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

Answer 1

If you already have a dataframe, you can extract the metadata (column names and types) from a dataframe (e.g. if you are controlling a BUG which is only triggered with certain inputs and need a empty dummy Dataframe):

colums_and_types <- sapply(df, class)

# prints: "c('col1', 'col2')"
print(dput(as.character(names(colums_and_types))))

# prints: "c('integer', 'factor')"
dput(as.character(as.vector(colums_and_types)))

And then use the read.table to create the empty dataframe

read.table(text = "",
   colClasses = c('integer', 'factor'),
   col.names = c('col1', 'col2'))

Answer 2

If you want to create an empty data.frame with dynamic names (colnames in a variable), this can help:

names <- c("v","u","w")
df <- data.frame()
for (k in names) df[[k]]<-as.numeric()

You can change the types as well if you need so. like:

names <- c("u", "v")
df <- data.frame()
df[[names[1]]] <- as.numeric()
df[[names[2]]] <- as.character()

Answer 3

Just declare

table = data.frame()

when you try to rbind the first line it will create the columns

Answer 4

To create an empty data frame, pass in the number of rows and columns needed into the following function:

create_empty_table <- function(num_rows, num_cols) {
    frame <- data.frame(matrix(NA, nrow = num_rows, ncol = num_cols))
    return(frame)
}

To create an empty frame while specifying the class of each column, simply pass a vector of the desired data types into the following function:

create_empty_table <- function(num_rows, num_cols, type_vec) {
  frame <- data.frame(matrix(NA, nrow = num_rows, ncol = num_cols))
  for(i in 1:ncol(frame)) {
    print(type_vec[i])
    if(type_vec[i] == 'numeric') {frame[,i] <- as.numeric(frame[,i])}
    if(type_vec[i] == 'character') {frame[,i] <- as.character(frame[,i])}
    if(type_vec[i] == 'logical') {frame[,i] <- as.logical(frame[,i])}
    if(type_vec[i] == 'factor') {frame[,i] <- as.factor(frame[,i])}
  }
  return(frame)
}

Use as follows:

df <- create_empty_table(3, 3, c('character','logical','numeric'))

Which gives:

   X1  X2 X3
1 <NA> NA NA
2 <NA> NA NA
3 <NA> NA NA

To confirm your choices, run the following:

lapply(df, class)

#output
$X1
[1] "character"

$X2
[1] "logical"

$X3
[1] "numeric"

Answer 5

If you are looking for shortness :

read.csv(text="col1,col2")

so you don't need to specify the column names separately. You get the default column type logical until you fill the data frame.

Answer 6

By Using data.table we can specify data types for each column.

library(data.table)    
data=data.table(a=numeric(), b=numeric(), c=numeric())