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in this tutorial, we'll explore three powerful libraries for data manipulation and visualization in python: numpy, pandas, and matplotlib. these libraries are widely used in the field of data science for tasks such as data analysis, cleaning, and visualization. let's get started!
numpy is a fundamental package for scientific computing with python. it provides support for large, multi-dimensional arrays and matrices, along with mathematical functions to operate on these arrays.
pandas is a data manipulation and analysis library. it provides data structures like series and dataframe, which are designed for efficient data manipulation.
matplotlib is a 2d plotting library for creating static, animated, and interactive visualizations in python.
this tutorial covers the basics of numpy, pandas, and matplotlib. you can explore each library further to leverage their advanced functionalities for more complex data science tasks. happy coding!
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