Python Packages for Data Science

Essential Python Packages for Data Science

. <span>Photo by <a href=";utm_medium=referral&amp;utm_content=creditCopyText">Hitesh Choudhary</a> on <a href=";utm_medium=referral&amp;utm_content=creditCopyText">Unsplash</a></span> ## Scientific Computing Libraries [Pandas]( Pandas is a fast, powerful, flexible and easy to use open source library. It allows for high-performance data structures and analysis tools. It is developed over the Numpy package and it is centered around the DataFrame object. [NumPy]( NumPy is an open source library that enables numerical computing with Python. You are able to utilize n-dimensional array objects and mathematical operations. [SciPy]( SciPy (pronounced “Sigh Pie”) is a Python-based ecosystem of open-source software for mathematics, science, and engineering. It is based on Numpy and provides packages for computation. ## Visualization Libraries [Matplotlib]( Matplotlib is a comprehensive library for creating static, animated, and interactive visualizations in Python. One can easily develop charts such as histograms, plots, bar charts, scatter plots, etc. [Seaborn]( Seaborn is a Python data visualization library based on Matplotlib. It provides a high-level interface for drawing attractive and informative statistical graphs such as heat maps. ## Algorithmic Libraries [Scikit-learn]( Scikit-learn is an open source python library that provides machine learning packages. It features various classification, regression, and clustering algorithms. It allows for simple and efficient tools for prediction data analysis. [Check Out the Article on Medium](