#numpy's universal function
X
array([[ 0, 1, 2],
[ 3, 4, 5],
[ 6, 7, 8],
[ 9, 10, 11],
[12, 13, 14]])
X + 1
array([[ 1, 2, 3],
[ 4, 5, 6],
[ 7, 8, 9],
[10, 11, 12],
[13, 14, 15]])
X * 2
array([[ 0, 2, 4],
[ 6, 8, 10],
[12, 14, 16],
[18, 20, 22],
[24, 26, 28]])
np.sin(X)
array([[ 0. , 0.84147098, 0.90929743],
[ 0.14112001, -0.7568025 , -0.95892427],
[-0.2794155 , 0.6569866 , 0.98935825],
[ 0.41211849, -0.54402111, -0.99999021],
[-0.53657292, 0.42016704, 0.99060736]])
x = np.arange(16)
x
array([ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15])
#随机打乱
np.random.shuffle(x)
x
array([ 2, 10, 4, 13, 7, 11, 8, 12, 5, 0, 3, 6, 14, 9, 15, 1])
#argsort 元素从小排序所对应的索引
np.argsort(x)
array([ 9, 15, 0, 10, 2, 8, 11, 4, 6, 13, 1, 5, 7, 3, 12, 14],
dtype=int64)
names = np.array(['Bob','Mor','Will','Joe','Mor','Will','Will'])
names
array(['Bob', 'Mor', 'Will', 'Joe', 'Mor', 'Will', 'Will'], dtype='<U4')
#使用np.random 模块的randn 生成一些正态分布的随机数据
data = np.random.randn(7,4)
data
array([[ 0.30878037, -0.4096957 , -0.83750594, -0.97213605],
[-0.14167727, -0.04756769, 1.97948161, -1.702129 ],
[-1.16628504, -0.4982823 , 1.53364224, -1.15853535],
[-0.11616092, 1.07999647, -0.35885284, -0.84570262],
[-0.12763289, -1.29314938, -0.80078425, -0.08737958],
[ 1.45718967, -1.14880644, 0.09459774, -0.25857695],
[-0.2095555 , -0.53830113, 0.63900549, 0.05845763]])
#假设 每个名字对应data数据的一行
#布尔型索引可以应用于数据的删选
data[names=='Joe']
array([[-0.11616092, 1.07999647, -0.35885284, -0.84570262]])
#布尔型索引应用修改值
#选取所有Mor的行,并且全部值 赋值为0
data[names=='Mor'] = 0
data
array([[ 0.30878037, -0.4096957 , -0.83750594, -0.97213605],
[ 0. , 0. , 0. , 0. ],
[-1.16628504, -0.4982823 , 1.53364224, -1.15853535],
[-0.11616092, 1.07999647, -0.35885284, -0.84570262],
[ 0. , 0. , 0. , 0. ],
[ 1.45718967, -1.14880644, 0.09459774, -0.25857695],
[-0.2095555 , -0.53830113, 0.63900549, 0.05845763]])
data[names=='Will',2:]=0
data
array([[ 0.30878037, -0.4096957 , -0.83750594, -0.97213605],
[ 0. , 0. , 0. , 0. ],
[-1.16628504, -0.4982823 , 0. , 0. ],
[-0.11616092, 1.07999647, -0.35885284, -0.84570262],
[ 0. , 0. , 0. , 0. ],
[ 1.45718967, -1.14880644, 0. , 0. ],
[-0.2095555 , -0.53830113, 0. , 0. ]])
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