在R中合并数据帧的多个重复行 [英] Consolidating multiple duplicated rows of a dataframe in R

问题描述

我有一个由六列组成的大型数据集，第一列是与剩余五列中的比率值相匹配的标识符列表：

I have a large dataset comprised of six columns, the first column being a list of Identifiers that match ratios values across the remaining five columns:

    Identifier cd_log.ratios cs_log.ratios me_log.ratios pn_log.ratios sm_log.ratios
          A2ICC5     0.3784142            NA            NA            NA            NA
          A2ICC5            NA    -0.4910396            NA            NA            NA
          A2ICC5            NA            NA    -0.1755617            NA            NA
          A2ICC5            NA            NA            NA            NA     0.2279259
          A2ICC8     0.3045490            NA            NA            NA            NA
          A2ICC8            NA     0.2045638            NA            NA            NA

注意前四行，五个比例列中的四个共享一个重复的标识符。如何整合我的数据框以删除重复的标识符并将比例转移到一行？输出将如下所示：

Notice for the first four rows, four of the five ratio columns share a duplicated Identifier. How can I consolidate my dataframe to remove duplicated identifiers and shift the ratios to one row? The output would look something like this:

Identifier  cd_log.ratios   cs_log.ratios   me_log.ratios   pn_log.ratios   sm_log.ratios
A2ICC5      0.3784142      -0.4910396      -0.1755617              NA       0.2279259
A2ICC8       0.304549       0.2045638              NA              NA              NA

谢谢你提前！

推荐答案

df = read.table(text = '   Identifier cd_log.ratios cs_log.ratios me_log.ratios pn_log.ratios sm_log.ratios
          A2ICC5     0.3784142            NA            NA            NA            NA
          A2ICC5            NA    -0.4910396            NA            NA            NA
          A2ICC5            NA            NA    -0.1755617            NA            NA
          A2ICC5            NA            NA            NA            NA     0.2279259
          A2ICC8     0.3045490            NA            NA            NA            NA
          A2ICC8            NA     0.2045638            NA            NA            NA', header = T)

library(data.table)
dt = data.table(df)

dt[, lapply(.SD, na.omit), by = Identifier]
#   Identifier cd_log.ratios cs_log.ratios me_log.ratios pn_log.ratios sm_log.ratios
#1:     A2ICC5     0.3784142    -0.4910396    -0.1755617            NA     0.2279259
#2:     A2ICC8     0.3045490     0.2045638            NA            NA            NA

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