Suppose you have some big data files to analyse, and you would like to know roughly how long it takes to run the analysis. This is so that in future, if you had to re-run the analysis, you could gauge that it will take long enough to go get a coffee or work on another job while you wait for
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In a previous post we learned how to use matplotlib’s gridspec to make subplots of unequal size. gridspec is quite powerful, but can be a little complicated to use. This is especially true if you are coming to Python from Matlab. In the current post we learn how to make figures and subplots in a manner that will be more
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Many studies take repeated observations on subjects. For example, clinical trials record outcomes from subjects before and after treatments, and laboratory studies might record physiological outcomes from the same subjects over time. In a dataframe, when observations from each subject are written on one row and repeated observations are stored as different column variables, we say the data are in
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Scientific figures are at their most informative when they include the individual data used to calculate summary statistics such as means and standard deviations. Why is showing data important? As previously pointed out here and here, figures with means, standard deviations, standard errors, etc. can be misleading and conceal the nature of the underlying data. As highlighted in our previous
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My last two posts have shown how to perform an independent t-test in the R programming language and the Python programming language. For those of you who are familiar with statistics, you likely know that an independent t-test is equivalent to performing an one-way analysis of variance on the data. What you may not have realised is that both these
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Jupyter notebooks are a scientific computing development platform that can run many different programming languages, including Python via the interactive Python interpreter IPython. The key advantage in a notebook environment is that code can be sectioned into cells for testing while retaining all the interactive features of IPython, including magic commands. IPython magics are a specialised set of commands hosted
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Scientifically Sound 