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with Terezija Semenski
Learn about NumPy, the most useful Python library for data science and numerical computing.
Take advantage of the power of NumPy
What you should know
Why should you use NumPy?
Python lists vs. NumPy arrays
Jupyter Notebook basics
Array types and conversions between types
Multidimensional arrays
Creating arrays from lists and other Python structures
Intrinsic NumPy array creation
Creating arrays filled with constant values
Finding the shape and size of an array
Adding, removing, and sorting elements
Copies and views
Reshaping arrays
Indexing and slicing
Joining and splitting arrays
Arithmetic operations and functions
Broadcasting
Aggregate functions
How to get unique items and counts
Transpose like operations
Reversing an array
Next steps