Python pandas—Merge Exercises—Fictitious Names

Sometimes we learn best by doing. Unlike my other videos, I’ll be going through these exercises cold. Sometimes we’ll encounter ambiguous questions, and sometimes I'll be wrong. Learning from our mistakes can be a powerful teacher. So, it’s OK to be wrong now, because we’ll know how to avoid it next time when it counts. My hope is that you will learn by doing.

Why don’t you proceed through the linked exercises before we walk through them together?

This series can be viewed in tandem with my “An Opinionated Guide to pandas” video series (links below), but it’s not required. This series is beginner-friendly but aimed most directly at intermediate users.

This Learning by Doing is part of the pandas Opinionated Guide series:

The jupyter notebooks can be found here:

guipsamora’s exercises can be found here:

[arhataria]

Things I learned from this lecture:
pd.concat([data1, data2], axis = 'columns')

[jimmymesa]

At step 4, data1.append(data2) works as well but at step 5, pd.concat([data1, data2], axis='columns') is the only option.

[emirhan]

Hey Nathan, appreciate the tutorials! It appears that your Jupyter notebook autofills your code and can show the further information about the function you have written as well. For some reason, mine does not seem to do that for me. I tried using 'Tab' but that is nothing like yours. Can you help me out with this?

[correa.cristobal]

Hey Nathaniel, great tutorial videos, as you yourself said, the merge one is much more explainative than most out there (is that a word? If not it should!). Pandas merge 101 StackOverflow post is also of great help.
Q tho, do you have a way of reaching out to you? I'm learning by doing and been able to clean the data I need to work with, but ran into a merge issues that maybe you could help with.

[ranjithraghunathan]

where can i download the data set for your videos