Software CarpentrySoftware Carpentry has contributed to the materials listed below.
Course lessons are developed as a part of a course curriculum. They teach specific learning objectives associated with data and scientific programming. Software Carpentry has contributed to the following lessons:
This lesson teaches you how to wrangle data (e.g. subselect, update, and combine) with pandas dataframes.
This lesson walks you through using indexing to select data from pandas dataframes.
This lesson walks you through describing, manipulating, and plotting pandas dataframes.
This lesson walks you through importing tabular data from .csv files to pandas dataframes.
This lesson walks you through manipulating, summarizing and plotting numpy arrays.
This lesson walks you through importing text data from .txt and .csv files into numpy arrays.
Version control allows you to track and manage changes to your files. Learn benefits of version control for scientific workflows and how git and GitHub.com support version control.
GitHub can be used to store and access files. Learn how to create a copy of files on Github (forking) and to use the Terminal to download the copy to your computer (cloning). You will also learn how to to update your forked repository with changes made in the original Github repository.
Learn how to fork a repository using the GitHub website.
Learn what version control is, and how Git and GitHub are used in a typical version control workflow.
Learn how to work with function arguments in the R programming language..
This lesson introduces the function environment and documenting functions in R. When you run a function intermediate variables are not stored in the global environment. This not only saves memory on your computer but also keeps our environment clean, reducing the risk of conflicting variables.
Learn how to write a function in the R programming language.
This lesson will cover the basic principles of using functions and why they are important.
Learn how to create a well-organized working directory to store your course data.
Learn what a package is in R and how to install packages to work with your data.
Learn how to work with R using the RStudio application.
Learn how to download and install R and RStudio on your computer.