根据另一个数据框/列表在数据框中的列子集 [英] subset a column in data frame based on another data frame/list

问题描述

我有以下table1，它是由6列和8083行组成的数据帧.在下面，我显示此table1的标题:

I have the following table1 which is a data frame composed of 6 columns and 8083 rows. Below I am displaying the head of this table1:

|gene ID        |   prom_65|   prom_66|  amast_69|  amast_70|   p_value|
|:--------------|---------:|---------:|---------:|---------:|---------:|
|LdBPK_321470.1 |   24.7361|   25.2550|   31.2974|   45.4209| 0.2997430|
|LdBPK_251900.1 |  107.3580|  112.9870|   77.4182|   86.3211| 0.0367792|
|LdBPK_331430.1 |   72.0639|   86.1486|   68.5747|   77.8383| 0.2469355|
|LdBPK_100640.1 |   43.8766|   53.4004|   34.0255|   38.4038| 0.1299948|
|LdBPK_330360.1 | 2382.8700| 1871.9300| 2013.4200| 2482.0600| 0.8466225|
|LdBPK_090870.1 |   49.6488|   53.7134|   59.1175|   66.0931| 0.0843242|

我有另一个数据框，称为accessions40，它是510个基因ID的列表.它是table1的第一列的子集，即它的所有值(510)都包含在table1的第一列(8083)中. accessions40的标题显示在下面:

I have another data frame, called accessions40 which is a list of 510 gene IDs. It is a subset of the first column of table1 i.e. all of its values (510) are contained in the first column of table1 (8083). The head of accessions40 is displayed below:

|V1             |
|:--------------|
|LdBPK_330360.1 |
|LdBPK_283000.1 |
|LdBPK_360210.1 |
|LdBPK_261550.1 |
|LdBPK_367320.1 |
|LdBPK_361420.1 |

我想要做的是:我想生成一个新的table2，它在第一列(基因ID)下仅包含accessions40中存在的值以及table1.换句话说，我想基于accessions40的值对table1的第一列进行子集化.

What I want to do is the following: I want to produce a new table2 which contains under the first column (gene ID) only the values present in accessions40 and the corresponding values from the other five columns from table1. In other words, I want to subset the first column of my table1 based on the values of accessions40.

推荐答案

我们可以使用%in%来获取逻辑向量，并基于此来获取'table1'的行.

We can use %in% to get a logical vector and subset the rows of the 'table1' based on that.

subset(table1, gene_ID %in% accessions40$V1)

---

更好的选择是data.table

library(data.table)
setDT(table1)[gene_ID %chin% accessions40$V1]

或使用dplyr

library(dplyr)
table1 %>%
      filter(gene_ID %in% accessions40$V1)

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