Programming is a useful skill that can help with a multitude of data analysis tasks, data visualization, statistical analysis, as well as machine learning. Learning a new programming language can sometimes be challenging, but still very worthwhile.
Here we present a series of Jupyter Notebooks that will walk you through the basics of Python. Follow these notebooks in order to get a sense of the syntax and logic of programming in Python. Follow the tabs in order above: Object Types, Programming Fundamentals, and Libraries. Each tab has a series concepts with a corresponding notebook. You can access all the notebooks in GitHub and Google Colab. You need to download Anaconda or Jupyter Notebooks (see below) in order to use the files in GitHub, which is recommended. However, if you want to start quickly, Google Colab, will work immediately through your Google Drive.
I recommend going through one Notebook a week. Don't worry about memorizing every function and technique. It is more important to understand how Python is structured and the logic behind it. You can always look up a function, if you forget.
Python is a popular, beginner-friendly programming language that is used in data science and can be extremely useful for research data analysis and data visualization. This programming language is a popular choice since it is open source and has a very supporting community that creates open source libraries for further functionality. The large ecosystem of libraries allows for easy adaptation of various applications. Documentation for Python can be found here.
Jupyter Notebook is an interactive coding environment used for writing and running Python code. It is a user interface that can be used to organize code. The markdown feature allows for notes and description of the code to make it easier to read and understand. Information about Jupyter Notebooks can be found here.
Anaconda is a distribution platform of Python, R, Jupyter Notebooks, and other packages like pandas and numpy. It is an organized software that makes it easy to get started with Python. Here is the website you can visit in order to download Anaconda.
Learning Python
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Python Data Science Handbook
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You can contact, Jacqueline Gunther, PhD, about any questions regarding this on-demand course.
The Bioinformatics Shared Resource has One-on-One Hands-On Training for Bioinformatics, Biostatistics, & Computational support mid-day on Thursdays. Additionally, they have office hours Thursday afternoons. To request an appointment, go to the Scientific Calendar Labwide emails for a scheduling link.