spike2py: a python package to process data collected with spike2
Category Archives: Python
Talk Python – Interview about data science
Earlier this year I was a guest on Talk Python , a wonderful podcast on my favourite programming language. Did you come into Python from a computational science side of things? Were you just looking for something better than Excel or Matlab and got pulled in by all the Python has to offer? That’s great! But following that path often
Read morePython virtual environments for scientists with conda part 4
In our previous post we learned how to verify what Python virtual environments were installed on our machine and what Python packages they contained. We also learned how to delete unwanted environments. In this post we are going to learn how to share our virtual environment with others. This is incredibly useful in this day and age of research reproducibility.
Read morePython virtual environments for scientists with conda part3
In our first post we learned about Python virtual environments and how to use conda to create and manage them. In our second post, we learned how to install packages that were not directly accessible from the command conda install. Specifically, we learned about conda channels hosted at https://anaconda.org as well as pip, both of which can be used to
Read morePython virtual environments for scientists with conda part2
In our previous post we learned about Python virtual environments and how conda makes it easy for us as scientists to use virtual environments and access hundreds of useful packages. Despite the number of packages directly available through conda, not all packages can be downloaded this way. In this post we will learn how to add such packages to our
Read morePython virtual environments for scientists with conda
I have been coding with Python for several years and I only recently took the time to learn about Python environments. Now that I understand them, I can see why they are so useful, especially in this day and age of large team collaborations, research reproducibility, and sharing data and code when research results are published. The purpose of this
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