Data Import and Export Tutorials

There are multiple function are available in R to export data. The following methods show how you can do it with syntax. Method 1: Exporting as a Text File write.table(data,"file.txt",sep="\t") Method 2: Exporting as a Excel File library("writexl") write_xlsx(df,"file.xlsx") Method 3: Exporting as a CSV File write.csv(data,"file.csv") Method 4: Exporting as a RDA File save(data,file= "file.Rda") The following examples show how to export data in R, depending on file format.

To caclulate standard error of the mean in R, you can use std.error() function from plotrix package or you can create function to create standard error of the mean. The following methods show how you can do it with syntax. Method 1: Use std.error() Function library(plotrix) std.error(data) Method 2: Create Function function(data) sd(data)/sqrt(length(data)) The following examples show how to calculate standard error of the mean in R. Use std.error() to Calculate Standard Error of Mean Let’s see how we can use std.

To calculate standardized regression coefficient in R, first you need to scale data using scale() function and then calculate linear regression using lm() function. The following method shows how you can do it with syntax. Method 1: Use scale() and lm() Function scaled_data <- scale(data) lm(scaled_data) The following example shows how to calculate regression coefficient in R. Using scale() and lm() Function Let’s see how we can calculate standard regression coefficient in R for dataframe:

To export data frame to CSV file in R, you can use write.csv() function. The following method shows how you can do it with syntax. Method 1: Use write.csv() Function write.csv(df,file_path) The following example shows how to export data frame to csv file using write.csv() function. Using write.csv() Function Let’s see how we can use write.csv() function in R to export data frame to CSV file: # Create dataframe df<-data.frame(Date=c("21-10-2023","22-10-2023","23-10-2023","24-10-2023","01-11-2023","02-11-2023","03-11-2023","04-11-2023"), Machine_type=c("Mach_1","Mach_2","Mach_3","Mach_4","Mach_A","Mach_B","Mach_C","Mach_D"), Status=c(TRUE,TRUE,FALSE,TRUE,FALSE,TRUE,FALSE,FALSE), Pressure=c(11,12,10,11,89,85,87,90), Temperature=c(45.

To import TSV file in R, you can use read_table() or read_tsv() function from readr package. The following methods show how you can do it with syntax. Method 1: Use read_table() Function library(readr) read.table("path of file") Method 2: Use read_tsv() Function library(readr) read_tsv('path of file') The following examples show how to import TSV file in R using different function. Use read_table() Function Let’s see how we can use read_table() function from readr package in R:

You can read zip files in R using unzip() function from readr package. Method: Use unzip() function library(readr) df <- read_csv(unzip("file.zip","data.csv")) Let’s understand this function using example. Using unzip() function Let’s assume I have product.zip file in my working directory. Follow below syntax to show all files in ZIP: # Get list of all files in zip folder files = unzip("product.zip", list = TRUE) # Print all files in zip folder print(files) Output :

The read.delim() function in R is used to read data from a delimited text file into a data frame. The following method shows how you can do it with syntax. Method 1: Use read.delim() Function read.delim(file, header=TRUE, sep='\t') The following example shows how to use read.delim() function in R to read data from text file. Using read.delim() Function Let’s see how to use read.delim() function in R: # Read in tab-delimited text file df_ <- read.

The write.table() function is used to export data to text file in R. The following method shows how you can do it with syntax. Method 1: Use write.table() Function write.table(dataframe,"file_name.txt") You can provide separator in values of exported file but by default it seperated by single space. For separator you can use sep argument. For example, you could choose tab as a separator: write.table(dataframe,"file_name.txt",sep='\t') The following example shows how to use write.

You can use write.table() function to export data frame to a text file in R. The following method shows how you can do it with syntax. Method: Use write.table() Function write.table(dataframe, path = "C:\\Users\\admin\\data.txt") The following example shows how to export data frame to text file in R. Using write.table() Function To use write.table() function you need to follow below steps: Step 1: Create a Data Frame Let first create data frame in R:

To pass data frame to csv file you can use write.csv() function in R. The following method shows how you can do it with syntax. Method: Use write.csv() Function write.csv(dataframe,path_of_csv_file) The following examples shows to export data frame to csv in R. Using write.csv() Function To use write.csv() function you need to follow below steps: Step 1: Create a Data Frame First let create data frame using data.frame() function: # Create data frame df <- data.

To export data frame to an excel file in R, you can use write_xlsx() function from writexl package. The following method shows how you can do it with syntax. Method: Use write.xlsx() Function library(writexl) write_xlsx(df,file_path) The following example shows how to export data frame to an excel using write_xlsx() function in R. Using write_xlsx() Function Let’s see how we can use write_xlsx() function to export a data frame to an excel in R:

There are three different methods available to import CSV file in R. The following methods show how you can do it with syntax. Method 1: Use read.csv() Function data <- read.csv("path_of_file",header=TRUE) Method 2: Use read_csv() from readr Package library(readr) data <- read_csv("path_of_file") Method 3: Use fread from data.table Package library(data.table) data <- fread("path_of_file") Let’s see example for each method how we can achieve importing CSV in R. Import CSV file Using read.