Read and write csv files in R

The CSV (Comma Separated Value) file is a plain text file that uses a comma to separate values.

R has a built-in functionality that makes it easy to read and write a CSV file.

Sample CSV File

To demonstrate how we read CSV files in R, let's suppose we have a CSV file named stud.csv with following data:

rollno   name    place mark

1    101   binu ernkulam   45

2    103  ashik alleppey   35

3    102 faisal   kollam   48

4    105   biju  kotayam   25

5    106    ann  thrisur   30

The csv file contains rollnumber,name,place and mark of students

Read a CSV File in R

In R, we use the read.csv() function to read a CSV file available in our current directory. For example,

stud=read.csv("stud.csv")

print(stud)

output:

 rollno   name    place mark

1    101   binu ernkulam   45

2    103  ashik alleppey   35

3    102 faisal   kollam   48

4    105   biju  kotayam   25

5    106    ann  thrisur   30

Note: If the file is in some other location, we have to specify the path along with the file name as: read.csv("D:/folder/stud.csv")

Number of Rows and Columns of CSV File in R

We use the ncol() and nrow() function to get the total number of rows and columns present in the CSV file in R. For example,
# read stud.csv file from our directory 

stud <- read.csv("stud.csv") 

# print total number of columns 

cat("Total Columns: ", ncol(stud)) 

 # print total number of rows 

cat("Total Rows:", nrow(stud))


Output

Total Columns: 4 

Total Rows: 5

In the above example, we have used the ncol() and nrow() function to find the total number of columns and rows in the stud.csv file.

Using min() and max() With CSV Files

In R, we can also find minimum and maximum data in a certain column of a CSV file using the min() and max() function. For example,

# read stud.csv file from our directory 

stud <- read.csv("stud.csv") 

 # return minimum mark

minmark <- min(stud$mark)

 # return maximum mark

maxmark<- max(stud$mark) 

print(paste("Max Mark=",maxmark))

print(paste("Minimum Mark=",minmark))

Output:

[1] "Max Mark= 48"

[1] "Minimum Mark= 25"

Subset of a CSV File in R

In R, we use the subset() function to return all the data from a CSV file that satisfies the specified condition. For example,

# read stud.csv file from our directory 

stud <- read.csv("stud.csv") 

#mark >40

studnew=subset(stud,mark>40)

print(studnew)

Output:

 rollno   name    place mark

1    101   binu ernkulam   45

3    102 faisal   kollam   48

In the above example, we have specified a certain condition inside the subset() function to extract data from a CSV file.Here, subset() creates a subset of stud.csv with data column mark having data greater than 40 marks and stored it in the studnew data frame.

Write Into CSV File in R

In R, we use the write.csv() function to write into a CSV file. We pass the data in the form of dataframe. For example,

# Create a data frame

dataframe <- data.frame (

  RollNo=c(101,102,103),

  Name = c("Juan", "Alcaraz", "Simantha"),

  Place = c('Alleppey','cochin','Trivandrum'),

  Mark = c(45,35,47))

# write dataframe into stud1 csv file

write.csv(dataframe, "stud1.csv")

In the above example, we have used the write.csv() function to export a data frame named dataframe to a CSV file. Notice the arguments passed inside write.csv(),

write.csv(dataframe, "stud1.csv")

Here,

dataframe\ - name of the data frame we want to export
stud1.csv - name of the csv file

Finally, the stud1.csv file is written in our directory. Open the file and check the output

If we pass "quote = FALSE" to write.csv() as:

write.csv(dataframe, "stud1.csv", quote = FALSE )

All the values were wrapped by double quotes " " are removed.