I just finished the two missions in the command line in the Data Science path.
It seems quite useful and interesting.
But I am not quite sure how to use this in practice. I feel there needs to be a guided project where we work with a more real setup (files and datasets) like in the preceding missions?
Not sure how and when this is good to use over python. Or is there even things you can do with this which you can’t with python? it is not clear for me.
I understand this need. We did try to address it during the courses. For instance, when learning about
cat (in the second screen of the Text Processing mission), we illustrated a real world scenario.
With the material taught in the first two command-line courses (there are more), the applications to the real world are mostly text processing (which we learn about in the second course) and typical file system manipulations like copying files, and so on.
Other uses are described in the introduction to the first course and in this blog post. Some of this applications you can see later on in the Data Scientist in Python path, some are on our radar, but not in the works yet.
You can do everything with Python, but it isn’t always the best tool. You can also do everything in the command-line, but it isn’t always the best tool.
Interacting with the operating system is something that’s usually better to do with the command-line, simple text-processing as well (it runs faster). On the other hand, complex data cleaning is much easier with Python (pandas), for example.
I hope this helps.