├── .gitignore
└── README.md


/.gitignore:
--------------------------------------------------------------------------------
 1 | # See https://help.github.com/articles/ignoring-files/ for more about ignoring files.
 2 | 
 3 | # dependencies
 4 | /node_modules
 5 | /.pnp
 6 | .pnp.js
 7 | 
 8 | # testing
 9 | /coverage
10 | 
11 | # next.js
12 | /.next/
13 | /out/
14 | 
15 | # production
16 | /build
17 | 
18 | # misc
19 | .DS_Store
20 | *.pem
21 | 
22 | # debug
23 | npm-debug.log*
24 | yarn-debug.log*
25 | yarn-error.log*
26 | 
27 | # local env files
28 | .env*.local
29 | .env
30 | 
31 | # vercel
32 | .vercel
33 | 
34 | # typescript
35 | *.tsbuildinfo
36 | next-env.d.ts
37 | 


--------------------------------------------------------------------------------
/README.md:
--------------------------------------------------------------------------------
 1 | # Used Cars Price Analysis
 2 | 
 3 | ## Overview
 4 | 
 5 | This repository contains a simple analysis of a dataset of used cars to identify the key factors influencing their prices in the second-hand market. The analysis is performed using Python with the help of pandas, numpy, and seaborn for visualization.
 6 | 
 7 | ## Dataset
 8 | 
 9 | The dataset (`used_cars.csv`) includes the following columns:
10 | 
11 | - `id`
12 | - `url`
13 | - `region`
14 | - `region_url`
15 | - `price`
16 | - `year`
17 | - `manufacturer`
18 | - `model`
19 | - `condition`
20 | - `cylinders`
21 | - `fuel`
22 | - `odometer`
23 | - `title_status`
24 | - `transmission`
25 | - `VIN`
26 | - `drive`
27 | - `size`
28 | - `type`
29 | - `paint_color`
30 | - `image_url`
31 | - `description`
32 | - `county`
33 | - `state`
34 | - `lat`
35 | - `long`
36 | - `posting_date`
37 | 
38 | ## Analysis Steps
39 | 
40 | 1. **Load and Explore Data:**
41 | 
42 |    - Load the dataset using pandas.
43 |    - Display basic information about the dataset.
44 |    - Select relevant columns for analysis.
45 | 
46 | 2. **Data Cleaning:**
47 | 
48 |    - Handle missing values (dropping or imputing, depending on the context).
49 |    - Convert necessary columns to the appropriate data types.
50 | 
51 | 3. **Exploratory Data Analysis:**
52 | 
53 |    - Visualize relationships between different variables and the target variable (price).
54 |    - Utilize scatter plots, box plots, etc., to understand patterns.
55 | 
56 | 4. **Insights:**
57 |    - Extract insights into how variables such as year, manufacturer, condition, cylinders, fuel, and odometer influence the price of used cars.
58 | 
59 | ## Usage
60 | 
61 | 1. Clone the repository:
62 | 
63 |    ```bash
64 |    git clone https://github.com/your-username/used-cars-analysis.git
65 |    cd used-cars-analysis
66 | 
67 |    ```
68 | 
69 | 2. Install the required dependencies:
70 | 
71 |    ```bash
72 |    pip install -r requirements.txt
73 | 
74 |    ```
75 | 
76 | ## Results
77 | 
78 | The analysis results are presented in various visualizations within the Jupyter notebook or script. These results can provide valuable insights for both buyers and sellers in the second-hand car market.
79 | 
80 | ## Contributing
81 | 
82 | If you find any issues or have suggestions for improvements, feel free to open an issue or submit a pull request.
83 | 
84 | ## License
85 | 
86 | This project is licensed under the MIT License - see the LICENSE file for details.
87 | 
88 | _Made with ❤️ by [Gimnath Perera](https://github.com/Gimnath-Perera)_
89 | 


--------------------------------------------------------------------------------