# 1. Introduction

This R program shows how to store data in a data frame and perform various operations on it. A data frame is a key data structure in R for storing datasets in a tabular format, similar to a spreadsheet or a database table.

# 2. Program Steps

1. Create a data frame.

2. Add a new column to the data frame.

3. Modify an existing column in the data frame.

4. Remove a column from the data frame.

5. Access a specific row of the data frame.

6. Print the final data frame after all operations.

# 3. Code Program

``````# Step 1: Create a data frame
data_df <- data.frame(Name = c("Alice", "Bob", "Charlie"), Age = c(25, 30, 35), Gender = c("Female", "Male", "Male"))

# Step 2: Add a new column (Salary)
data_df\$Salary <- c(50000, 60000, 55000)

# Step 3: Modify an existing column (Age)
data_df\$Age <- data_df\$Age + 5

# Step 4: Remove a column (Gender)
data_df\$Gender <- NULL

# Step 5: Access a specific row (Row 2)
accessed_row <- data_df[2, ]

# Step 6: Print the final data frame
print("Final Data Frame after operations:")
print(data_df)

``````

### Output:

```Final Data Frame after operations:
Name Age Salary
1    Alice  30  50000
2      Bob  35  60000
3 Charlie  40  55000
```

### Explanation:

1. data.frame(Name = c("Alice", "Bob", "Charlie"), Age = c(25, 30, 35), Gender = c("Female", "Male", "Male")): Creates a data frame with three columns: Name, Age, and Gender.

2. data_df\$Salary <- c(50000, 60000, 55000): Adds a new column 'Salary' to the data frame.

3. data_df\$Age <- data_df\$Age + 5: Modifies the 'Age' column by incrementing each value by 5.

4. data_df\$Gender <- NULL: Removes the 'Gender' column from the data frame.

5. data_df[2, ]: Accesses the second row of the data frame.

6. print("Final Data Frame after operations:"), print(data_df): Prints the final data frame after performing all operations.