R Program to add a new column in a given data frame

How to add a new column in a given data frame

Here we are explaining how to write an R program to add a new column in a given data frame. Here we are using a built-in function data.frame() for this. A data frame is used for storing data tables which has a list of vectors with equal length. The data frames are created by function data.frame(), which has tightly coupled collections of variables. The syntax of this function is,

data.frame(…, row.names = NULL, check.rows = FALSE,check.names = TRUE, fix.empty.names = TRUE,stringsAsFactors = default.stringsAsFactors())

– Where dots(…) indicates the arguments are of either the form value or tag = value and row. name is a NULL or a single integer or character string.

How to add a new column in a given data frame in the R program

Below are the steps used in the R program to add a new column in a given data frame. In this R program, we directly give the data frame to a built-in function. Here we are using variables E, N, S, A, Q for holding different types of vectors. Call the function data.frame() for creating dataframe. Finally, add a new column to a given data frame by calling like E$country

ALGORITHM

  • STEP 1: Assign variables E,N,S,A,Q with vector values
  • STEP 2: First print original vector values
  • STEP 3: Add a new column in a given data frame as E$country
  • STEP 4: Print the final data frame

R Source Code

df = data.frame(
                  N = c('Jhon', 'Hialy', 'Albert', 'James', 'Delma'),
                  S = c(10, 9.5, 12.2, 11, 8),
                  A = c(2, 1, 2, 4, 1),
                  Q = c('yes', 'no', 'yes', 'no', 'no')
                )

print("Original dataframe:")
## [1] "Original dataframe:"
print(df)
##        N    S A   Q
## 1   Jhon 10.0 2 yes
## 2  Hialy  9.5 1  no
## 3 Albert 12.2 2 yes
## 4  James 11.0 4  no
## 5  Delma  8.0 1  no
print("New data frame after adding the 'country' column:")
## [1] "New data frame after adding the 'country' column:"
df$Country = c("USA","INDIA","USA","INDIA","USA")

print(df)
##        N    S A   Q Country
## 1   Jhon 10.0 2 yes     USA
## 2  Hialy  9.5 1  no   INDIA
## 3 Albert 12.2 2 yes     USA
## 4  James 11.0 4  no   INDIA
## 5  Delma  8.0 1  no     USA