## About these Guides

The Anaconda Python distribution includes the Spyder IDE, the JupyterLab IDE, the Python Programming Language and the most common libraries used for data science such as the numeric python library (numpy), the plotting library (matplotlib) and the Python and data analysis library (pandas). Python with these common data science libraries can be used as an open source replacement for expensive commercial products such as MATLAB for scientific computing and data science. This guide is geared at beginners who want to learn scientific computing (my own background being in biophysics).

## Anaconda Installation

## JupyterLab IDE

These guides were originally written on WordPress and based on the Spyder 4 IDE. I have since updated them to be JupyterLab Notebook files which you can view to read directly in your web browser or download and open in JupyterLab as an interactive notebook. The links below will take you to GitHub which will view the file in the browser with the option to download the folder.

### Python Programming Language

This is a beginner guide for starting with Python and coming to concepts with object orientated programming. You can view the Notebook files in a browser using the NBViewer link or download the folder containing the Notebook from GitHub to open in JupyterLab to interact with it.

should ensure you are comfortable with this before moving onto additional python libraries.

### The numpy Library

The numeric python library abbreviated numpy is the most commonly used python library. It is used for array manipulation.

### The pandas Library

The python and data analysis library abbreviated pandas is one of the most commonly used libraries in data science. This library allows for dataframe or spreadsheet manipulation or in other words is in essence the Excel of python.

The matplotlib Plotting Library

The matplotlib library is the python plotting and data visualization and is highly based on matlab/octave.

## Spyder IDE (Older Guides)

Spyder an acronym for Scientific python development environment is a Python IDE that has a user interface similar to Matrix Laboratory (MATLAB). MATLAB is a Commercial product commonly used in the physical sciences and engineering fields. Python and the Spyder IDE are open-source and can be freely downloaded using the Anaconda Python Distribution.

The Anaconda Python distribution includes the Spyder IDE, the JupyterLab IDE, the Python Programming Language and the most common libraries used for data science such as the numeric python library (numpy), the plotting library (matplotlib) and the Python and data analysis library (pandas). Python with these common data science libraries can be used to replace the commercial product MATLAB for most applications.

This guide is geared at beginners who want to learn scientific computing (my own background being in biophysics) and those that are transferring from MATLAB. In other words, this guide looks specifically at using Spyder as an open-source alternative to MATLAB.

## Python Programming Language

In this guide I discuss the Spyder 4 user interface and how to use the core python library. You should ensure you are comfortable with this before moving onto additional python libraries.

## Core Python Libraries for Data Science

### The numpy Library

The numeric python library abbreviated numpy is the most commonly used python library. It is used for array manipulation.

### The pandas Library

The python and data analysis library abbreviated pandas is one of the most commonly used libraries in data science. This library allows for dataframe or spreadsheet manipulation or in other words is in essence the Excel of python.

### The matplotlib Plotting Library

The matplotlib library is the python plotting and data visualization and is highly based on matlab/octave.

## Machine Learning

### The SciKit Learn Library (sklearn)

The sklearn library can be used for machine learning applications. I demonstrate some of the fundamentals of machine learning using the standard example datasets.

## General User Interface (GUI)

### The Python Quasar toolkit 5 (PyQt5)

The Python Quasar toolkit 5 library abbreviated as PyQt5 is used to create an interactive General User Interface (GUI). In this guide I reinforce the basics behind object orientated programming and then look at creating some basic GUIs.