R Program to Drop Rows from a Dataframe

1. Introduction

When working with dataframes in R, there might be situations where we need to drop specific rows, either based on their index or based on some conditions. In this guide, we will explore how to achieve this using R.

2. Program Overview

1. Create an initial dataframe.

2. Drop rows based on their index.

3. Drop rows based on a condition.

3. Code Program

# Load necessary libraries
library(dplyr)

# Create an initial dataframe
df <- data.frame(
  Name = c('Alice', 'Bob', 'Charlie', 'David', 'Eve'),
  Age = c(25, 30, 28, 35, 29),
  Occupation = c('Engineer', 'Doctor', 'Lawyer', 'Artist', 'Engineer')
)

# Print the original dataframe
print("Original Dataframe:")
print(df)

# Drop the 2nd and 4th rows
df <- df[-c(2,4), ]

# Print the dataframe after dropping rows by index
print("Dataframe after Dropping 2nd and 4th Rows:")
print(df)

# Drop rows where Occupation is 'Engineer'
df <- df %>% filter(Occupation != "Engineer")

# Print the dataframe after dropping rows by condition
print("Dataframe after Dropping Rows with Occupation as 'Engineer':")
print(df)

Output:

[1] "Original Dataframe:"
      Name Age Occupation
1   Alice  25   Engineer
2     Bob  30     Doctor
3 Charlie  28     Lawyer
4   David  35     Artist
5     Eve  29   Engineer

[1] "Dataframe after Dropping 2nd and 4th Rows:"
      Name Age Occupation
1   Alice  25   Engineer
3 Charlie  28     Lawyer
5     Eve  29   Engineer

[1] "Dataframe after Dropping Rows with Occupation as 'Engineer':"
      Name Age Occupation
3 Charlie  28     Lawyer

4. Step By Step Explanation

- We start by creating a dataframe df with columns Name, Age, and Occupation.- To drop rows based on their index, we use negative indexing. For instance, to drop the 2nd and 4th rows, we use df <- df[-c(2,4), ].- To drop rows based on a specific condition, we use the filter function from the dplyr package. In our example, we drop rows where the Occupation column has the value 'Engineer'.