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from IPython.display import display_pretty
import numpy as np

Numpy Reference

array object
ndarray
np.transpose permute the dimensions of an array
np.broadcast
np.expand_dims expand shape of an array
np.squeeze
np.asarray
- np.asanyarray
- np.asfarray parse array to float
- `np.asfortranarray
np.asmatrix
np.asscalar
np.require
np.column_stack
np.concatenate join a sequence of array together
np.dstack
np.hstack
np.vstack
np.array_split
- np.dsplit
- np.hsplit
- np.split
- np.vsplit
np.tile
np.repeat
np.delete
np.insert
np.append
np.resize
np.trim_zeros
np.unique
np.in1d
np.intersec1d
np.setdiff1d
np.setxor1d
np.union1d

sorting

np.sort
np.lexsort
np.argsort
np.ndarray.sort
np.msort
np.sort_complex
np.partition
np.argpartition
np.argmax
np.nanargmax
np.argmin
np.nanargmin

Indexing

np.argwhere
np.nonzero
np.flatnonzero
np.where
np.searchsorted return the index where element should be inserted in maintain order
np.extract
np.count_nonzero

np.column_stack



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a = [1, 2, 3]
b = [4, 5, 6]
np.column_stack((a, b))

np.concatenate



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a = np.array([[1,2], [3,4]])
b = np.array([[5,6]])
x1 = np.concatenate((a, b), axis=0)
x2 = np.concatenate((a, b.T), axis=1)
display_pretty(x1, x2)

np.dstack



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a = np.array((1, 2, 3))
b = np.array((4, 5, 6))
np.dstack((a, b))

np.tile



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a = np.array((0, 1, 2))
np.tile(a, 2)

np.sort



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a = np.array([[1, 5, 3], [2, 3, 1]])
np.sort(a, axis=0)

np.where



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cond = [[True, False], [True, True]]
x = [[1, 2], [3, 4]]
y = [[9, 8], [7, 6]]
a = np.where(cond, x, y)
display_pretty(a)

# equal to blow
for c, xv, yv in zip(cond, x, y):
    for c2, xv2, yv2 in zip(c, xv, yv):
        print(xv2 if c2 else yv2, end=', ')
print()

x = np.arange(9).reshape((3, 3))
display_pretty(x > 5)
b = np.where(x > 5)
display_pretty(b)

# frequently use
c = np.where(x > 3, x, -1)
display_pretty(c)