This tutorial explains various ways to create an empty data frame with R.
Method 1: Create an empty data frame
blank_df <- data.frame()
Method 2: Create an empty data frame using matrix and convert to data.frame
blank_df <- data.frame(matrix(ncol = 0, nrow = 0))
Method 3: Creating an empty data frame with structure()
empty_df <- structure(list(), class = "data.frame")
Method 4: Create an empty data frame using tibble
library(dplyr) empty_df <- tibble()
To check the number of rows and columns in a dataframe, you can use the function dim()
dim(empty_df)
It returns 0 0 for empty_df which means 0 number of rows and columns.
The following code creates an empty data frame with column names and data types.
empty_df <- data.frame(Column1 = numeric(0), Column2 = character(0), Column3 = logical(0))
You can also specify the column names like the code below to create an empty data frame.
empty_df <- data.frame(matrix(ncol = 3, nrow = 0)) col_names <- c("Column1", "Column2", "Column3") names(empty_df) <- col_names
Creating an empty data frame before entering a loop can be very useful, especially when you plan to append data or results from each iteration of the loop. This practice ensures that you have a pre-defined structure in place to which you can add data in subsequent iterations.
By creating an empty data frame before the loop, you define the column names, data types, and other necessary attributes of the data frame. This helps avoid potential issues with mismatched data types or columns that might arise if you directly add data to the data frame within the loop without predefining its structure. Check out the code below.
logitfn = function(df,depvar) { dummydt=data.frame(matrix(ncol=0,nrow=0)) depvar1 = deparse(substitute(depvar)) xxxx = names(df)[which(names(df)!= depvar1)] for (i in 1:length(xxxx)) { mylogit = glm(formula(paste(depvar1,"~",xxxx[i])), data = df, family = "binomial") coeff = data.frame(summary(mylogit)$coefficient) if (i==1) { output = rbind(dummydt,coeff) } else { output = rbind(output,coeff) } } return(output) } # Convert the target variable "Species" to binary iris$is_setosa <- ifelse(iris$Species == "setosa", 1, 0) iris <- iris[, !(names(iris) %in% "Species")] outdata <- logitfn(iris, is_setosa)
Code not working
ReplyDelete> dummydt=data.frame(matrix(ncol=0,nrow=0))
ReplyDelete> unilogit2 = function(df,depvar, output) {
+ dummydt=data.frame(matrix(ncol=0,nrow=0)) depvar1 = deparse(substitute(depvar))
Error: unexpected symbol in:
"unilogit2 = function(df,depvar, output) {
dummydt=data.frame(matrix(ncol=0,nrow=0)) depvar1"
> out = deparse(substitute(output))
> xxxx = names(df)[which(names(df)!= depvar1)]
Error in which(names(df) != depvar1) : object 'depvar1' not found
> for (i in 1:length(xxxx)) {
+ mylogit = glm(formula(paste(depvar1,"~",xxxx[i])), data = df, family = "binomial")
+ coeff = data.frame(summary(mylogit)$coefficient)
+ if (i==1) {output = rbind(dummydt,coeff)} else {output = rbind(output,coeff)} assign(out,output, envir = .GlobalEnv)
Error: unexpected symbol in:
" coeff = data.frame(summary(mylogit)$coefficient)
if (i==1) {output = rbind(dummydt,coeff)} else {output = rbind(output,coeff)} assign"
> }
Error: unexpected '}' in " }"
>