在R中将稀疏数据合并成单行的最佳方式是什么？ [英] What's the best way to collapse sparse data into single rows in R?

问题描述

我有一些我想在R中转换的交易数据。

I've got some transactional data that I'd like to transform in R.

df <- data.frame(
  customer_id = c(123, 123, 123),
  time = c(1, 2, 3),
  rec_type = c('contact', 'appointment', 'sale'),
  variable_1 = c('Yes', NA, NA),
  variable_2 = c(NA, 'No', NA),
  variable_3 = c(NA, NA, 'complete'))

数据如下所示：

customer_id     time    rec_type     variable_1     variable_2  variable_3
123             1        contact      Yes            NA          NA
123             2        appointment  NA             No          NA
123             3        sale         NA             NA          complete

本质上，我想通过删除具体时间和特定记录的数据来总结个人数据信息，然后将个人的唯一数据折叠成单行r独特的信息，所以它看起来像：

Essentially, I'm trying to summarise the data on individuals by removing the time-specific and record-specific information and then collapse the unique data on an individual into a single row for the unique information so it would look like:

customer_id   variable_1    variable_2    variable_3
123           Yes           No            complete

在R中执行此操作的最佳方法是什么？

What's the best way to do this in R?

推荐答案

Easy with data.table

Easy with data.table

library(data.table)

setDT(mydata)[,.(na.omit(variable_1),na.omit(variable_2),na.omit(variable_3)), by=.(customer_id)]

这篇关于在R中将稀疏数据合并成单行的最佳方式是什么？的文章就介绍到这了，希望我们推荐的答案对大家有所帮助，也希望大家多多支持IT屋！