CODEWITHSUNDEEP
r
user2374133
user2374133

Reputation: 193

How do you pivot data from a list of data frames in R?

Let's say I have a list of data frames ldf:

df1 <- data.frame(date = c(1,2), value = c(4,5))
df2 <- data.frame(date = c(1,2), value = c(4,5))
ldf <- list(df1, df2)

What is the best way to get the sum (or any other function) of values by date, i.e. some data frame like:

data.frame(date = c(1,2), value = c(8,10))

Upvotes: 1

Views: 169

Answers (3)

A5C1D2H2I1M1N2O1R2T1
A5C1D2H2I1M1N2O1R2T1

Reputation: 193507

Another option is to use unnest from "tidyr" in conjunction with the typical grouping and aggregation functions via "dplyr":

library(dplyr)
library(tidyr)

unnest(ldf) %>%
  group_by(date) %>%
  summarise(value = sum(value))
# Source: local data frame [2 x 2]
# 
#   date value
# 1    1     8
# 2    2    10

Upvotes: 0

akrun
akrun

Reputation: 886938

You could use:

library(data.table)
dt1 <- rbindlist(ldf)
setkey(dt1,'date')
dt1[,list(value=sum(value)), by='date']
 date value
1:    1     8
2:    2    10

Upvotes: 2

Matthew Lundberg
Matthew Lundberg

Reputation: 42629

If these rows were all in the same data frame, you would use aggregate to do the sum. You can combine them with rbind so they are in the same data frame:

aggregate(value ~ date, data=do.call(rbind, ldf), FUN=sum)
  date value
1    1     8
2    2    10

If the date columns in all the data frames are identical, you can easily use Reduce to do the sum:

Reduce(function(x, y) data.frame(date=x$date, value=x$value+y$value), ldf)
  date value
1    1     8
2    2    10

This should be a lot faster than rbind-ing the data together and aggregating.

Upvotes: 1

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