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It allows users to track, categorize, and evaluate their progress, identify patterns in problem-solving, and optimize the preparation.\n\n\n### Data Extraction:\n\n-- Automatically scrape or import problem data from LeetCode CSV export.\n-- Include details such as problem title, difficulty level, tags, acceptance rate, and frequency.\n\n### Visualization and Statistics:\n\n-- Display problem-solving stats (e.g., total solved, difficulty distribution).\n-- Visualize progress using bar charts, pie charts, or line graphs.\n-- Highlight areas for improvement based on tag-based performance (e.g., Arrays, DP, Graphs).\n\n### Problem Categorization:\n\n-- Group problems by difficulty (Easy, Medium, Hard).\n-- Filter unsolved or partially solved problems.\n\n### Performance Tracking:\n\n-- Track the average time spent per problem.\n-- Analyze accuracy and revisit frequently failed problems.\n-- Show historical progress over time.\n\n### Search and Sort:\n\n-- Implement search functionality to find problems by title, tags, or difficulty.\n-- Sort problems based on acceptance rate, frequency, or user-defined criteria.\n-- Export analysis data in formats such as CSV  for further processing.\n\n### Python Libraries:\n\n-- Data Handling: pandas, numpy\n-- Visualization: matplotlib, seaborn, \n\n### Analysis:\n-- Perform data cleaning and aggregation.\n-- Generate visual and numerical insights.\n\n### Conclusion:\n-- 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.\n-- By leveraging data analysis, visualization, categorization techniques and create meaningful insight from it. \n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2FMadhuresh2011%2FLeetcode-Questions-Analysis-Using-Python","html_url":"https://awesome.ecosyste.ms/projects/github.com%2FMadhuresh2011%2FLeetcode-Questions-Analysis-Using-Python","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2FMadhuresh2011%2FLeetcode-Questions-Analysis-Using-Python/lists"}