Top 10 libraries of Data Science
Top 10 libraries of Data Science 1. Pandas Pandas is primarily used for data analysis, and it is one of the most commonly used Python libraries. It provides you with some of the most useful set of tools to explore, clean, and analyze your data. With Pandas, you can load, prepare, manipulate, and analyze all kinds of structured data. Machine learning libraries also revolve around Pandas DataFrames as an input. 2. NumPy NumPy is an open-source numerical Python library. NumPy contains a multi-dimensional array and matrix data structures. It can be utilised to perform a number of mathematical operations on arrays such as trigonometric, statistical, and algebraic routines. 3. Scikit-learn Scikit - learn is probably the most useful library for machine learning in Python. The sklearn library contains a lot of efficient tools for machine learning and statistical modeling including classification, regression, clu...