1. PyCharm: A powerful Python IDE that provides intelligent code completion, error highlighting, and a variety of tools for debugging and testing. It offers integration with popular version control systems like Git and Mercurial, making it easy to collaborate on projects with other developers. PyCharm also supports web development with Django and Flask frameworks.
2. Pandas: A data manipulation library that provides high-performance data structures and tools for analyzing large datasets. With Pandas, you can easily load data from various sources, clean and transform it, and perform complex operations like grouping, filtering, and merging. Its intuitive API makes it a favorite among data scientists and analysts.
3. Requests: A simple yet powerful HTTP library for making requests to web servers in Python. With Requests, you can easily send GET or POST requests, handle cookies and sessions, and customize headers and parameters. It simplifies working with APIs and
2. Pandas: A data manipulation library that provides high-performance data structures and tools for analyzing large datasets. With Pandas, you can easily load data from various sources, clean and transform it, and perform complex operations like grouping, filtering, and merging. Its intuitive API makes it a favorite among data scientists and analysts.
3. Requests: A simple yet powerful HTTP library for making requests to web servers in Python. With Requests, you can easily send GET or POST requests, handle cookies and sessions, and customize headers and parameters. It simplifies working with APIs and