Read Data from CSV File

In R Language one can easily read data from CSV file format. One can use the read.csv() function. There are different ways to read the CSV file in R and the read.csv() function has many useful arguments.

It is important to note that a CSV file is a comma-separated value file. Usually, CSV files are generated from spreadsheet-like software such as MS Excel. Regarding the file type CSV files are very similar to txt files, however, CSV files can be easily opened in MS Excel. The read.csv() function imports the CSV file as a data frame in R Language, a fundamental data structure in R.

Using the read.csv() function one can read the data from a CSV file by choosing the file (a dialog box opens to select the appropriate file). This is the easy way to choose a data file as the user does not need to type the file path. For example,

data <- read.csv(file.choose(),header =TRUE)

The file.choose() argument will open a dialog box for the selection of the required file.

Read Data from CSV File

After selecting the data file, one can use the data and may display and get the data information, such as

head(data)
str(data)

There is another way to read the data by giving the complete path to the file with the data file name and its extension.

data <-read.csv("C:\\book1.csv", header=TRUE)
data <-read.csv("C:\\mywork\\data\\book1.csv", header=TRUE)

After reading the data file, one can check the names of each variable by using names() function.

names(data)

One can select a column (variable) by using square brackets and column index or by use of a dollar sign. For example

data$X1    # Selects the variable X1
data[, 1]  # selects the variable in column 1
data[, 4]  # selects the variable in column 4
data[, 1:3] # selects column 1, 2 and 3 

Similarly, one can also select the rows from a data file. For example

data[12, ]   # select the 12 observation/ row of all variables (columns)
data[5:10, ] # selects rows 5 to 10 with all columns/variables

One can also subset the data by using some conditional operator. For example, the following command reads $X_1$ variable from data having greater than 0.7 values.

data1[data1$X1 > 0.7, ]

One can also a CSV file as a table. For example,

data <- read.table("C:\\data.csv",sep ",",header True)

Some important arguments related to read.csv() function:

  • file: The file argument is used to specify the path to the CSV file. One can provide either the absolute path (e.g., “C:/Users/yourname/Documents/data.csv”) or the relative path if the file is in the working directory.
  • header (optional): The header argument is logical (either TRUE or FALSE), it indicates whether the first row of the CSV file contains names of the columns. By default, header=TRUE. In case, if the file does not have a header row, set it header=FALSE.
  • sep (optional): The sep argument specifies the delimiter (separator) used between values in the CSV file. The default is a comma (“,”).
  • dec (optional): The dec argument defines the decimal point character used in the CSV file. The default is “.”.

https://itfeature.com

https://gmstat.com

Leave a Reply

Discover more from R Frequently Asked Questions

Subscribe now to keep reading and get access to the full archive.

Continue reading