python学习--Numpy1

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# Numpy包的使用数据分析最重要的库
# instance 1 向量加法
import numpy as np
def pythonsum(n):a = list(range(n))b = list(range(n))c = []for i in range(len(a)):a[i] = i**2b[i] = i**3c.append(a[i]+b[i])return cdef numpysum(n):a = np.arange(n)**2b = np.arange(n)**3c = a+breturn c
import sys
from datetime import datetime
import numpy as np
size = 1000
#np.arrange[n]产生的数组就相当于[0,1,'''''',n-1]
start = datetime.now()
c = pythonsum(size)
delta = datetime.now() - start
print("The last 2 elements of the sum",c[-2:])
print("PythonSum elapsed time in microseconds",delta.microseconds)start = datetime.now()
c = numpysum(size)
delta = datetime.now() - start
print("The last 2 elements of the sum",c[-2:])
print("NumpySum elapsed time in microseconds",delta.microseconds)a = np.arange(5)a
a.shape
print(a.shape)
#创建多维数组
m = np.array([np.arange(2), np.arange(2)])
print(m)
print(m.shape) # 2*2的数组
print(m.dtype) # 数据类型f = np.zeros(10)
print(f,'\n')t = np.zeros((3,6))
print(t)t1 = np.empty((2,3,2))
t2 = np.arange(15)
print(t1)
print(t2)a = np.array([[1,2],[3,4]])print("In: a")
print(a)print("In: a[0,0]")
print(a[1,1])print("In: arrange(7,dtype = uint16)")
print(np.arange(7,dtype=np.uint16))arr = np.array([1,2,3,4,5])
arr.dtype
float_arr = arr.astype(np.float64)
print(float_arr.dtype)print(a.dtype.byteorder)
print(a.dtype.itemsize)t = np.dtype([('name',np.str_,40),('numitems',np.int32),("price",np.float32)])
print(t)
print(t['name'])itemz = np.array([("Meaning of life DVD",42,3.14),("butter",13,2.72)],dtype=t)
print(itemz[0])
print(itemz[1])
#创建数组
a = list(range(10))
for i in range(len(a)):a[i]=int(input("Please put number: "))for i in a:print(i)

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