Smartphone Specifications Data Cleaning and Exploratory Data Analysis

Repository Description: This project involves cleaning and analyzing smartphone specifications and prices data obtained from Kaggle. The dataset contains various attributes such as brand, model, price, RAM, ROM, battery, etc. The goal is to process the data, remove missing values, extract relevant information, and perform exploratory data analysis (EDA) to gain insights into the smartphone market in India.

Project Overview:

1. Data Cleaning:

   • Removed null ratings as they are the focus of the analysis and essential for potential ML projects involving rating prediction.
   • Manually corrected misaligned column values to ensure data integrity.

2. Data Extraction:

   • Extracted essential information like price, RAM, ROM, battery, etc. from complex strings using regular expressions (regex).
   • Formatted the data for easy analysis and visualization.

3. Exploratory Data Analysis (EDA):

   • Conducted EDA using Python libraries such as Pandas, Matplotlib, and Seaborn.
   • Explored top smartphone brands and popular models in the dataset.
   • Analyzed distributions of various attributes like price, RAM, ROM, and battery.
   • Examined correlations between attributes to identify potential patterns.

4. Results:

   • The cleaned dataset named "smartphone_specs_clean.csv" is ready for further analysis or ML projects.
   • EDA revealed valuable insights into the smartphone market, helping identify trends and patterns.
   • Before Cleanup:
   • After Cleanup:

Data and Libraries Used:

• Dataset Source: Kaggle - Smartphone Specifications and Prices in India
• Libraries: Pandas, Matplotlib, Seaborn, and Regular Expressions.

Conclusion: This data cleaning and exploratory analysis project provides a clear and organized dataset, enabling further in-depth analysis and the possibility of applying machine learning models for rating prediction or other predictive tasks. The EDA sheds light on the Indian smartphone market, assisting businesses, researchers, and enthusiasts in making informed decisions and understanding market trends.