Create an empty data.frame
Create an empty data.frame
Question
I'm trying to initialize a data.frame without any rows. Basically, I want to specify the data types for each column and name them, but not have any rows created as a result.
The best I've been able to do so far is something like:
df <- data.frame(Date=as.Date("01/01/2000", format="%m/%d/%Y"),
File="", User="", stringsAsFactors=FALSE)
df <- df[-1,]
Which creates a data.frame with a single row containing all of the data types and column names I wanted, but also creates a useless row which then needs to be removed.
Is there a better way to do this?
Accepted Answer
Just initialize it with empty vectors:
df <- data.frame(Date=as.Date(character()),
File=character(),
User=character(),
stringsAsFactors=FALSE)
Here's an other example with different column types :
df <- data.frame(Doubles=double(),
Ints=integer(),
Factors=factor(),
Logicals=logical(),
Characters=character(),
stringsAsFactors=FALSE)
str(df)
> str(df)
'data.frame': 0 obs. of 5 variables:
$ Doubles : num
$ Ints : int
$ Factors : Factor w/ 0 levels:
$ Logicals : logi
$ Characters: chr
N.B. :
Initializing a data.frame with an empty column of the wrong type does not prevent further additions of rows having columns of different types.
This method is just a bit safer in the sense that you'll have the correct column types from the beginning, hence if your code relies on some column type checking, it will work even with a data.frame with zero rows.
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If you already have an existent data frame, let's say df that has the columns you want, then you can just create an empty data frame by removing all the rows:
empty_df = df[FALSE,]
Notice that df still contains the data, but empty_df doesn't.
I found this question looking for how to create a new instance with empty rows, so I think it might be helpful for some people.
You can do it without specifying column types
df = data.frame(matrix(vector(), 0, 3,
dimnames=list(c(), c("Date", "File", "User"))),
stringsAsFactors=F)
You could use read.table with an empty string for the input text as follows:
colClasses = c("Date", "character", "character")
col.names = c("Date", "File", "User")
df <- read.table(text = "",
colClasses = colClasses,
col.names = col.names)
Alternatively specifying the col.names as a string:
df <- read.csv(text="Date,File,User", colClasses = colClasses)
Thanks to Richard Scriven for the improvement
Just declare
table = data.frame()
when you try to rbind the first line it will create the columns
The most efficient way to do this is to use structure to create a list that has the class "data.frame":
structure(list(Date = as.Date(character()), File = character(), User = character()),
class = "data.frame")
# [1] Date File User
# <0 rows> (or 0-length row.names)
To put this into perspective compared to the presently accepted answer, here's a simple benchmark:
s <- function() structure(list(Date = as.Date(character()),
File = character(),
User = character()),
class = "data.frame")
d <- function() data.frame(Date = as.Date(character()),
File = character(),
User = character(),
stringsAsFactors = FALSE)
library("microbenchmark")
microbenchmark(s(), d())
# Unit: microseconds
# expr min lq mean median uq max neval
# s() 58.503 66.5860 90.7682 82.1735 101.803 469.560 100
# d() 370.644 382.5755 523.3397 420.1025 604.654 1565.711 100