Column tracking by groups

Question

I have a data framework in the following format:

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" 

As you can see, the "logs" column includes row vectors in each cell.

Is there an effective way to convert a data frame to a long format (one observation per row) without an intermediate step of dividing the “logs” into several columns?

This is important because the data set is very large and the number of logs per person seems arbitrary.

In other words, I need the following:

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" 

Here is the dputsection of a real data frame:

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

This is an ideal case for tidyr:

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

Answer 2

listCol_l splitstackshape , "logs" data.frame 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 3

Just to show another option

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