Python has grown quickly to become one of the most widely used programming languages. While it’s a powerful, multi-purpose language used for creating just about any type of application, it has become a go-to language for data science, rivaling even “R”, the longtime favorite language and platform for data science.
Python’s popularity for data-based solutions has grown because of the many powerful, opensource, data-centric libraries it has available. Some of these libraries include:
NumPy
A library used for creating and manipulating multi-dimensional data arrays and can be used for handling multi-dimensional data and difficult mathematical operations.
Pandas
Pandas is a library that provides easy-to-use but high-performance data structures, such as the DataFrame, and data analysis tools.
Matplotlib
Matplotlib is a library used for data visualization such as creating histograms, bar charts, scatter plots, and much more.
SciPy
SciPy is a library that provides integration, statistics, and linear algebra packages for numerical computations.
Scikit-learn
Scikit-learn is a library used for machine learning. It is built on top of some other libraries including NumPy, Matplotlib, and SciPy.
There are many other data-centric Python libraries and some will be introduced in future articles. More can be learned here: https://www.python.org/
The Data Community 