Python Pandas Series and Dataframes: Indexing, Selection, Booleans
In this video, you’ll learn all about Pandas Series and DataFrames. Pandas library is essential to Machine Learning! You’ll learn about how to convert a python list, numpy array, and dictionary into a Pandas Series; how to perform indexing and selection on a Pandas Series, how to create a DataFrame from scratch; how to perform indexing and selection on a Pandas DataFrame; and how to relate Booleans and DataFrames. Additionally, you’ll learn how to add columns to and drop columns from a DataFrame. After watching this video and learning the basics of Pandas Series and DataFrames, there’s an activity right below this description for you to try out on your own using the skills you learned here. Enjoy!
PANDAS SERIES AND DATAFRAMES ACTIVITY:
Use Python lists to create a DataFrame with two rows and three columns and filter this DataFrame so that it outputs only numbers larger than 2.
TIMESTAMP:
00:00 Introduction & Recap of Last Video
00:22 Lesson Structure for Numpy Array Basics Video
00:55 Turning python list, numpy array, and dictionary into Pandas Series
04:32 Performing indexing/selection on Pandas Series
05:17 Creating DataFrame from scratch
07:15 Performing indexing/selection on Pandas DataFrame
10:56 Relating Booleans and DataFrames
13:58 Recap of Current Video
14:36 Call-to-action: Pandas Series and DataFrames
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