...
In our notebook, we can see which modules are available by opening a new cell with the + button. In our cell box, set as “code” use the python import command, followed by a space, then hit tab to get a list of options. Hitting tab after import runs autocomplete options for the import command. This list of options has populated all modules available to us in our jupyter notebook: |
 |
New Cell in our Notebook
...
Since we appear to have a large number of packages available in this environment, we’ll import one we expect to be there.
In our bottom-most cell, add to the import command by typing an import for a common package used in mathematic and multi dimensional matrix computations - numpy.
...
Can we get a more comprehensive list?
Yes. By running help('modules')
Note: the numpy library isn’t available |
 Image Added |
...
In R:
...
We can confirm the package we need is unavailable:
Our output results in an error: |
 |
The error means this particular module is not available in the kernel we have loaded, despite being a commonly used software package for researchers and computations. While many packages were listed when we autocompleted an import command, most of them were installed as part of the jupyter installation and underlying OS environment. Most software we’d need to perform even more simple and common activities for our research would still need to be installed or made available somehow. What are our options?
|
...