将不等数组的列转换为 R 中的单个值列

本文介绍了将不等数组的列转换为 R 中的单个值列的处理方法，对大家解决问题具有一定的参考价值，需要的朋友们下面随着小编来一起学习吧！ 问题描述

作为此之后的下一步 previous question，假设有多个长度不同的数组列.例如:

As a next step after this previous question, assume that there are multiple columns of arrays that do not have the same length. For example:

Col_ACol_BCol_C

[0.1,0.5,0.7]	[1.54E12, 1.54E12, 1.54E12]	[1, 3, 4, 5}

我如何采用这种格式并将其重新格式化为以下格式，在适当的情况下为 Col_A 和 Col_b 提供 NA:

How can I take this format and reformat it to the following giving NAs to Col_A and Col_b where appropriate:

Col_ACol_BCol_C

0.1	1.54E12	1
0.5	1.54E12	3
0.7	1.54E12	4
不适用	不适用	5

此代码适用于所有数组相等的情况，但如果数组不相等则会抛出错误:

This code works for when all arrays are equal but will throw an error if the arrays are not equal:

library(dplyr) library(stringr) library(tidyr) df %>% mutate(across(everything(), str_extract_all, "(?<=\\[)[^]]+")) %>% unnest(c(NDVIs, dates)) %>% separate_rows(c(NDVIs, dates), sep=",\\s+", convert = TRUE)

推荐答案

我们可以使用 splitstackshape

library(splitstackshape) library(data.table) cSplit(setDT(df)[, lapply(.SD, gsub, pattern = "[][}]", replacement = "")], names(df), sep=",", fixed = FALSE, "long") # Col_A Col_B Col_C #1: 0.1 1.54e+12 1 #2: 0.5 1.54e+12 3 #3: 0.7 1.54e+12 4 #4: NA NA 5

数据

df <- structure(list(Col_A = "[0.1,0.5,0.7]", Col_B = "[1.54E12, 1.54E12, 1.54E12]", Col_C = "[1, 3, 4, 5}"), class = "data.frame", row.names = c(NA, -1L))