In this short post, we are going to learn how to turn the code from blog posts to Jupyter notebooks.
Tag: jupyter notebook
In this post, we will learn how to create a binder so that our data analysis, for instance, can be fully reproduced by other researchers. That is, here we will learn how to use a tool called Binder for reproducible research.
In previous posts, we have learned how to carry out data analysis (e.g., ANOVA) and data visualization (e.g., Raincloud plots) using Python. The code we have used have been uploaded in the forms of Jupyter Notebooks.
For users of R Statistical Environment;
Although this is great, we also need to make sure that we share our computational environment so that our code can be re-run and produce the same output. That is, to have a fully reproducible example, we need a way to capture the different versions of the Python packages we’re using.