python numpy 基本操作
阿新 • • 發佈：2018-11-14
首先匯入import模組
import numpy as np
建立list和matrix
vector = np.array([5, 10, 15, 20]) # list
matrix = np.array([[5, 10, 15], [20, 25, 30], [35, 40, 45]]) # matrix
print vector
print matrix
#列印輸出
[ 5 10 15 20]
[[ 5 10 15]
[20 25 30]
[35 40 45]]
求取矩陣的各種屬性
print(vector.shape) #列印list形狀
print(matrix. 提取矩陣元素
vector = numpy.array([5, 10, 15, 20])
print(vector[0:3])
#列印輸出
[ 5 10 15]
matrix = numpy.array([
[5, 10, 15],
[20, 25, 30],
[ ==操作
vector = numpy.array([5, 10, 15, 20])
vector == 10
#列印輸出
array([False, True, False, False], dtype=bool)
matrix = numpy.array([
[5, 10, 15],
[20, 25, 30],
[35, 40, 45]
])
matrix == 25
array([[False, False, False],
[False, True, False],
[False, False, False]], dtype=bool)
vector = numpy.array([5, 10, 15, 20])
equal_to_ten = (vector == 10)
print equal_to_ten
print(vector[equal_to_ten])
#列印輸出
[False True False False]
[10]
matrix = numpy.array([
[5, 10, 15],
[20, 25, 30],
[35, 40, 45]
])
second_column_25 = (matrix[:,1] == 25)
print second_column_25
print(matrix[second_column_25, :])
[False True False]
[[20 25 30]]
vector = numpy.array([5, 10, 15, 20])
equal_to_ten_and_five = (vector == 10) & (vector == 5)
print equal_to_ten_and_five
[False False False False]
vector = numpy.array([5, 10, 15, 20])
equal_to_ten_or_five = (vector == 10) | (vector == 5)
print equal_to_ten_or_five
[True True False False]
vector = numpy.array([5, 10, 15, 20])
equal_to_ten_or_five = (vector == 10) | (vector == 5)
vector[equal_to_ten_or_five] = 50
print(vector)
[50 50 15 20]
matrix = numpy.array([
[5, 10, 15],
[20, 25, 30],
[35, 40, 45]
])
second_column_25 = matrix[:,1] == 25
print second_column_25
matrix[second_column_25, 1] = 10
print matrix
[False True False]
[[ 5 10 15]
[20 10 30]
[35 40 45]]
改變矩陣元素資料型別 astype
vector = numpy.array(["1", "2", "3"])
print vector.dtype
print vector
vector = vector.astype(float)
print vector.dtype
print vector
#列印輸出
|S1
['1' '2' '3']
float64
[ 1. 2. 3.]
sum， axis = 0 列相加， axis = 1 行相加
vector = numpy.array([5, 10, 15, 20])
vector.sum()
50
matrix = numpy.array([
[5, 10, 15],
[20, 25, 30],
[35, 40, 45]
])
matrix.sum(axis=1)
array([ 30, 75, 120])
matrix = numpy.array([
[5, 10, 15],
[20, 25, 30],
[35, 40, 45]
])
matrix.sum(axis=0)
array([60, 75, 90])
reshape（變形），shape（檢視陣列形狀），ndim（維度），dtype（檢視資料型別），size（總的元素個數），zeros（全0矩陣陣列），ones（全1矩陣陣列）
a = np.arange(15).reshape(3, 5) #arange生成0-14間隔為1的陣列
a
array([[ 0, 1, 2, 3, 4],
[ 5, 6, 7, 8, 9],
[10, 11, 12, 13, 14]])
a.shape
(3, 5)
a.ndim
2
a.dtype.name
'int32'
a.size
15
np.zeros ((3,4))
array([[ 0., 0., 0., 0.],
[ 0., 0., 0., 0.],
[ 0., 0., 0., 0.]])
np.ones( (2,3,4), dtype=np.int32 )
array([[[1, 1, 1, 1],
[1, 1, 1, 1],
[1, 1, 1, 1]],
[[1, 1, 1, 1],
[1, 1, 1, 1],
[1, 1, 1, 1]]])
np.arange(a,b,n)生成間隔為n，資料範圍為[a,b)的序列
np.arange( 10, 30, 5 )
array([10, 15, 20, 25])
np.arange( 0, 2, 0.3 )
array([ 0. , 0.3, 0.6, 0.9, 1.2, 1.5, 1.8])
np.arange(12).reshape(4,3)
array([[ 0, 1, 2],
[ 3, 4, 5],
[ 6, 7, 8],
[ 9, 10, 11]])
np.random.random(a,b)（生成0-1之間矩陣大小為(a,b)隨機數）
np.linspace(a,b,num)（生成a-b之間等間隔的num個數據）
np.random.random((2,3))
array([[ 0.40130659, 0.45452825, 0.79776512],
[ 0.63220592, 0.74591134, 0.64130737]])
from numpy import pi
np.linspace( 0, 2*pi, 100 )
array([ 0. , 0.06346652, 0.12693304, 0.19039955, 0.25386607,
0.31733259, 0.38079911, 0.44426563, 0.50773215, 0.57119866,
0.63466518, 0.6981317 , 0.76159822, 0.82506474, 0.88853126,
0.95199777, 1.01546429, 1.07893081, 1.14239733, 1.20586385,
1.26933037, 1.33279688, 1.3962634 , 1.45972992, 1.52319644,
1.58666296, 1.65012947, 1.71359599, 1.77706251, 1.84052903,
1.90399555, 1.96746207, 2.03092858, 2.0943951 , 2.15786162,
2.22132814, 2.28479466, 2.34826118, 2.41172769, 2.47519421,
2.53866073, 2.60212725, 2.66559377, 2.72906028, 2.7925268 ,
2.85599332, 2.91945984, 2.98292636, 3.04639288, 3.10985939,
3.17332591, 3.23679243, 3.30025895, 3.36372547, 3.42719199,
3.4906585 , 3.55412502, 3.61759154, 3.68105806, 3.74452458,
3.8079911 , 3.87145761, 3.93492413, 3.99839065, 4.06185717,
4.12532369, 4.1887902 , 4.25225672, 4.31572324, 4.37918976,
4.44265628, 4.5061228 , 4.56958931, 4.63305583, 4.69652235,
4.75998887, 4.82345539, 4.88692191, 4.95038842, 5.01385494,
5.07732146, 5.14078798, 5.2042545 , 5.26772102, 5.33118753,
5.39465405, 5.45812057, 5.52158709, 5.58505361, 5.64852012,
5.71198664, 5.77545316, 5.83891968, 5.9023862 , 5.96585272,
6.02931923, 6.09278575, 6.15625227, 6.21971879, 6.28318531])
numpy數學運算
a = np.array( [20,30,40,50] )
b = np.arange( 4 )
print a
print b
c = a-b
print c
b**2
print b**2
print a<35
[20 30 40 50]
[0 1 2 3]
[20 29 38 47]
[0 1 4 9]
[True True False False]
A = np.array( [[1,1],
[0,1]] )
B = np.array( [[2,0],
[3,4]] )
print A
[[1 1]
[0 1]]
print B
[[2 0]
[3 4]]
print A*B # 矩陣對應元素相乘
[[2 0]
[0 4]]
print A.dot(B) # 矩陣相乘
[[5 4]
[3 4]]
print np.dot(A, B)
[[5 4]
[3 4]]
np.sqrt （開根號），np.floor（向下取整），ravel（拉伸為一維），.T（轉置）
a = 10*np.random.random((3,4))
print a
[[ 2.82298425 7.14369753 8.69695365 3.25215523]
[ 4.05086915 6.52158344 7.14745109 3.37805305]
[ 5.08484091 7.04078148 7.7110627 4.13750478]]
a = np.floor(a)
print a
[[ 2. 7. 8. 3.]
[ 4. 6. 7. 3.]
[ 5. 7. 7. 4.]]
print a.ravel()
[ 2. 7. 8. 3. 4. 6. 7. 3