Core Scientific PackagesΒΆ
This section introduces you to the core numerical libraries in Python. These libraries are essential for scientific computing in a Python environment.
NumPy introduces arrays to python. Numpy arrays are an essential tool for scientific computing in Python. Arrays are an efficient way to perform computations on large datasets. A wide variety of functions for manipulating arrays and performing linear algebra calculations are included in NumPy.
To install NumPy in your python environment simply run:
conda install numpy
SciPy contains a broad range of useful tools for scientific computing including optimization functions, mathematical transforms, distance calculations, statistical tools, and image processing applications.
To install SciPy in your python environment simply run:
conda install scipy
Pandas brings the feel of spreadsheets to your python computing environment! Pandas provides powerful, easy-to-use data structures and analysis tools to help you handle your datasets. Pandas makes importing, navigating, and manipulating datasets easy!
To install pandas in your python environment simply run:
conda install pandas