Question

我有以下格式的数据框：

id | name               | logs                                  
---+--------------------+-----------------------------------------
84 |          "zibaroo" |                             "C47931038" 
12 | "fabien kelyarsky" | c("C47331040", "B19412225", "B18511449")
96 |     "mitra lutsko" |              c("F19712226", "A18311450")
34 |       "PaulSandoz" |                             "A47431044" 
65 |       "BeamVision" |                             "D47531045"

如您所见，列＃34;记录＆＃34;包括每个单元格中的字符串向量。

是否有一种有效的方法可以将数据帧转换为长格式（每行一次观察），而无需分离＆＃34;日志＆＃34;分成几列？

这很重要，因为数据集非常大，每人的日志数量似乎是任意的。

换句话说，我需要以下内容：

id | name               | log                                 
---+--------------------+------------
84 |          "zibaroo" | "C47931038" 
12 | "fabien kelyarsky" | "C47331040"
12 | "fabien kelyarsky" | "B19412225"
12 | "fabien kelyarsky" | "B18511449"
96 |     "mitra lutsko" | "F19712226"
96 |     "mitra lutsko" | "A18311450"
34 |       "PaulSandoz" | "A47431044" 
65 |       "BeamVision" | "D47531045"

以下是实际数据框的一部分的dput：

structure(list(id = 148:157, name = c("avihil1", "Niarfe", "doug henderson", 
"nick tan", "madisp", "woodbusy", "kevinhcross", "cylol", "andrewarrow", 
"gstavrev"), logs = list("Z47331572", "Z47031573", c("F47531574", 
"B195945", "D186871", "S192939", "S182865", "G19539045"), c("A47231575", 
"A190933", "C181859"), "F47431576", c("B47231577", "D193936", 
"Q184862"), "Y47331579", c("A47531580", "Z195944", "B185870"), 
"N47731581", "E47231582")), .Names = c("id", "name", "logs"
), row.names = 149:158, class = "data.frame")

Answer 1

使用listCol_l中的splitstackshape可能是一个很好的选择，因为列＆＃34;记录＆＃34; data.frame中的list

library(splitstackshape)
listCol_l(df, 'logs')

 #    id           name   logs_ul
 #1: 148        avihil1 Z47331572
 #2: 149         Niarfe Z47031573
 #3: 150 doug henderson F47531574
 #4: 150 doug henderson   B195945
 #5: 150 doug henderson   D186871
 #6: 150 doug henderson   S192939
 #7: 150 doug henderson   S182865
 #8: 150 doug henderson G19539045
 #9: 151       nick tan A47231575
#10: 151       nick tan   A190933
#11: 151       nick tan   C181859
#12: 152         madisp F47431576
#13: 153       woodbusy B47231577
#14: 153       woodbusy   D193936
#15: 153       woodbusy   Q184862
#16: 154    kevinhcross Y47331579
#17: 155          cylol A47531580
#18: 155          cylol   Z195944
#19: 155          cylol   B185870
#20: 156    andrewarrow N47731581
#21: 157       gstavrev E47231582

Answer 2

这是tidyr的完美案例：

library(tidyr)
library(dplyr)
dat %>% unnest(logs)

Answer 3

只是为了显示另一个选项

library(data.table)
setDT(df)[, .(logs = unlist(logs)), by = .(id, name)]

Answer 4

另一个data.table选项

library(data.table)
dt <- data.table(df)
dt[,.(id,logs=logs[[1]]), by = name]

按组不列出列

4 个答案: