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Tag: reproducible

How to Use Binder and R for Reproducible Research

In a previous post, we learned how to use Binder and Python for reproducible research. Now we are going to learn how to create a Binder for our data analysis in R, so it can be fully reproduced by other researchers. More specifically, in this post we will learn how to use Binder for reproducible research.

Many researchers upload their code for data analysis and visualization using git (e.g., to GitHub, Gitlab).

No doubt, uploading your R scripts is great. However, we also need to make sure that we share the complete computational environment so that our code can be re-run and so that others can reproduce the results. That is, to have a fully reproducible example, we need a way to capture the different versions of the R packages we were using, at that particular time.

How to Use Binder and Python for Reproducible Research

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 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.