From the course: Python Data Science Mistakes to Avoid
Unlock the full course today
Join today to access over 22,600 courses taught by industry experts or purchase this course individually.
Not organizing your directory - Python Tutorial
From the course: Python Data Science Mistakes to Avoid
Not organizing your directory
- [Instructor] Another common mistake to avoid when working with data is not organizing your directory. It's important to organize all the files in your directory into relevant categories, otherwise things can get messy and you may get confused about what each file is for and how the files relate to each other. Also, when you share your work with a teammate they can navigate through your directory more easily if it's categorized. To illustrate how to create subcategories in your directory, I will be walking through an example. Let's take this directory as an example. One of the first things you might notice is that there are several files in here and it looks cluttered. First, let's look at the file types. There are some IPython notebooks which have the .IPYNB extension, as well as some CSV or comma-separated values files which have the .CSV extension, and some text files, which have the .TXT extension. Next, let's take…
Practice while you learn with exercise files
Download the files the instructor uses to teach the course. Follow along and learn by watching, listening and practicing.
Contents
-
-
-
(Locked)
Not writing comments3m 11s
-
(Locked)
Not organizing your directory3m 11s
-
(Locked)
Not testing2m 36s
-
(Locked)
Not sharing data referenced in code1m 10s
-
Hard coding inaccessible paths3m 10s
-
Name clashing with Python standard library2m 26s
-
(Locked)
Not importing relevant libraries and modules43s
-
(Locked)
Naming vaguely1m 51s
-
(Locked)
-
-
-
-