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Diamond Price Analysis and EDA
Overview
This project explores a real world diamonds dataset with the goal of understanding how physical and qualitative characteristics influence market price.
The analysis includes data cleaning, descriptive statistics, visual explorations, comparisons between diamond types, and extraction of insights.
Main Research Question
How is the price of a diamond influenced by its different characteristics?
Research Sub-Questions
- How are diamond carat sizes distributed across the dataset?
- In which price ranges are most diamonds found?
- Which numeric features have the strongest influence on price?
- How does price vary between different size categories?
- What are the price differences between natural diamonds and lab grown diamonds?
Key numeric features include carat weight, dimensions (length, width, height), depth percent and table percent.
Categorical features include shape, color, clarity, polish, symmetry, girdle and type.
Data Cleaning
Several steps were taken to prepare the data:
- Removed three columns with many missing values: Fluorescence, Cut, Culet.
- Removed 3 duplicate rows.
- Removed rows with missing values in essential columns.
- Considered but avoided categorical encoding to keep data readable.
- Standardized the Type column to separate Natural and Lab grown.
Exploratory Data Analysis
Carat Weight Distribution
Price Distribution by Ranges
Feature Importance
Price Distribution by Size Categories
Natural vs Lab Grown Trend Lines (1 to 2 carat)
Key Insights
- Carat Weight is by far the strongest predictor of price.
- Most diamonds are around one carat and cost between 1000 and 2000 dollars.
- Price variation grows significantly with size.
- Lab grown diamonds are consistently cheaper than natural diamonds.
- The effect of carat weight on price is much weaker for lab grown diamonds compared to natural diamonds.
How to Load This Dataset
from datasets import load_dataset
dataset = load_dataset("your-username/diamond-prices")
Files Included
- dataset.csv
- EDA_notebook.ipynb
- README.md
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