Python pandas—Vizualization—Online Retail

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:

[DrDemolition]

Had to come here because this was quite possibly the hardest exercise.

[karakol]

I love these and as a new user who is teaching myself python, this is very very helpful. Always look forward to your videos!!!

[JRay]

In retail, negative values usually comes from returns measured in a different time period. For example, December has positive sales for customers XYZ. In January, that same customer returns it. They don’t purchase anything else. This would shoe as negative for January.

[cordularaecke]

Thanks so much for this... very helpful to see the approach when it's not straightforward. Please make more of these videos.

[nacholupotti]

Thank you! I would love more videos like this, they are fantastic for learning!

[arhataria]

Step 6 ~ 8 were very confusing 😕
Things I learend from this lecture:
df['bins'] = pd.cut(df['a'], range(0, 50))

percentile99 = df['a'].quantile(.99)
df.loc[df['a'] >= percentile99]



plt.xlim(-30, 2000)
plt.ylim(-1, 80)

[ngoc]

It takes me so long to read the file and seems like it takes forever for me to process any line of code. Can anyone help? Thanks!

[mahmoudsharqawi]

hi, the code in your github is not same as in the video and i got lost in between! could you help me more?

[santharavi]

Can you do a tutorial on very large categorical data cleansing and finding the facts

[davidrosen]

where is your code and where the data set?

[yiykkbo]

Can I ask you some questions in private like email or on other social media, i have a project about the same thing but different questions