Python 3.5 + SciPy




Python 3.5 with NumPy and SciPy stack

This project can serves you as template for all kind numerical computation. You can analyze data with pandas, you can use linear algebra algorithms from scipy and process matices with numpy or use matplotlib for visualizations and plotting. This is good starting point for data science developent the most popular libraries are installed but if you need something custom you can easily install wiht use of pip, just type in console

!pip install library_name

If you are looking for more specialized template projects or projects for other languages just browse our repository Plon Team template projects.

SciPy is a Python-based ecosystem of open-source software for mathematics, science, and engineering.


  • NumPy
  • SciPy
  • Matplotlib
  • Sympy
  • pandas

The image is based on Ubuntu 16.04.

Libraries installed:

  • SciPy - is a set of open-source libraries for mathematics, science, and engineering
  • NumPy - is the fundamental package for scientific computing with Python. With NumPy you can use:
    • N-dimensional array object
    • sophisticated (broadcasting) functions
    • useful linear algebra, Fourier transform, and random number capabilities
  • Pandas - is an open source library providing high-performance, easy-to-use data structures for data analysis
  • Matplotlib - is a Python 2D plotting library which produces publication quality figures in a variety of hardcopy formats and interactive environments across platforms.
  • Sympy - is a Python library for symbolic mathematics. It aims to become a full-featured computer algebra system.
  • Numba -Numba gives you the power to speed up your applications with high performance functions written directly in Python. With a few annotations, array-oriented and math-heavy Python code can be just-in-time compiled to native machine instructions, similar in performance to C, C++ and Fortran, without having to switch languages or Python interpreters.


  • 1.0.0 Initial commit