Convert list of lists to dataframe
Question
I got a nested list, named mylist which has length 4.
Each element of this list is an experiment: exp1.1 , exp1.2 , exp2.1 and exp2.2 .
Each experiment contains observations of length (in days) of four plant growth stages: EM-V6 V6-R0 R0-R4 and R4-R9 .
Each growth stage is organized as a data frame with year and mean .
Here is the complete data:
mylist=structure(list(exp1.1 = structure(list(`EM-V6` = structure(list(
year = 2011:2100, mean = c(34, 34, 32, 28, 25, 32, 32, 28,
27, 30, 32, 31, 33, 28, 26, 31, 33, 27, 34, 26, 28, 27, 27,
30, 29, 31, 34, 30, 26, 31, 33, 33, 27, 30, 28, 32, 31, 29,
32, 31, 25, 28, 28, 26, 32, 29, 26, 31, 28, 29, 30, 25, 27,
32, 27, 28, 28, 30, 24, 30, 29, 29, 29, 28, 26, 28, 26, 26,
28, 31, 30, 27, 26, 28, 25, 24, 24, 30, 27, 26, 26, 27, 26,
26, 24, 26, 28, 25, 30, 26)), .Names = c("year", "mean"), row.names = c(NA,
-90L), class = "data.frame"), `V6-R0` = structure(list(year = 2011:2100,
mean = c(30, 33, 33, 32, 29, 30, 32, 31, 32, 30, 33, 30,
32, 33, 33, 32, 29, 31, 32, 28, 31, 29, 36, 29, 30, 30, 33,
31, 33, 30, 34, 32, 29, 31, 28, 30, 30, 29, 34, 31, 32, 31,
30, 28, 32, 29, 29, 32, 29, 28, 29, 29, 32, 31, 27, 32, 29,
31, 29, 29, 30, 29, 29, 29, 28, 28, 30, 30, 30, 32, 29, 29,
30, 29, 29, 29, 28, 28, 29, 30, 29, 29, 29, 30, 28, 30, 30,
29, 29, 29)), .Names = c("year", "mean"), row.names = c(NA,
-90L), class = "data.frame"), `R0-R4` = structure(list(year = 2011:2100,
mean = c(31, 32, 32, 33, 32, 32, 33, 31, 34, 32, 33, 33,
32, 31, 33, 31, 32, 32, 32, 30, 32, 31, 34, 30, 31, 32, 34,
33, 34, 32, 36, 33, 32, 32, 31, 30, 32, 32, 32, 32, 32, 32,
31, 30, 30, 31, 32, 32, 30, 30, 32, 31, 31, 32, 30, 32, 29,
32, 31, 30, 32, 30, 30, 31, 32, 30, 31, 30, 31, 32, 31, 31,
30, 30, 30, 31, 30, 30, 31, 30, 31, 30, 30, 30, 31, 32, 30,
31, 30, 30)), .Names = c("year", "mean"), row.names = c(NA,
-90L), class = "data.frame"), `R4-R9` = structure(list(year = 2011:2100,
mean = c(27, 29, 28, 28, 27, 30, 29, 27, 30, 26, 30, 28,
29, 28, 29, 27, 29, 28, 25, 26, 26, 25, 27, 27, 27, 28, 30,
28, 29, 27, 29, 28, 29, 28, 26, 26, 28, 28, 30, 28, 27, 25,
26, 25, 25, 26, 26, 27, 25, 25, 26, 25, 27, 28, 24, 27, 25,
28, 26, 24, 27, 26, 27, 25, 26, 26, 24, 26, 25, 26, 24, 25,
25, 26, 26, 25, 25, 25, 25, 25, 26, 25, 25, 25, 25, 26, 26,
26, 25, 24)), .Names = c("year", "mean"), row.names = c(NA,
-90L), class = "data.frame")), .Names = c("EM-V6", "V6-R0", "R0-R4",
"R4-R9")), exp1.2 = structure(list(`EM-V6` = structure(list(year = 2011:2100,
mean = c(34, 34, 32, 28, 25, 32, 32, 28, 27, 30, 32, 31,
33, 28, 26, 31, 33, 27, 34, 26, 28, 27, 27, 30, 29, 31, 34,
30, 26, 31, 33, 33, 27, 30, 28, 32, 31, 29, 32, 31, 25, 28,
28, 26, 32, 29, 26, 31, 28, 29, 30, 25, 27, 32, 27, 28, 28,
30, 24, 30, 29, 29, 29, 28, 26, 28, 26, 26, 28, 31, 30, 27,
26, 28, 25, 24, 24, 30, 27, 26, 26, 27, 26, 26, 24, 26, 28,
25, 30, 26)), .Names = c("year", "mean"), row.names = c(NA,
-90L), class = "data.frame"), `V6-R0` = structure(list(year = 2011:2100,
mean = c(30, 33, 33, 32, 29, 30, 32, 31, 32, 30, 33, 30,
32, 33, 33, 32, 29, 31, 32, 28, 31, 29, 36, 29, 30, 30, 33,
31, 33, 30, 34, 32, 29, 31, 28, 30, 30, 29, 34, 31, 32, 31,
30, 28, 32, 29, 29, 32, 29, 28, 29, 29, 32, 31, 27, 32, 29,
31, 29, 29, 30, 29, 29, 29, 28, 28, 30, 30, 30, 32, 29, 29,
30, 29, 29, 29, 28, 28, 29, 30, 29, 29, 29, 30, 28, 30, 30,
29, 29, 29)), .Names = c("year", "mean"), row.names = c(NA,
-90L), class = "data.frame"), `R0-R4` = structure(list(year = 2011:2100,
mean = c(31, 32, 32, 33, 32, 32, 33, 31, 34, 32, 33, 33,
32, 31, 33, 31, 32, 32, 32, 30, 32, 31, 34, 30, 31, 32, 34,
33, 34, 32, 36, 33, 32, 32, 31, 30, 32, 32, 32, 32, 32, 32,
31, 30, 30, 31, 32, 32, 30, 30, 32, 31, 31, 32, 30, 32, 29,
32, 31, 30, 32, 30, 30, 31, 32, 30, 31, 30, 31, 32, 31, 31,
30, 30, 30, 31, 30, 30, 31, 30, 31, 30, 30, 30, 31, 32, 30,
31, 30, 30)), .Names = c("year", "mean"), row.names = c(NA,
-90L), class = "data.frame"), `R4-R9` = structure(list(year = 2011:2100,
mean = c(27, 29, 28, 28, 27, 30, 29, 27, 30, 26, 30, 28,
29, 28, 29, 27, 29, 28, 25, 26, 26, 25, 27, 27, 27, 28, 30,
28, 29, 27, 29, 28, 29, 28, 26, 26, 28, 28, 30, 28, 27, 25,
26, 25, 25, 26, 26, 27, 25, 25, 26, 25, 27, 28, 24, 27, 25,
28, 26, 24, 27, 26, 27, 25, 26, 26, 24, 26, 25, 26, 24, 25,
25, 26, 26, 25, 25, 25, 25, 25, 26, 25, 25, 25, 25, 26, 26,
26, 25, 24)), .Names = c("year", "mean"), row.names = c(NA,
-90L), class = "data.frame")), .Names = c("EM-V6", "V6-R0", "R0-R4",
"R4-R9")), exp2.1 = structure(list(`EM-V6` = structure(list(year = 2011:2100,
mean = c(34, 34, 32, 28, 25, 32, 32, 28, 27, 30, 32, 31,
33, 28, 26, 31, 33, 27, 34, 26, 28, 27, 27, 30, 29, 31, 34,
30, 26, 31, 33, 33, 27, 30, 28, 32, 31, 29, 32, 31, 25, 28,
28, 26, 32, 29, 26, 31, 28, 29, 30, 25, 27, 32, 27, 28, 28,
30, 24, 30, 29, 29, 29, 28, 26, 28, 26, 26, 28, 31, 30, 27,
26, 28, 25, 24, 24, 30, 27, 26, 26, 27, 26, 26, 24, 26, 28,
25, 30, 26)), .Names = c("year", "mean"), row.names = c(NA,
-90L), class = "data.frame"), `V6-R0` = structure(list(year = 2011:2100,
mean = c(30, 33, 33, 32, 29, 30, 32, 31, 32, 30, 33, 30,
32, 33, 33, 32, 29, 31, 32, 28, 31, 29, 36, 29, 30, 30, 33,
31, 33, 30, 34, 32, 29, 31, 28, 30, 30, 29, 34, 31, 32, 31,
30, 28, 32, 29, 29, 32, 29, 28, 29, 29, 32, 31, 27, 32, 29,
31, 29, 29, 30, 29, 29, 29, 28, 28, 30, 30, 30, 32, 29, 29,
30, 29, 29, 29, 28, 28, 29, 30, 29, 29, 29, 30, 28, 30, 30,
29, 29, 29)), .Names = c("year", "mean"), row.names = c(NA,
-90L), class = "data.frame"), `R0-R4` = structure(list(year = 2011:2100,
mean = c(31, 32, 32, 33, 32, 32, 33, 31, 34, 32, 33, 33,
32, 31, 33, 31, 32, 32, 32, 30, 32, 31, 34, 30, 31, 32, 34,
33, 34, 32, 36, 33, 32, 32, 31, 30, 32, 32, 32, 32, 32, 32,
31, 30, 30, 31, 32, 32, 30, 30, 32, 31, 31, 32, 30, 32, 29,
32, 31, 30, 32, 30, 30, 31, 32, 30, 31, 30, 31, 32, 31, 31,
30, 30, 30, 31, 30, 30, 31, 30, 31, 30, 30, 30, 31, 32, 30,
31, 30, 30)), .Names = c("year", "mean"), row.names = c(NA,
-90L), class = "data.frame"), `R4-R9` = structure(list(year = 2011:2100,
mean = c(27, 29, 28, 28, 27, 30, 29, 27, 30, 26, 30, 28,
29, 28, 29, 27, 29, 28, 25, 26, 26, 25, 27, 27, 27, 28, 30,
28, 29, 27, 29, 28, 29, 28, 26, 26, 28, 28, 30, 28, 27, 25,
26, 25, 25, 26, 26, 27, 25, 25, 26, 25, 27, 28, 24, 27, 25,
28, 26, 24, 27, 26, 27, 25, 26, 26, 24, 26, 25, 26, 24, 25,
25, 26, 26, 25, 25, 25, 25, 25, 26, 25, 25, 25, 25, 26, 26,
26, 25, 24)), .Names = c("year", "mean"), row.names = c(NA,
-90L), class = "data.frame")), .Names = c("EM-V6", "V6-R0", "R0-R4",
"R4-R9")), exp2.2 = structure(list(`EM-V6` = structure(list(year = 2011:2100,
mean = c(34, 34, 32, 28, 25, 32, 32, 28, 27, 30, 32, 31,
33, 28, 26, 31, 33, 27, 34, 26, 28, 27, 27, 30, 29, 31, 34,
30, 26, 31, 33, 33, 27, 30, 28, 32, 31, 29, 32, 31, 25, 28,
28, 26, 32, 29, 26, 31, 28, 29, 30, 25, 27, 32, 27, 28, 28,
30, 24, 30, 29, 29, 29, 28, 26, 28, 26, 26, 28, 31, 30, 27,
26, 28, 25, 24, 24, 30, 27, 26, 26, 27, 26, 26, 24, 26, 28,
25, 30, 26)), .Names = c("year", "mean"), row.names = c(NA,
-90L), class = "data.frame"), `V6-R0` = structure(list(year = 2011:2100,
mean = c(30, 33, 33, 32, 29, 30, 32, 31, 32, 30, 33, 30,
32, 33, 33, 32, 29, 31, 32, 28, 31, 29, 36, 29, 30, 30, 33,
31, 33, 30, 34, 32, 29, 31, 28, 30, 30, 29, 34, 31, 32, 31,
30, 28, 32, 29, 29, 32, 29, 28, 29, 29, 32, 31, 27, 32, 29,
31, 29, 29, 30, 29, 29, 29, 28, 28, 30, 30, 30, 32, 29, 29,
30, 29, 29, 29, 28, 28, 29, 30, 29, 29, 29, 30, 28, 30, 30,
29, 29, 29)), .Names = c("year", "mean"), row.names = c(NA,
-90L), class = "data.frame"), `R0-R4` = structure(list(year = 2011:2100,
mean = c(31, 32, 32, 33, 32, 32, 33, 31, 34, 32, 33, 33,
32, 31, 33, 31, 32, 32, 32, 30, 32, 31, 34, 30, 31, 32, 34,
33, 34, 32, 36, 33, 32, 32, 31, 30, 32, 32, 32, 32, 32, 32,
31, 30, 30, 31, 32, 32, 30, 30, 32, 31, 31, 32, 30, 32, 29,
32, 31, 30, 32, 30, 30, 31, 32, 30, 31, 30, 31, 32, 31, 31,
30, 30, 30, 31, 30, 30, 31, 30, 31, 30, 30, 30, 31, 32, 30,
31, 30, 30)), .Names = c("year", "mean"), row.names = c(NA,
-90L), class = "data.frame"), `R4-R9` = structure(list(year = 2011:2100,
mean = c(27, 29, 28, 28, 27, 30, 29, 27, 30, 26, 30, 28,
29, 28, 29, 27, 29, 28, 25, 26, 26, 25, 27, 27, 27, 28, 30,
28, 29, 27, 29, 28, 29, 28, 26, 26, 28, 28, 30, 28, 27, 25,
26, 25, 25, 26, 26, 27, 25, 25, 26, 25, 27, 28, 24, 27, 25,
28, 26, 24, 27, 26, 27, 25, 26, 26, 24, 26, 25, 26, 24, 25,
25, 26, 26, 25, 25, 25, 25, 25, 26, 25, 25, 25, 25, 26, 26,
26, 25, 24)), .Names = c("year", "mean"), row.names = c(NA,
-90L), class = "data.frame")), .Names = c("EM-V6", "V6-R0", "R0-R4",
"R4-R9"))), .Names = c("exp1.1", "exp1.2", "exp2.1", "exp2.2"
))
What I need to do is to "unlist" this nested list to a data frame that will look like this:
YEAR EXP EM-V6 V6-R0 R0-R4 R4-R9
2011 exp1.1 34 30 31 27
2011 exp1.2 34 30 31 27
2011 exp2.1 34 30 31 27
2011 exp1.1 34 30 31 27
Which means:
- first year, first experiment, and growth stages.
- first year, second experiment and growth stages.
- first year, third experiment and growth stages
- first year, fourth experiment and growth stages
- second year, first experiment and growth stages
and so on.
How to perform that data transformation?
3 answers
solution1
7 ACCPTED 2017-01-23 11:01:22
An alternative using rbindlist from the data.table -package twice:
library(data.table)
# bind the dataframes in the 'listed lists' together and include the year with the 'id'-parameter
# the resulting 'data.table's are returned as a list
step1 <- lapply(mylist, rbindlist, id = 'stages')
# bind the resulting list together and include the experiment id
step2 <- rbindlist(step1, id = 'experiment')
# reshape to wide format
dcast(step2, year + experiment ~ stages, value.var = 'mean')
Or in one go:
dcast(rbindlist(lapply(mylist, rbindlist, id = 'stages'), id = 'experiment'),
year + experiment ~ stages, value.var = 'mean')
which gives:
year experiment EM-V6 R0-R4 R4-R9 V6-R0
1: 2011 exp1.1 34 31 27 30
2: 2011 exp1.2 34 31 27 30
3: 2011 exp2.1 34 31 27 30
4: 2011 exp2.2 34 31 27 30
5: 2012 exp1.1 34 32 29 33
---
356: 2099 exp2.2 30 30 25 29
357: 2100 exp1.1 26 30 24 29
358: 2100 exp1.2 26 30 24 29
359: 2100 exp2.1 26 30 24 29
360: 2100 exp2.2 26 30 24 29
solution2
6 2017-01-23 12:26:08
Alternate tidyverse:
library(tidyverse)
map_df(mylist, ~bind_rows(., .id="id"), .id="EXP") %>%
spread(id, mean)
solution3
1 2017-01-23 10:56:35
We can use tidyverse with more compact and readable code
library(dplyr)
library(tidyr)
library(purrr)
res1 <- mylist %>%
#bind the inner datasets and create an id column
map(bind_rows, .id = "id") %>%
#bind the outer datasets and create an EXP column
bind_rows(.id = "EXP") %>%
#reshape to wide format
spread(id, mean)
head(res1, 4)
# EXP year EM-V6 R0-R4 R4-R9 V6-R0
#1 exp1.1 2011 34 31 27 30
#2 exp1.1 2012 34 32 29 33
#3 exp1.1 2013 32 32 28 33
#4 exp1.1 2014 28 33 28 32
Or we can approach this by looping through the mylist with lapply , then create a new column 'name' usign Map by cbind ing the names of the inner list elements, then rbind the list elements with do.call(rbind , now do a second Map to create a new column based on the names of 'mylist', rbind the list elements and then reshape from base R to convert it to 'wide'
res <- do.call(rbind, Map(cbind, lapply(mylist, function(x)
do.call(rbind, Map(cbind, x, name = names(x)))), EXP= names(mylist)))
res2 <- reshape(res, idvar = c("year", "EXP"),
timevar = "name", direction = "wide")
row.names(res2) <- NULL
head(res2, 4)
# year EXP mean.EM-V6 mean.V6-R0 mean.R0-R4 mean.R4-R9
#1 2011 exp1.1 34 30 31 27
#2 2012 exp1.1 34 33 32 29
#3 2013 exp1.1 32 33 32 28
#4 2014 exp1.1 28 32 33 28
NOTE: No external packages used (100% base R )
or use dcast from reshape2 to transform to 'wide' format
library(reshape2)
res2 <- dcast(res, year + EXP~name, value.var = "mean")
head(res2, 4)
# year EXP EM-V6 V6-R0 R0-R4 R4-R9
#1 2011 exp1.1 34 30 31 27
#2 2011 exp1.2 34 30 31 27
#3 2011 exp2.1 34 30 31 27
#4 2011 exp2.2 34 30 31 27
The technical post webpages of this site follow the CC BY-SA 4.0 protocol. If you need to reprint, please indicate the site URL or the original address.Any question please contact:yoyou2525@163.com.
Related Question
convert a list with lists to a dataframe
R convert list of lists to dataframe
How to convert a dataFrame to a list of Lists?
Convert lists in a dataframe column into a single list in R
How to convert R dataframe into a list of lists?
R - Convert List of Lists into single dataframe
How to convert list of lists to dataframe in R
How to convert list of lists of vectors to a dataframe
How to convert a list of nested lists of dataframes into a dataframe?
Convert a dataframe to a list of lists based on common features
Related Tags