This repository will go through detailed examples of how you can use the pandas and numpy librery to process and organise your data-set based on your needs .
Pandas is a Python library used for data manipulation and analysis. It provides data structures for efficiently storing and manipulating large datasets, as well as tools for reading and writing data to and from different file formats. Pandas is widely used in data science and machine learning for tasks such as data cleaning, data exploration, and data visualization. It is a powerful tool for working with tabular data, including data that is messy or incomplete. With pandas, you can easily filter, sort, group, and aggregate data, as well as perform statistical analysis and create visualizations.
You can download the librery by using the :
pip install pandas
NumPy is a Python library used for scientific computing and numerical analysis. It provides a powerful array object that allows you to efficiently store and manipulate large datasets in a compact and memory-efficient way. NumPy arrays are much faster than traditional Python lists, as they are implemented in C and optimized for numerical operations.
NumPy also provides a wide range of mathematical functions for working with arrays, including basic arithmetic operations, linear algebra, Fourier transforms, and random number generation. Additionally, it offers tools for integrating with other languages like C, C++, and Fortran, making it a popular choice for scientific computing and data analysis.
pip install numpy