Python: Numpy入門

NumpyはPythonの数値計算用ライブラリです。Numpyを使用することで、行列計算を高速に行うことができます。

任意の１次元配列を作成

import numpy as	np
data = [1, 2, 3, 4]
arr = np.array(data)
print(arr)
#[1 2 3 4]
print(type(arr))
#<class 'numpy.ndarray'>
print(arr.shape)
#(4,)

任意の2次元配列を作成

import numpy as np
data = [[1, 2, 3, 4], [5, 6, 7, 8]]
arr = np.array(data)
print(arr)
#[[1 2 3 4]
# [5 6 7 8]]
print(arr.shape)
#(2, 4)

要素がすべて０の配列を作成

import numpy as np
arr = np.zeros(10)
print(arr)
#[0. 0. 0. 0. 0. 0. 0. 0. 0. 0.]
print(arr.shape)
#(10,)
arr = np.zeros((3, 4))
print(arr)
#[[0. 0. 0. 0.]
# [0. 0. 0. 0.]
# [0. 0. 0. 0.]]
print(arr.shape)
#(3, 4)

要素がすべて１の配列を作成

import numpy as np
arr = np.ones(10)
print(arr)
#[1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]
print(arr.shape)
#(10,)
arr = np.ones((3, 4))
print(arr)
#[[1. 1. 1. 1.]
# [1. 1. 1. 1.]
# [1. 1. 1. 1.]]
print(arr.shape)
#(3, 4)

連続した数字の配列を作成

import numpy as	np
arr1 = np.arange(10)
print(arr1)
#[0 1 2 3 4 5 6 7 8 9]
print(arr1.shape)
#(10,)
arr2 = np.arange(5, 10)
print(arr2)
#[5 6 7 8 9]
print(arr2.shape)
#(5,)
arr3 = np.arange(2, 10, 2)
print(arr3)
#[2 4 6 8]
print(arr3.shape)
#(4,)

基本的な計算

import numpy as np
data1 = [[1, 2], [3, 4]]
arr1 = np.array(data1)
data2 = [[0, 1], [2, 3]]
arr2 = np.array(data2)
 
print(arr1)
#[[1 2]
# [3 4]]
print(arr1.shape)
#(2, 2)
print(arr2)
#[[0 1]
# [2 3]]
print(arr2.shape)
#(2, 2)
 
print(arr1 * arr2)
#[[ 0  2]
# [ 6 12]]
print(arr1 - arr2)
#[[1 1]
# [1 1]]
print(arr2 / arr1)
#[[0.         0.5       ]
# [0.66666667 0.75      ]]
print(arr1 ** 2)
#[[ 1  4]
# [ 9 16]]
print(arr1 > arr2)
#[[ True  True]
# [ True  True]]