Python Pandas Grouping Mechanisms - Concatenating, Merging, Joining, Groupby

In this video, you’ll learn about Python Pandas Grouping Mechanisms: Concatenating, Merging, Joining, and Groupby. The Pandas library is essential to Machine Learning! You’ll learn how to concatenate DataFrames; how to merge DataFrames; how to join DataFrames; how to create a Groupby object and utilize methods such as count(), describe(), mean(), min(), max(), and std(). After watching this video and learning several Pandas grouping mechanisms, there’s an activity right below this description for you to try out on your own using the skills you learned here. Enjoy!

PANDAS GROUPING ACTIVITY:

Create a Pandas DataFrame that represents a restaurant scenario in which one column indicates the number of different dishes a person orders (this column should have some repeating values), another column that indicates the total price of that person’s meal, and a third column representing the name of that person. Then use the groupby object to sort by number of dishes and obtain the mean price. *Hint: to do this, revisit the example in my video!

TIMESTAMP:

00:00 Introduction & Recap of Last Video
00:20 Lesson Structure for Pandas Grouping Mechanisms Video
00:40 Concatenating DataFrames
06:06 Merging DataFrames
10:04 Joining DataFrames
12:07 Groupby Object and Methods
16:54 Recap of Current Video
17:51 Call-to-action: Pandas Grouping Mechanisms

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