Leetcode-Questions-Analysis

The LeetCode Question Analysis is a Python-based project designed to help users analyze and gain insights into LeetCode problems. It allows users to track, categorize, and evaluate their progress, identify patterns in problem-solving, and optimize the preparation.

Data Extraction:

-- Automatically scrape or import problem data from LeetCode CSV export. -- Include details such as problem title, difficulty level, tags, acceptance rate, and frequency.

Visualization and Statistics:

-- Display problem-solving stats (e.g., total solved, difficulty distribution). -- Visualize progress using bar charts, pie charts, or line graphs. -- Highlight areas for improvement based on tag-based performance (e.g., Arrays, DP, Graphs).

Problem Categorization:

-- Group problems by difficulty (Easy, Medium, Hard). -- Filter unsolved or partially solved problems.

Performance Tracking:

-- Track the average time spent per problem. -- Analyze accuracy and revisit frequently failed problems. -- Show historical progress over time.

Search and Sort:

-- Implement search functionality to find problems by title, tags, or difficulty. -- Sort problems based on acceptance rate, frequency, or user-defined criteria. -- Export analysis data in formats such as CSV for further processing.

Python Libraries:

-- Data Handling: pandas, numpy -- Visualization: matplotlib, seaborn,

Analysis:

-- Perform data cleaning and aggregation. -- Generate visual and numerical insights.

Conclusion:

-- The LeetCode Question Analysis Tool is a powerful Python-based project designed to streamline and enhance the problem-solving journey for coding enthusiasts and professionals. -- By leveraging data analysis, visualization, categorization techniques and create meaningful insight from it.