I am assuming you have followed the previous tutorials in this short series on how to manipulate Pubmed references using Python (1, 2, 3). You should have a list variable called refs4 in your Python console that contains the cleaned references. Because we will be working with this cleaned version of the references from now on, it would be a
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Sometimes we would like to focus more on some data and less on others, but still provide a visual display. The matplotlib function gridspec allows subplots of unequal size to be plotted on the same figure. How this function can be applied will be demonstrated using simulated data. Let’s simulate some common probability distributions of different statistics using Python’s numpy.random
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In hypothesis testing, the number of samples needed to find an effect depends on the: size of the effect variability of the effect tolerance to reporting a false positive (Type I error) and probability of not reporting a false negative (1 – probability of Type II error) The following code uses the stats package in R to calculate sample size
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I am assuming you have followed the first and second tutorial in this short series. You should now have a list variable called refs2 in your Python console. If you inspected the first item in refs2 list, you will notice that it specifies the journal, volume and page information for the first reference. 1 ‘1. J Neurosci. 2015 Dec 9;35(49):16159-70.
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In the previous post, I explained how I recently had to sort through PubMed references to extract email addresses. As part of the tutorial, I had you download a sample text file containing 14 references, and we read the content of this file in Python. We are now going to continue cleaning the references to have them in a standardized
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My colleagues and I recently needed to identify all the PubMed references on a given topic and locate email addresses of the corresponding authors. The good news is that the Author information section of PubMed references contains one or more email addresses approximately half of the time. This meant that I could automate the extraction of these email addresses by
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Scientifically Sound 