全世界はすべて見ることが好きです:numpyの基礎知識は必ず知っています!
45361 ワード
import numpy as np
#
array1=np.array([1,2,3,4,5])
#print(array1)
#
array2=np.array([[1,2,3,4],[4,5,6,7],[5,6,7,8]])
print(array2)
#
print(array2.shape)
#
print(array2.dtype)
#
print(array2.size)
# ( )
print(array2.itemsize)
#
print(array2.ndim)
# shape
array2.shape=4,3
print(array2)
# arrange
array3=np.arange(1,10,2)
print(array3)
# linspace ,
array4=np.linspace(1,10,50)
print(array4)
# logspace ，
array5=np.logspace(1,10,50)
print(array5)
# zeros ， 0
array6=np.zeros((2,3))#
print(array6)
# eyes ，
array7=np.eye(5)
print(array7)
# diag
array8=np.diag([1,2,3,4])
print(array8)
"""
[[1 0 0 0]
[0 2 0 0]
[0 0 3 0]
[0 0 0 4]]
"""
# ones 1
array9=np.ones(5)
print(array9)
array91=np.ones([2,4])
print(array91)
#
#
print(np.float64(64))
#
print(np.int32(12.2))
# bool,
print(np.bool(8))#True
print(np.bool(0))#False
# bool ，
print(np.int32(True))#1
print(np.int32(False))#0
# 。 ， 40
# ， 64 ， 64
df=np.dtype([('name',np.str_,40),('count',np.int64),('price',np.float64)])
print(df)
"""
[('name', '
#
print(df['name'])
#
items1=np.array([('apple',100,5),('pear',50,8)])
items2=np.array([('apple',100,5),('pear',50,8)],dtype=df)
print(items1)
"""
[['apple' '100' '5']
['pear' '50' '8']]
"""
print(items2)
"""
[('apple', 100, 5.) ('pear', 50, 8.)]
"""
# 0 1
print(np.random.randint(100))#100
print(np.random.randint(2,10,size=(2,5)))#2 5 2 10
# 0 1
print(np.random.random(100))
# 0 1
print(np.random.rand(100))#100
print(np.random.rand(10,5))#10 5
#
print(np.random.randn(10))#10
print(np.random.randn(5,5))#5 5
#
arry=np.arange(1,10)
#print(arry)#[1 2 3 4 5 6 7 8 9]
print(arry[0])#1
print(arry[1:3])#[2 3]
print(arry[:5])#[1 2 3 4 5]
print(arry[-1])#9
print(arry[:-1])#[1 2 3 4 5 6 7 8]
print(arry[::-1])#[9 8 7 6 5 4 3 2 1]
print(arry[-1:])#[9]
print(arry[2::-1])#[3 2 1]
#
arry[2:4]=100,101
print(arry)#[ 1 2 100 101 5 6 7 8 9]
print(arry[5:1:-2])#[ 6 101]
print(arry[5:-1:2])#[6 8]
print(arry[5:-2:2])#[6]
#
arr = np.array ( [ [1, 2, 3, 4, 5],[4, 5, 6, 7, 8], [7, 8, 9, 10, 11] ] )
print(arr)
print(arr[0,3:5])#[4 5]
print(arr[1:,2:])# (hang,lie)
"""
[[ 6 7 8]
[ 9 10 11]]
"""
print(arr[:,2])#[3 6 9] 1 3
#
print(arr[[(0,1,2),(1,2,3)]])#[ 2 6 10]
print(arr[1:,(0,2,3)])
"""
[[ 4 6 7]
[ 7 9 10]]
"""
#
ar=np.arange(12)
print(ar)
print(ar.reshape(3,4))
#ravel
print(ar.reshape(3,4).ravel())
#flatten
print(ar.reshape(3,4).flatten())# 'C'
print(ar.reshape(3,4).flatten('F'))#
#
#ar1=np.array([1,2,3,4])
#ar2=np.array([[1,2,3,4],[2,3,4,5],[3,4,5,6]])
#
#print(np.hstack((ar1,ar2)))#
#print(np.concatenate((ar1,ar2),axis=1))#
#
#print(np.vstack((ar1,ar2)))
#print(np.concatenate((ar1,ar2),axis=0))
"""
[[1 2 3 4]
[1 2 3 4]
[2 3 4 5]
[3 4 5 6]]
"""
#
#
a=np.arange(16).reshape(4,4)
print(a)
print(np.hsplit(a,2))
"""
[array([[ 0, 1],
[ 4, 5],
[ 8, 9],
[12, 13]]), array([[ 2, 3],
[ 6, 7],
[10, 11],
[14, 15]])]
"""
#
print(np.vsplit(a,2))
"""
[array([[0, 1, 2, 3],
[4, 5, 6, 7]]), array([[ 8, 9, 10, 11],
[12, 13, 14, 15]])]
"""
#numpy
# mat
mat1=np.mat("3 2 1;6 5 4;9 8 7")
print(mat1)
print(mat1.dtype)
"""
[[3 2 1]
[6 5 4]
[9 8 7]]
"""
# matrix
matrix1=np.matrix([[1,2,3],[4,5,6],[7,8,9]])
#print(matrix1)
"""
[[1 2 3]
[4 5 6]
[7 8 9]]
"""
# bmat
#print(np.bmat(("mat1,matrix1;mat1,matrix1")))
"""
[[3 2 1 1 2 3]
[6 5 4 4 5 6]
[9 8 7 7 8 9]
[3 2 1 1 2 3]
[6 5 4 4 5 6]
[9 8 7 7 8 9]]
"""# print(np.bmat(("mat1,mat1;matrix1,matrix1")))
"""
[[3 2 1 3 2 1]
[6 5 4 6 5 4]
[9 8 7 9 8 7]
[1 2 3 1 2 3]
[4 5 6 4 5 6]
[7 8 9 7 8 9]]
"""
#
#
matrix_new=matrix1*3#
#print(matrix_new)
"""
[[ 3 6 9]
[12 15 18]
[21 24 27]]
"""
#
matrix_new1=matrix1*matrix1
#print(matrix_new1)
"""
[[ 30 36 42]
[ 66 81 96]
[102 126 150]]
"""
#
matrix_new2=np.multiply(matrix1,matrix1)
#print(matrix_new2)
"""
[[ 1 4 9]
[16 25 36]
[49 64 81]]
"""
#
#print(matrix1.T)#
"""
[[1 4 7]
[2 5 8]
[3 6 9]]
"""
#print(matrix1.I)#
"""
[[ 3.15251974e+15 -6.30503948e+15 3.15251974e+15]
[ -6.30503948e+15 1.26100790e+16 -6.30503948e+15]
[ 3.15251974e+15 -6.30503948e+15 3.15251974e+15]]
"""
#print(matrix1.H)#
"""
[[1 4 7]
[2 5 8]
[3 6 9]]
"""
#print(matrix1.A)# 2
"""
[[1 2 3]
[4 5 6]
[7 8 9]]
"""
#ufnc （universal function）， 。
#x=np.array( [1,3,5] )
#y=np.array( [2,4,3] )
#print(np.any(x==y))
"""
False
"""
#x=np.array( [1,3,5] )
#y=np.array( [2,4,3] )
#print(np.all(x==y))
"""
False
"""
#x=np.array([[1,3,5],[1,1,1],[2,2,2],[3,3,3]])
#y=np.array([2,4,3])
#print(x)
#print(y)
#print(x+y)
"""
[[3 7 8]
[3 5 4]
[4 6 5]
[5 7 6]]
"""
#x=np.array([[0,0,0],[1,1,1],[2,2,2],[3,3,3]])
#y=np.array([1,2,3,4]).reshape((4,1))
#print(x)
#print(y)
#print(x+y)
"""
[[1 1 1]
[3 3 3]
[5 5 5]
[7 7 7]]
"""
#numpy
"""
save 。 np.save ("../tmp/save_arr "
, arr)
Ø load 。 np.load("../tmp/ save_arr.npy")
Ø savez 。 np.savez('../tmp/savez_arr'
,arr1,arr2)
Ø ， 。
"""
#x=np.array([[0,0,0],[1,1,1],[2,2,2],[3,3,3]])
#y=np.array([1,2,3,4]).reshape((4,1))
#print(x)
#print(y)
#np.save("C:/Users/lenovo/Desktop/numpy .txt",x)
#load_data=np.load("C:/Users/lenovo/Desktop/numpy .txt")
#
#a=np.array([3,2,6,4,5])
#b=np.array([50,30,40,20,10,])
#c=np.array([400,300,600,100,200])
#d=np.argsort((a,b,c))#argsort 。 arr.argsort()
#print(d)
"""
[[1 0 3 4 2]
[4 3 1 2 0]
[3 4 1 0 2]]
"""
#d=np.lexsort((a,b,c))#lexsort 。 np.lexsort((a,b,c))
#print(d)
"""
[3 4 1 0 2]
"""
#tile
#a=np.arange(5)
#print(np.tile(a,3))
"""
[0 1 2 3 4 0 1 2 3 4 0 1 2 3 4]
"""
#repeat
#a=np.arange(5)
#print(np.repeat(a,3,axis=0))
"""
[0 0 0 1 1 1 2 2 2 3 3 3 4 4 4]
"""
"""
，tile ，repeat
"""
a=np.arange(16).reshape(4,4)
print(a)
"""
[[ 0 1 2 3]
[ 4 5 6 7]
[ 8 9 10 11]
[12 13 14 15]]
"""
print(np.repeat(a,3,axis=0))#
"""
[[ 0 1 2 3]
[ 0 1 2 3]
[ 0 1 2 3]
[ 4 5 6 7]
[ 4 5 6 7]
[ 4 5 6 7]
[ 8 9 10 11]
[ 8 9 10 11]
[ 8 9 10 11]
[12 13 14 15]
[12 13 14 15]
[12 13 14 15]]
"""
print(np.repeat(a,3,axis=1))#
"""
[[ 0 0 0 1 1 1 2 2 2 3 3 3]
[ 4 4 4 5 5 5 6 6 6 7 7 7]
[ 8 8 8 9 9 9 10 10 10 11 11 11]
[12 12 12 13 13 13 14 14 14 15 15 15]]
"""
#
"""
sum
mean
std
var
min
max
argmin
argmax
cumsum
cumprod
"""
a=np.arange(20).reshape(4,5)
print(np.sum(a))#190
#
print(np.sum(a,axis=0))
"""
[30 34 38 42 46]
"""
#
print(np.sum(a,axis=1))
"""
[10 35 60 85]
"""