The undertaken project focused on developing a Pokémon database system, commonly referred to as a Pokédex, by employing Python and PostgreSQL. The primary goal was to compile and store comprehensive information about diverse Pokémon species, sourced from https://pokemondb.net/, and present this data in a structured database. This initiative served as a personal project, aiming to highlight my competencies in SQL, Python, and Data Analysis. Python was selected as the primary programming language for project implementation. The uti- lization of libraries such as Beautiful Soup and Requests facilitated web scraping of Pokémon data from the designated website, enabling the extraction of details like Pokémon names, types, abilities, and stats. The integration of Pandas, a potent data manipulation library in Python, played a pivotal role in refining and processing the scraped data. It provided the means to convert raw web data into a structured format suitable for insertion into the database. For the creation and management of the Pokémon database, PostgreSQL, a robust relational database management system, was employed. SQL was instrumental in defining the schema, es- tablishing tables, and inserting data, ensuring that the information was well-organized and easily retrievable through queries. To summarize, this project served as a demonstration of my proficiency in Python, expertise in data manipulation using Pandas, and competence in SQL-based database management. It represented a valuable opportunity to enhance skills in web scraping, data cleaning, and database design, underscoring the developer’s capabilities in these critical domains.
- Which type has more pokemon?
- Which region has introduced more pokemon?
- Top 10 strongest and weakest non legenday pokemon?(Excludes mega evolve)
- Top 10 weakest and strongest pokemon from each type? (Excludes mega evolve and legendary pokemons)
- Top 5 strongest legendary pokemon? (Excludes mega evolve)