1. Flask: A micro web framework for Python that is lightweight and easy to use. It allows developers to quickly build web applications with minimal code. With its built-in development server and debugger, Flask is perfect for prototyping and developing small to medium-sized projects. Its extensive documentation and active community make it a popular choice among developers.
2. Pandas: A powerful data manipulation library for Python that provides data structures like DataFrames and Series, as well as tools for cleaning, transforming, and analyzing data. Pandas is widely used in data science and machine learning projects due to its efficiency in handling large datasets. Its intuitive syntax and rich functionality make it a go-to tool for data wrangling tasks.
3. Matplotlib: A versatile plotting library for Python that allows users to create various types of visualizations, including line plots, bar charts, histograms, scatter plots, and more. Matplotlib's custom
2. Pandas: A powerful data manipulation library for Python that provides data structures like DataFrames and Series, as well as tools for cleaning, transforming, and analyzing data. Pandas is widely used in data science and machine learning projects due to its efficiency in handling large datasets. Its intuitive syntax and rich functionality make it a go-to tool for data wrangling tasks.
3. Matplotlib: A versatile plotting library for Python that allows users to create various types of visualizations, including line plots, bar charts, histograms, scatter plots, and more. Matplotlib's custom