This question already has answers here:
Split comma-separated strings in a column into separate rows
(6 answers)
Closed 6 years ago.
Sorry for the naive question but I have a dataframe like this:
n sp cap
1 1 a 3
2 2 b 3+2+4
3 3 c 2
4 4 d 1+5
I need to split the numbers separated by the add sign ("+") into new rows in order to the get a new dataframe like this below:
n sp cap
1 1 a 3
2 2 b 3
3 2 b 2
4 2 b 4
5 3 c 2
6 4 d 1
7 4 d 5
How can I do that? strsplit?
thanks in advance
We could use cSplit from splitstackshape
library(splitstackshape)
cSplit(df1, 'cap', sep="+", 'long')
# n sp cap
#1: 1 a 3
#2: 2 b 3
#3: 2 b 2
#4: 2 b 4
#5: 3 c 2
#6: 4 d 1
#7: 4 d 5
Or could do this in base R. Use strsplit to split the elements of "cap" column to substrings, which returns a list (lst), Replicate the rows of dataset by the length of each list element, subset the dataset based on the new index, convert the "lst" elements to "numeric", unlist, and cbind with the modified dataset.
lst <- strsplit(as.character(df1$cap), "[+]")
df2 <- cbind(df1[rep(1:nrow(df1), sapply(lst, length)),1:2],
cap= unlist(lapply(lst, as.numeric)))
Related
This question already has answers here:
Combine a list of data frames into one data frame by row
(10 answers)
Closed 1 year ago.
I have an object with each row being a dataframe or list itself like this:
[[1]]
1: a b c d
1 1 2 4
[[2]]
1: a b c d
4 3 6 2
[[3]]
1: a b c d
1 2 2 1
How can I transform this to a dataframe like below?
a b c d
1 1 2 4
4 3 6 2
1 2 2 1
We can use rbindlist
library(data.table)
rbindlist(lst1)
Or with rbind and do.call in base R
do.call(rbind, lst1)
This question already has answers here:
Collapse / concatenate / aggregate a column to a single comma separated string within each group
(6 answers)
Count number of rows within each group
(17 answers)
Closed 2 years ago.
I want to count the unique combinations of a variable that appear per group.
For example:
df <- data.frame(id = c(1,1,1,2,2,2,3,3,4,4,4,5,6,6,7,7,7),
status = c("a","b","c","a","b","c","b","c","b","c","d","b","b","c","b","c", "d"))
> df
id status
1 1 a
2 1 b
3 1 c
4 2 a
5 2 b
6 2 c
7 3 b
8 3 c
9 4 b
10 4 c
11 4 d
12 5 b
13 6 b
14 6 c
15 7 b
16 7 c
17 7 d
So that, for example, I can tally how many times a given combination of "status" appears.
By hand, for example, I see that "a,b,c" appears twice total (id's 1 and 2).
These seem to be similar questions, but I couldn't work out how to do it and with clearer explanation in R:
Counting unique combinations
Count of unique combinations despite order
The result I think I am looking for would be something like:
abc 2
bc 3
b 1
...
An option with tidyverse where group by 'id', paste the 'status' and get the count
library(dplyr)
library(stringr)
df %>%
group_by(id) %>%
summarise(status = str_c(status, collapse="")) %>%
count(status)
# A tibble: 4 x 2
# status n
# <chr> <int>
#1 abc 2
#2 b 1
#3 bc 2
#4 bcd 2
Here is a base R option via aggregate
> aggregate(.~status,rev(aggregate(.~id,df,paste0,collapse = "")),length)
status id
1 abc 2
2 b 1
3 bc 2
4 bcd 2
You can use the apply family of functions too with tapply and lapply to get there with table.
tap <- tapply(df$status, df$id ,FUN= function(x) unique(x))
lap <- lapply(tap,FUN = function(x) paste0(x,collapse=""))
status <- unlist(lap)
df1 <- data.frame(table(status))
> df1
status Freq
1 abc 2
2 b 1
3 bc 2
4 bcd 2
This question already has answers here:
Repeat each row of data.frame the number of times specified in a column
(10 answers)
Closed 3 years ago.
I have a data.frame with n rows and I would like to repeat this rows according to the observation of another variable
This is an example for a data.frame
df <- data.frame(a=1:3, b=letters[1:2])
df
a b
1 1 a
2 2 b
3 3 c
And this one is an example for a variable
df1 <- data.frame(x=1:3)
df1
x
1 1
2 2
3 3
In the next step I would like to repeat every row from the df with the observation of df1
So that it would look like this
a b
1 1 a
2 2 b
3 2 b
4 3 c
5 3 c
6 3 c
If you have any idea how to solve this problem, I would be very thankful
You simply can repeat the index like:
df[rep(1:3,df1$x),]
# a b
#1 1 a
#2 2 b
#2.1 2 b
#3 3 c
#3.1 3 c
#3.2 3 c
or not fixed to size 3
df[rep(seq_along(df1$x),df1$x),]
Suppose I have a dataframe like so
a b c
1 2 3
1 3 4
1 4 5
2 5 6
2 6 7
3 7 8
4 8 9
What I want is the following:
a b c d
1 2 3 a
1 3 4 b
1 4 5 c
2 5 6 a
2 6 7 b
3 7 8 a
4 8 9 a
Essentially, I want to do a cycling, for each group by the column a, I want to create a new column which cycles the letters from a to z in order. Group 1 has three elements, so the letter goes from 'a' to 'c'. Group 3 and 4 has only 1 element, so the letter only gets assigned 'a'.
A data.table option is
library(data.table)
setDT(dd)[, d:= letters[seq_len(.N)], by = a]
One way to do this is with a split-apply-combine paradigm, as in plyr (or dplyr or data.table or ...
Create data:
dd <- data.frame(a=rep(1:4,c(3,2,1,1)),
b=2:8,c=3:9)
Use ddply to split the data frame by variable a, transforming each piece by adding an appropriate variable, then recombine:
library("plyr")
ddply(dd,"a",
transform,
d=letters[1:length(b)])
Or in dplyr:
library("dplyr")
dd %>% group_by(a) %>%
mutate(d=letters[1:n()])
Or in base R (thanks #thelatemail):
dd$d <- ave(rownames(dd), dd$a,
FUN=function(x) letters[seq_along(x)] )
This question already has answers here:
Repeat each row of data.frame the number of times specified in a column
(10 answers)
Closed 7 years ago.
I have a data frame with names by type and their frequencies. I'd like to expand this data frame so that the names are repeated according to their name-type frequency.
For example, this:
> df = data.frame(name=c('a','b','c'),type=c(0,1,2),freq=c(2,3,2))
name type freq
1 a 0 2
2 b 1 3
3 c 2 2
would become this:
> df_exp
name type
1 a 0
2 a 0
3 b 1
4 b 1
5 b 1
6 c 2
7 c 2
Appreciate any suggestions on a easy way to do this.
You can just use rep to "expand" your data.frame rows:
df[rep(sequence(nrow(df)), df$freq), c("name", "type")]
# name type
# 1 a 0
# 1.1 a 0
# 2 b 1
# 2.1 b 1
# 2.2 b 1
# 3 c 2
# 3.1 c 2
And there's a function expandRows in the splitstackshape package that does exactly this. It also has the option to accept a vector specifying how many times to replicate each row, for example:
expandRows(df, "freq")