Python学习之Numpy基础（二）

一：判断array中的值是否满足条件

vector = numpy.array([10, 20, 30, 40, 50])
equal_to_ten = (vector == 10)
print(equal_to_ten)

打印结果：

[ True False False False False]

1.返回真实值：

print(vector[equal_to_ten])

 打印结果：

[10]

2.在二维数组中的应用：bool可值当做索引

matrix = numpy.array([
    [1, 2, 3],
    [4, 5, 6],
    [7, 8, 9]
])
print(matrix[:, 1])  #返回第二列
second_column_25 = (matrix[:, 1] == 5) #判断第二列中的值是否等于5
print(second_column_25)
print(matrix[second_column_25, :])  #打印第二列等于5那一行中所有的值

打印结果：

[2 5 8]
[False  True False]

[[4 5 6]]

3.多条件判断

vector = numpy.array([10, 20, 30, 40, 50])
equal_to_ten_and_tewnty = (vector == 10) & (vector == 20)
print(equal_to_ten_and_tewnty)

打印结果：[False False False False False]

vector = numpy.array([10, 20, 30, 40, 50])
equal_to_ten_or_twenty = (vector == 10) | (vector == 20)
print(equal_to_ten_or_twenty)

打印结果：[ True  True False False False]

应用：

vector = numpy.array([10, 20, 30, 40, 50])
equal_to_ten_or_twenty = (vector == 10) | (vector == 20) 
vector[equal_to_ten_or_twenty] = 5
print(vector)

打印结果：[ 5  5 30 40 50]

二：dtype的类型转换

vector = numpy.array([1, 2, 3, 4])
print(vector.dtype)
print(vector)
vector = vector.astype(float)
print(vector.dtype)
print(vector)
vector = vector.astype(str)
print(vector.dtype)
print(vector)

打印结果：

int32

[1 2 3 4]
float64
[ 1.  2.  3.  4.]
<U32

['1.0' '2.0' '3.0' '4.0']

三：numpy.array的属性

1.更多请参考：http://blog.youkuaiyun.com/cjgs45/article/details/79517275

print(vector.min())

print(vector.max())

2.按行求和

matrix = numpy.array([
    [1, 2, 3],
    [4, 5, 6],
    [7, 8, 9]
])
print(matrix.sum(axis=1))  #axis=0则为按列求和

打印结果：

[ 6 15 24]