问题描述
我假设已经多次询问了这个问题，但是我找不到合适的词来找到可行的解决方案。
I assume this has been asked multiple times but I couldn't find the proper words to find a workable solution.
我如何 Spread（）一个基于多个键的多个值的数据帧？
How can I spread() a data frame based on multiple keys for multiple values?
一个简化的例子（我有更多的列可以展开，但是仅两个键：给定度量的 Id 和 time 点）我正在使用的数据如下所示：
A simplified (I have many more columns to spread, but on only two keys: Id and time point of a given measurement) data I'm working with looks like this:
df <- data.frame(id = rep(seq(1:10),3),
time = rep(1:3, each=10),
x = rnorm(n=30),
y = rnorm(n=30))
> head(df)
id time x y
1 1 1 -2.62671241 0.01669755
2 2 1 -1.69862885 0.24992634
3 3 1 1.01820778 -1.04754037
4 4 1 0.97561596 0.35216040
5 5 1 0.60367158 -0.78066767
6 6 1 -0.03761868 1.08173157
> tail(df)
id time x y
25 5 3 0.03621258 -1.1134368
26 6 3 -0.25900538 1.6009824
27 7 3 0.13996626 0.1359013
28 8 3 -0.60364935 1.5750232
29 9 3 0.89618748 0.0294315
30 10 3 0.14709567 0.5461084
我要做什么d希望拥有一个填充如下的数据框：
What i'd like to have is a dataframe populated like this:
每个 Id 列中的每一行，分别表示时间中的每个值和每个测量变量。
One row per Id columns for each value from the time and each measurement variable.
推荐答案
使用$ dcast 最好使用多个值变量进行重塑或 reshape 从 base R 开始。
Reshaping with multiple value variables can best be done with dcast from data.table or reshape from base R.
library(data.table)
out <- dcast(setDT(df), id ~ paste0("time", time), value.var = c("x", "y"), sep = "")
out
# id xtime1 xtime2 xtime3 ytime1 ytime2 ytime3
# 1: 1 0.4334921 -0.5205570 -1.44364515 0.49288757 -1.26955148 -0.83344256
# 2: 2 0.4785870 0.9261711 0.68173681 1.24639813 0.91805332 0.34346260
# 3: 3 -1.2067665 1.7309593 0.04923993 1.28184341 -0.69435556 0.01609261
# 4: 4 0.5240518 0.7481787 0.07966677 -1.36408357 1.72636849 -0.45827205
# 5: 5 0.3733316 -0.3689391 -0.11879819 -0.03276689 0.91824437 2.18084692
# 6: 6 0.2363018 -0.2358572 0.73389984 -1.10946940 -1.05379502 -0.82691626
# 7: 7 -1.4979165 0.9026397 0.84666801 1.02138768 -0.01072588 0.08925716
# 8: 8 0.3428946 -0.2235349 -1.21684977 0.40549497 0.68937085 -0.15793111
# 9: 9 -1.1304688 -0.3901419 -0.10722222 -0.54206830 0.34134397 0.48504564
#10: 10 -0.5275251 -1.1328937 -0.68059800 1.38790593 0.93199593 -1.77498807
使用重塑我们可以做
# setDF(df) # in case df is a data.table now
reshape(df, idvar = "id", timevar = "time", direction = "wide")
这篇关于tidyr :: spread（）具有多个键和值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！