Mod8HTML.Rmd

---
title: "Module 8"
author: "Chris Reddish"
date: "2025-03-03"
output: html_document
---
In this assignment, I worked with the "Assignment 6 Dataset.txt" file to perform data operations in R using the plyr package. The goal was to:

Import the dataset.
Calculate the mean of grades grouped by Sex.
Filter names containing the letter "i".
Write the outputs to files.

## 🔹 Step 1: Import Dataset & Calculate Mean of Grades by Sex
First, I imported the dataset into R using the read.table() function. Then, I used the ddply() function from the plyr package to calculate the average grade for each gender (Male and Female). Here's the code I used:
```{r}
# Load the plyr package
library(plyr)

# Import dataset
Student_assignment_6 <- read.table("Assignment 6 Dataset.txt", header = TRUE, sep = ",")

# View the full dataset
View(Student_assignment_6)
print(Student_assignment_6)

# Calculate mean grade by Sex
StudentAverage <- ddply(Student_assignment_6, "Sex", transform, Grade.Average = mean(Grade))

# View the dataset with the Grade.Average column
View(StudentAverage)
print(StudentAverage)

# Write results to CSV
write.table(StudentAverage, "Students_Gendered_Mean.csv", sep = ",", row.names = FALSE)

```
The "Students_Gendered_Mean.csv" file was created, containing the full dataset with an additional column called Grade.Average, which shows the average grade of each gender.

## Step 2: Filter Names Containing the Letter "i"
Next, I filtered the dataset to create a new subset containing only the student names with the letter "i" (case-insensitive). This was done using the subset() function along with grepl() to match the letter "i" or "I" in the "Name" column.
```{r}
# Filter names with the letter "i"
i_students <- subset(Student_assignment_6, grepl("[iI]", Student_assignment_6$Name))

# View the filtered dataset
View(i_students)
print(i_students)
```
## Step 3: Write Filtered Names to a CSV
Finally, I wrote the filtered names dataset to a CSV file called "Students_With_I.csv" using the write.table() function.
```{r}
# Write filtered names to CSV
write.table(i_students, "Students_With_I.csv", sep = ",", row.names = FALSE)

```
The "Students_With_I.csv" file was created, containing only the students whose names have the letter "i" in them.

# Reflection:
This assignment helped me practice:

Importing datasets.
Grouping data and calculating summary statistics using the plyr package.
Filtering data based on string matching.
Exporting results to CSV files.
By following these steps, I successfully produced two output files as required and reinforced my understanding of R's data manipulation functions.

# Files Created:
Students_Gendered_Mean.csv
Students_With_I.csv