
>> > very slow and memory consuming.
>> > Is there a way to run it more efficiently?
>> > Thank you
>> >
>> > ```
>> > V = c("A", "B", "C", "D")
>> > df = data.frame(n = 1:10,
>> >        col_01 = sample(V, 10, replace = TRUE, prob = NULL),
>> >        col_02 = sample(V, 10, replace = TRUE, prob = NULL),
>> >        col_03 = sample(V, 10, replace = TRUE, prob = NULL),
>> >        col_04 = sample(V, 10, replace = TRUE, prob = NULL),
>> >        col_05 = sample(V, 10, replace = TRUE, prob = NULL),
>> >        stringsAsFactors = FALSE)
>> >
>> > q = vector()
>> > for(i in 1:nrow(df)) {
>> >   x = as.vector(t(df[i,2:ncol(df)]))
>> >   q[i] =    names(which.max(table(x)))
>> > }
>> > df$most = q
>> > ```
>> >
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>> >
>>
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>>
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>> and provide commented, minimal, self-contained, reproducible code.



-- 
Best regards,
Luigi