Car Sales Data Analysis using R

📄 Description

This project analyzes car sales data from a large dataset containing over 550,000 observations and 16 variables. The analysis focuses on identifying trends in car sales, particularly by exploring the popularity of different car makes and models across various states, and examining the distribution of selling prices. The project leverages R for data manipulation and visualization.

🗄️ Files Included

• cars.csv: The dataset used for analysis, containing detailed information on car sales, including variables such as year, make, model, state, selling price, and more.
• cars.Rmd: The RMarkdown file containing the data analysis, including data cleaning, visualization, and statistical analysis.
• cars.html: The HTML output of the RMarkdown file, providing a nicely formatted and interactive version of the analysis.

📊 Key Analyses

• State-wise Analysis: Investigation into whether certain car makes or models are more popular in specific states.
• Price Distribution: Analysis of car sales based on selling price quantiles, and visualization of the number of cars sold in each price range.
• Transmission Analysis: Exploration of the distribution of transmission types (e.g., automatic vs. manual) across different states.
• Interactive Visualizations: Use of interactive plots to enhance data exploration, such as visualizing average selling prices and price distributions with additional details available on hover.

⚙️ How to Run the Analysis

1. Clone the Repository:

   git clone https://github.com/Oscaretz/Data_Analysis_R-Car_Sales.git

2. Install Dependencies: Make sure you have R installed, then install the necessary packages:

   install.packages(c(
  "skimr",
  "janitor",
  "ggplot2",
  "dplyr",
  "tidyverse",
  "tidyr",
  "tidytext",
  "hrbrthemes",
  "plotly",
  "knitr",
  "scales"
))

3. Run the RMarkdown File: Open cars.Rmd in RStudio and knit it to see the analysis in action. Alternatively, open cars.html for a ready-made version of the analysis.

💡Results and Insights

• A clear understanding of the most popular car makes in various states.
• Insights into the distribution of car sales across different price ranges.
• Identification of transmission preferences in top-selling states.
• Extra findings collected during the analysis.