The course is free to attend for anyone at the LMB. Further details of the course are given below:
Python is a powerful and versatile programming language that can be used to analyse large and complex datasets. Whether you're collating results, performing statistical tests or investigating gene expression matrices, this course will equip you with the core skills to analyse biological data sets.
Topics include:
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Manipulating data using the pandas library
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Plotting figures
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Introducing Python libraries for mathematical and statistical analyses
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Documenting and sharing results with Jupyter Notebooks
By the end of the course, attendees should understand how to handle and investigate large datasets using Python. And although we can't cover every form of analysis in the course, the topics covered will make a good starting point for your own studies.
If there is an upcoming course scheduled, you can register here (you will need to be connected to the LMB intranet).
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Log in to your JupyterHub account via a Web Browser.
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Copy the link below into your browser and press Enter.
The course files should now be copied from this Git repository to your JupyterHub account.
If you are based at the LMB and want access to our JupyterHub server then please let me know and I shall set you up with an account.
If you are based outside the LMB and do not have access to the JupyterHub server then you will need to run the Jupyter Notebook file "Data_Analysis_with_Python_Course.ipynb" on your own computer. To do this, we recommend installing one of the following software products:
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Install Visual Studio Code. Then, open VS Code and from within VS Code install the relevant JupyterLab widgets.
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Or alternatively, work on one of Google's powerful cloud machines with Colab.
(If you wish to use a Python virtual environment to run the Jupyter Notebook, a requirements file can be found in the "ancillary_files" folder.)
Please feel free to email Steven Wingett for further details.