Python numpy相关操作
1.新建一个np数组
numpy.empty(shape, dtype = float, order = ‘C’)
import numpy as np
test = np.empty((4,3), dtype = float, order = 'C')//可选np.ones / np.zero
print(test)
import numpy as np
b = np.linspace(1,10,10)//参数为(开始,结束,元素个数)
print(b)
import numpy as np
b = np.arange(1,10,1)//参数为(开始,结束,间隔数)
print(b)
2.切片
2.1一维数组切片
import numpy as np
a = np.arange(10)
b = a[2:7:2]
print(b)
2.2 二维数组切一行一列或某个位置的值
a = np.ones((4,3))
print(a[0,:])
print(a[:,0])
print(a[0][0])
3.更新元素
a = np.ones((4,3))
a[0][0] = 2
print(a)
4.改变np性状,reshape
import numpy as np
a = np.ones((2,8))
print(a)
print(a.reshape((4,4)))
将多维数组折叠成一维
import numpy as np
a = np.ones((2,8))
print(a.flatten())
print(a.ravel())
np转置
import numpy as np
a = np.ones((2,8))
print(a.transpose())
5.np分析数据的一些函数
axis = 0 或1
np.sum(),返回求和
np.mean(),返回均值
np.max(),返回最大值
np.min(),返回最小值
np.ptp(),数组沿指定轴返回最大值减去最小值,即(max-min)
np.std(),返回标准偏差(standard deviation)
np.var(),返回方差(variance)
np.cumsum(),返回累加值
np.cumprod(),返回累乘积值
import numpy as np
a = np.random.randn(5,5)
print(a.mean())
print(a.var())
print(a.std())
print(np.median(a))
print(np.percentile(a))
6.删除某一行。一列
numpy.delete(arr, obj, axis=None)
import numpy as np
a = np.random.randn(5,5)
print(np.delete(a, 1, axis=1))
Original: https://blog.csdn.net/qq_41194643/article/details/123758104
Author: 98年的xujia
Title: Python numpy操作
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