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NumPy

NumPy Cheat Sheet for Data Scientists
40 Methods used 95% of the time.
 • 
Avi Chawla
A Comprehensive NumPy Cheat Sheet Of 40 Most Used Methods
...that data scientists use 95% of the time.
 • 
Avi Chawla
2
40 NumPy Methods That Data Scientists Use 95% of the Time
Applying the Pareto's principle to NumPy Library.
 • 
Avi Chawla
A Major Limitation of NumPy Which Most Users Aren't Aware Of
..and here's how to address it.
Beware of This Unexpected Behaviour of NumPy Methods
...and here's how to counter it.
 • 
Avi Chawla
Speedup NumPy Methods 25x With Bottleneck
NumPy's methods are already highly optimized for performance.
 • 
Avi Chawla
Pandas and NumPy Return Different Values for Standard Deviation. Why?
Pandas assumes that the data is a sample of the population and that the obtained result can be biased towards the sample.
 • 
Avi Chawla
Speed-up Pandas Apply 5x with NumPy
While creating conditional columns in Pandas, we tend to use the 𝐚𝐩𝐩𝐥𝐲() method almost all the time.
 • 
Avi Chawla
Speed-up NumPy 20x with Numexpr
Numpy already offers fast and optimized vectorized operations.
 • 
Avi Chawla
An Elegant Way To Perform Matrix Multiplication
Matrix multiplication is a common operation in machine learning.
 • 
Avi Chawla
Difference Between Dot and Matmul in NumPy
The 𝐧𝐩.𝐦𝐚𝐭𝐦𝐮𝐥() and 𝐧𝐩.𝐝𝐨𝐭() methods produce the same output for 2D (and 1D) arrays.
 • 
Avi Chawla
Don't Print NumPy Arrays! Use Lovely-NumPy Instead.
We often print raw numpy arrays during debugging.
 • 
Avi Chawla
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