NumPy Array Advanced Indexing Practice - Learn NumPy Series

This video is apart of a full learn NumPy series. Check out the playlist here:

In this one we'll get some more practice indexing numpy arrays with some advanced methods. Try the projects out too and let me know how you do them!

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Full code from the video:
import numpy as np

# Introduce arange function
print(array_a)

print(array_a)

# Return Every Last Value of Row with Negative Indexing
print(array_a[:,-1])

# boolean practice:
array_above_50 = array_a[array_a #greater than (YouTube Description doesn't allow angle brackets 50]
print(array_above_50)

#Indexing using Python Slices on one dimensional array
print(array_above_50[0:len(array_above_50):2])

#Taking Slice from Each Row of Array
print(array_a[:,0:5:2])

# Challenges Reverse each array row using negative indexing.
# index all values greater than 20 and less than 75, make everything else a value of zero and retain shape.

Packages (& Versions) used in this video:
Python 3.7
NumPy 1.17

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[yndolokoppavel]

hi, need help. how could i get this(replace two rows with ones)
array([[1, 1, 1],
[1, 1, 1],
[0, 4, 4],
[3, 3, 4],
[1, 3, 0]])

with a np.where function. I could not figure the right syntax for the condition

[yuliu]

Challenge one: matrix[:, ::-1], challenge two: matrix.where((matrix<75)&(matrix>20), matrix, 'value' ). Am I right?

[alexteka]

Challenge 1) print (array_a_reshape[:, -1:-4:-1])
Challenge 2)
betwen_25_and_75 = 20, array_a_reshape < 75)
result =
reshape_the_result = result.reshape(2, 5)
print (reshape_the_result)

I know I'm wrong with the 2nd challenge can anyone help me?