Grouping & Pivoting in Pandas

This video contains useful concepts when working with large datasets especially in the field of Data Science/Machine Learning in general or Explorative Data Analysis in specific.
Before moving to the main concepts we are using Data Cleaning/Manipulation and some slicing. The datetime transformer function of Pandas is really really useful and I am highly recommending to get comfortable with it :)
Grouping and Pivoting are very useful to get a better overview and to aggregate data. I am also doing some Visualizations to show you how to approach to larger datasets and getting a better overview.
The shown groupby function could also be used to apply certain functions (such as lambda) but I am not covering that in this video.

In the end of this video I am showing a trick to speed up your data selection and giving you a mini Data Science project ideal. Have fun solving it! :-)

As always if there are remaining questions I am very happy to help!

0:00-02:02 Intro
02:02- 03:39 String to date transformation
03:39-06:35 Grouping on one column
06:35- 08:32 Grouping on multiple columns
08:32-13:38 Pivoting/Pivot Tables in Pandas

#Pandas #DataScience #Python

[PassingTheDog]

Hey Algo. Decided to go to your old videos! Coming from R this is a very nice explanation :)!

[Baldur]

Thanks for the Video. Ive got the population from Wikipedia for every state and there is a 0.8339 correlation between population and number of deaths