numpy安装:
pip install numpy
numpy.ndarray基本使用:
import numpy as np
np.__version__ # 获取numpy的版本
# numpy.__version__ # name 'numpy' is not defined
nparr = np.array(list(range(10)))
nparr # array([0, 1, 2, 3, 4, 5, 6, 7, 8, 9])
type(nparr) # numpy.ndarray
nparr.dtype # 数据类型,WIN和IOS可能不一样
nparr[3] # 3
nparr[3] = 33
nparr # array([ 0, 1, 2, 33, 4, 5, 6, 7, 8, 9])
# nparr[5] = 'hello' ValueError: invalid literal for int() with base 10: 'hello'
nparr[5] = 55.8
nparr # array([ 0, 1, 2, 33, 4, 55, 6, 7, 8, 9])
nparr2 = np.array([1, 2, 3.0])
nparr2.dtype # dtype('float64')
nparr2 # array([1., 2., 3.])
nparr3 = np.array([1, 2, 3], dtype=float)
nparr3.dtype # dtype('float64')
numpy与python性能比较:
import numpy as np
def python_test(n):
a = [i**2 for i in range(n)]
b = [i**3 for i in range(n)]
c = []
for i in range(n):
c.append(a[i]+b[i])
return c
python_test(10)
def numpy_test(n):
a = np.arange(n) ** 2
b = np.arange(n) ** 3
c = a + b
return c
numpy_test(10)
%time res = python_test(10000000) # Wall time: 9.37 s
%time res = numpy_test(10000000) # Wall time: 275 ms
注:代码来自《Python全栈工程师特训班》课程