合并几个不同列长的数据帧并操作列

问题描述

| 我正在使用9个具有不同数据的文件（每个组织数据中的蛋白质）。每个文件代表一个不同的组织，并具有蛋白质表达值（以数字表示）。我正在尝试将数据合并到一个data.frame中。我用了

read.delim(\"fileName.txt\")  

对于所有文件。之后，我为所有数据框使用了一个列表

l <- list(data.frame1,..etc)

然后我使用了plyr库和

do.call(rbind.fill,l)

。 我的问题： 1）我希望遍历9个数据的列表。框架在其中找到唯一的数据并将其绘制为直方图。如果我发现多个名称相同但组织不同的条目，则应将其添加到直方图中，每个条目都应位于正确的组织标签上方。那就是-我转到列表中的第一个data.frame，从中取出第一个条目，搜索是否在其他data.frame之一中找到了该条目，然后将其添加到直方图中。 直方图在x轴上有9个组织，y轴是我文件中的值。我无法弄清楚如何获取直方图（和代码）以适当地更改名称以及如何在正确的位置显示条形图。 此外，我不知道如何构建轴以获取每个条下的组织名称。 我有一些基本的代码不能满足我的需求：

i=1

for( val in list2[1:9] )
{
    if( val appears in one of the other data.frames)
           plot a bar over the correct tissue.

    hist(val[i,8],breaks=11,col=\"blue\",density=13,angle=45,labels=c(\"Lung\",\"ErythroleukemicCellLine\",\"TCells\",\"Blood\",\"liver\",\"BLimpho\",\"pancreas\",\"prostate\",\"Bladder\"),main=fileName[i,1])
    dev.new() #each hist in a new window
    i = i + 1

}

谢谢 意格 这是代码输出结尾的几行： 用read.delim（\“ nameOfFile.txt \”）读取文件后

 dput(BloodErythroleukemicCellLineFile)
 \"Tax_Id=9606 Gene_Symbol=ZNF589 Uncharacterized protein\",\"Tax_Id=9606 Gene_Symbol=ZNF598 Isoform 1 of Zinc finger protein 598\",\"Tax_Id=9606 Gene_Symbol=ZNF609 Zinc finger protein 609\",\"Tax_Id=9606 Gene_Symbol=ZNF610 Isoform 1 of Zinc finger protein 610\",\"Tax_Id=9606 Gene_Symbol=ZNF613 Isoform 1 of Zinc finger protein 613\",\"Tax_Id=9606 Gene_Symbol=ZNF614 Zinc finger protein 614\",\"Tax_Id=9606 Gene_Symbol=ZNF622 Zinc finger protein 622\",\"Tax_Id=9606 Gene_Symbol=ZNF625 Zinc finger protein 625\",\"Tax_Id=9606 Gene_Symbol=ZNF638 Isoform 1 of Zinc finger protein 638\",\"Tax_Id=9606 Gene_Symbol=ZNF638 Isoform 4 of Zinc finger protein 638\",\"Tax_Id=9606 Gene_Symbol=ZNF646 Isoform 1 of Zinc finger protein 646\",\"Tax_Id=9606 Gene_Symbol=ZNF658B Zinc finger protein 658B\",\"Tax_Id=9606 Gene_Symbol=ZNF667 Zinc finger protein 667,isoform CRA_a\",\"Tax_Id=9606 Gene_Symbol=ZNF671 Zinc finger protein 671\",\"Tax_Id=9606 Gene_Symbol=ZNF687 Isoform 1 of Zinc finger protein 687\",\"Tax_Id=9606 Gene_Symbol=ZNF687 Zinc finger protein 687\",\"Tax_Id=9606 Gene_Symbol=ZNF691 cDNA FLJ56317,highly similar to Zinc finger protein 691\",\"Tax_Id=9606 Gene_Symbol=ZNF700 Zinc finger protein 700\",\"Tax_Id=9606 Gene_Symbol=ZNF714 Isoform 1 of Zinc finger protein 714\",\"Tax_Id=9606 Gene_Symbol=ZNF72 Zinc finger protein 72 (Fragment)\",\"Tax_Id=9606 Gene_Symbol=ZNF721 zinc finger protein 721\",\"Tax_Id=9606 Gene_Symbol=ZNF76 Isoform 2 of Zinc finger protein 76\",\"Tax_Id=9606 Gene_Symbol=ZNF782 Zinc finger protein 782\",\"Tax_Id=9606 Gene_Symbol=ZNF787 Zinc finger protein 787\",\"Tax_Id=9606 Gene_Symbol=ZNF800 Zinc finger protein 800\",\"Tax_Id=9606 Gene_Symbol=ZNF827 21 kDa protein\",\"Tax_Id=9606 Gene_Symbol=ZNF828 Zinc finger protein 828\",\"Tax_Id=9606 Gene_Symbol=ZNF837 Zinc finger protein 837\",\"Tax_Id=9606 Gene_Symbol=ZNF878 Zinc finger protein 878\",\"Tax_Id=9606 Gene_Symbol=ZNF891 Zinc finger protein 891\",\"Tax_Id=9606 Gene_Symbol=ZNHIT2 Zinc finger HIT domain-containing protein 2\",\"Tax_Id=9606 Gene_Symbol=ZP2 Zona pellucida sperm-binding protein 2\",\"Tax_Id=9606 Gene_Symbol=ZRANB2 Isoform 1 of Zinc finger Ran-binding domain-containing protein 2\",\"Tax_Id=9606 Gene_Symbol=ZSWIM6 Zinc finger SWIM domain-containing protein 6\",\"Tax_Id=9606 Gene_Symbol=ZUFSP 32 kDa protein\",\"Tax_Id=9606 Gene_Symbol=ZW10 Centromere/kinetochore protein zw10 homolog\",\"Tax_Id=9606 Gene_Symbol=ZWINT ZW10 interactor\",\"Tax_Id=9606 Gene_Symbol=ZYG11B Isoform 1 of Protein zyg-11 homolog B\",\"Tax_Id=9606 Gene_Symbol=ZYX cDNA FLJ53160,highly similar to Zyxin\",\"Tax_Id=9606 Gene_Symbol=ZYX Uncharacterized protein\",\"Tax_Id=9606 Gene_Symbol=ZYX Zyxin\"
    ),class = \"factor\")),.Names = c(\"proteinIdentifier\",\"protein\",\"spectra\",\"unique_peptides\",\"fdr\",\"local_fdr\",\"sequence_coverage\",\"expression_value\",\"expression_percentile\",\"organism\",\"tissue\",\"localization\",\"condition\",\"experiment\",\"annotation\"),class = \"data.frame\",row.names = c(NA,-4802L))

它在控制台中要长得多     

解决方法

在您的问题中找到问题的核心并不容易。 为了使用一个或多个公共字段合并数据帧，可以使用merge（）函数，例如：

merge(dataframe1,dataframe2,by=c(\'column_name1\',\'column_name2\'),suffixes=c(\'.from_df1\',\'.from_df2\'))

如果要选择行或列，可以这样做：

dataframe1[dataframe$column1 == \'some_value\",c(\'col1\',\'col2\')]

等等... 这对您有帮助吗？