# Re: [R] median of grouped data

From: jim holtman <jholtman_at_gmail.com>
Date: Fri, 27 Jun 2008 22:25:31 -0400

> # split the dataframe by the grouping (z was your sample data)
> z.s <- split(z, z[[1]])
> # calculate the median
> (ans <- lapply(z.s, function(.grp) apply(.grp[,7:9], 2, median)))
\$HOR006_3
TC.15_comps IC.16_comps SOC.17_comps
10.549669 4.224790 7.012470

\$HOR006_4
TC.15_comps IC.16_comps SOC.17_comps
14.428948 7.557801 6.568626

\$HOR006_5
TC.15_comps IC.16_comps SOC.17_comps
22.378523 13.666364 7.290354

```         TC.15_comps IC.16_comps SOC.17_comps
HOR006_3    10.54967    4.224790     7.012470
HOR006_4    14.42895    7.557801     6.568626
HOR006_5    22.37852   13.666364     7.290354

```

On Fri, Jun 27, 2008 at 7:19 PM, Bricklemyer, Ross S <rsb_at_wsu.edu> wrote:
> I am having difficulty calculating the median of grouped data. I have 8 to 10 repeated measures per sample and I have successfully used the following code to calculate the average for each sample.
>
> libs.norm.preds.median[,7:9]<-apply(libs.norm.preds.median[,7:9],MARGIN=2, FUN=ave,libs.norm.preds.median[,1])
>
> I then use the unique function to collapse the data into one line per sample.
>
> I would also like to calculate the median, standard error, and coefficient of variation as well. I have not been able to get median to work properly. I have tried this and variants:
>
> libs.norm.preds.median[,7:9]<-apply(libs.norm.preds.median[,7:9],MARGIN=2, FUN=median,libs.norm.preds.median[,1])
>
>
> I receive the following error:
> Warning messages:
> 1: In if (na.rm) x <- x[!is.na(x)] else if (any(is.na(x))) return(x[FALSE][NA]) :the condition has length > 1 and only the first element will be used
>
> Here is a subset of my data (tab delimited):
>
> samp.id core field TC IC SOC TC.15 comps IC.16 comps SOC.17 comps TC.15 comps IC.16 comps SOC.17 comps
> HOR006_3 HOR006 HOR 7.157 0 7.157 8.008273281 0.786161341 6.402343153 8.008273281 0.786161341 6.402343153
> HOR006_3 HOR006 HOR 7.157 0 7.157 6.258510623 -1.117567268 6.987405984 6.258510623 0 6.987405984
> HOR006_3 HOR006 HOR 7.157 0 7.157 14.21306811 7.968072165 6.818917226 14.21306811 7.968072165 6.818917226
> HOR006_3 HOR006 HOR 7.157 0 7.157 17.73301788 9.017994045 9.035508792 17.73301788 9.017994045 9.035508792
> HOR006_3 HOR006 HOR 7.157 0 7.157 12.54204929 6.285521186 6.052762372 12.54204929 6.285521186 6.052762372
> HOR006_3 HOR006 HOR 7.157 0 7.157 10.07603128 3.485872902 6.937777459 10.07603128 3.485872902 6.937777459
> HOR006_3 HOR006 HOR 7.157 0 7.157 11.02330763 4.963708049 7.03753441 11.02330763 4.963708049 7.03753441
> HOR006_3 HOR006 HOR 7.157 0 7.157 11.02330763 4.963708049 7.03753441 11.02330763 4.963708049 7.03753441
> HOR006_3 HOR006 HOR 7.157 0 7.157 9.249550001 1.92641169 7.675586354 9.249550001 1.92641169 7.675586354
> HOR006_3 HOR006 HOR 7.157 0 7.157 7.414208739 -0.020533568 7.057048733 7.414208739 0 7.057048733
> HOR006_4 HOR006 HOR 11.73 0 11.73 14.42894814 8.998403641 5.752994239 14.42894814 8.998403641 5.752994239
> HOR006_4 HOR006 HOR 11.73 0 11.73 13.65284466 6.757373476 6.388413921 13.65284466 6.757373476 6.388413921
> HOR006_4 HOR006 HOR 11.73 0 11.73 10.72185703 5.053095924 6.016783029 10.72185703 5.053095924 6.016783029
> HOR006_4 HOR006 HOR 11.73 0 11.73 14.68382689 7.557801473 6.667911142 14.68382689 7.557801473 6.667911142
> HOR006_4 HOR006 HOR 11.73 0 11.73 2.287381003 -3.074174656 6.654986023 2.287381003 0 6.654986023
> HOR006_4 HOR006 HOR 11.73 0 11.73 14.57145428 8.812845515 6.625453309 14.57145428 8.812845515 6.625453309
> HOR006_4 HOR006 HOR 11.73 0 11.73 21.12964238 13.27394496 6.568626499 21.12964238 13.27394496 6.568626499
> HOR006_4 HOR006 HOR 11.73 0 11.73 19.46136803 8.03100103 6.910126723 19.46136803 8.03100103 6.910126723
> HOR006_4 HOR006 HOR 11.73 0 11.73 13.16591198 4.738398449 6.051036242 13.16591198 4.738398449 6.051036242
> HOR006_5 HOR006 HOR 20.339 14.383 5.956 24.17001811 15.44634892 8.095868636 24.17001811 15.44634892 8.095868636
> HOR006_5 HOR006 HOR 20.339 14.383 5.956 19.17125764 12.28559645 7.468646662 19.17125764 12.28559645 7.468646662
> HOR006_5 HOR006 HOR 20.339 14.383 5.956 20.18713584 13.12584843 6.985808635 20.18713584 13.12584843 6.985808635
> HOR006_5 HOR006 HOR 20.339 14.383 5.956 25.58402927 18.23958469 6.960777883 25.58402927 18.23958469 6.960777883
> HOR006_5 HOR006 HOR 20.339 14.383 5.956 24.04109959 16.32371239 7.12821025 24.04109959 16.32371239 7.12821025
> HOR006_5 HOR006 HOR 20.339 14.383 5.956 19.809507 12.28987767 7.290354063 19.809507 12.28987767 7.290354063
> HOR006_5 HOR006 HOR 20.339 14.383 5.956 22.37852335 13.66636406 7.814588276 22.37852335 13.66636406 7.814588276
> HOR006_5 HOR006 HOR 20.339 14.383 5.956 20.67374067 12.99877903 6.997267952 20.67374067 12.99877903 6.997267952
> HOR006_5 HOR006 HOR 20.339 14.383 5.956 24.69721989 16.10787468 8.381673118 24.69721989 16.10787468 8.381673118
>
>
> *******************************************************************
> Ross Bricklemyer
> Dept. of Crop and Soil Sciences
> Washington State University
> 251 Johnson Hall
> PO Box 646420
> Pullman, WA 99164-6420
> Work: 509.335.3661
> Cell/Home: 406.570.8576
> Fax: 509.335.8674
> Email: rsb_at_wsu.edu
>
>
>
> ______________________________________________
> R-help_at_r-project.org mailing list
> https://stat.ethz.ch/mailman/listinfo/r-help
> and provide commented, minimal, self-contained, reproducible code.
>

```--
Jim Holtman
Cincinnati, OH
+1 513 646 9390

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