Storing Datasets
Datasets and the corresponding Jupyter Notebook can be stored in a folder on GitHub. You can then create an interact link for the entire folder. When students click this link, the entire folder will appear on their JupyterHub account.
You can store the data on an online host such as Box, Google Drive, or even GitHub. You can then include a cell with this download_dataset function or have students read the data directly via URL. The read_table function for the Table data structure supports URLs.
Contact us on Piazza if you want your data to be saved in shared folder on JupyterHub directly. Notebooks stored on JupyterHub will be able to access this data. This is the preferred method for large datasets.
Students can directly upload data files that you provide them onto their JupyterHub accounts. This method can get messy if notebooks expect the data to be stored at a certain filepath and students upload the files to a different location. Therefore, we recommend using the other methods listed on this page.
For datasets on the order of GB, we recommend that you contact us regarding hosting a shared copy on JupyterHub. You can also use use outside hosts and provide students with a URL to the data, which they can then read into a Table or other data structure.