numpy常用API用法总结

numpy常用API用法总结

numpy入门指南：https://docs.scipy.org/doc/numpy/user/basics.html

numpy快速数据处理

numpy.array(object, dtype=None, copy=True, order=’K’, subok=False, ndmin=0)



参考链接：https://docs.scipy.org/doc/numpy/reference/generated/numpy.array.html#numpy.array

numpy.zeros(shape, dtype=float, order=’C’)



参考链接：https://docs.scipy.org/doc/numpy/reference/generated/numpy.zeros.html#numpy.zeros

numpy.ones(shape, dtype=None, order=’C’)



参考链接：https://docs.scipy.org/doc/numpy/reference/generated/numpy.ones.html#numpy.ones

numpy.arange([start, ]stop, [step, ]dtype=None)



参考链接：https://docs.scipy.org/doc/numpy/reference/generated/numpy.arange.html#numpy.arange

numpy.mat(data, dtype=None)[source]



参考链接：https://docs.scipy.org/doc/numpy/reference/generated/numpy.mat.html#numpy.mat

numpy.reshape(a, newshape, order=’C’)[source]



参考链接：

https://docs.scipy.org/doc/numpy/reference/generated/numpy.reshape.html#numpy.reshape

ndarray.flatten(order=’C’)



参考链接：

https://docs.scipy.org/doc/numpy/reference/generated/numpy.ndarray.flatten.html#numpy.ndarray.flatten

numpy.random.randn(d0, d1, …, dn)



参考链接：

https://docs.scipy.org/doc/numpy/reference/generated/numpy.random.randn.html#numpy.random.randn

numpy.random.shuffle(x)



参考链接：

https://docs.scipy.org/doc/numpy/reference/generated/numpy.random.shuffle.html#numpy.random.shuffle

numpy.stack(arrays, axis=0)[source]



参考链接：

https://docs.scipy.org/doc/numpy/reference/generated/numpy.stack.html#numpy.stack

numpy.random.permutation(x)



参考链接：https://docs.scipy.org/doc/numpy/reference/generated/numpy.random.permutation.html#numpy.random.permutation

numpy.random.seed(seed=None)



参考链接：https://docs.scipy.org/doc/numpy/reference/generated/numpy.random.seed.html#numpy.random.seed

numpy.linalg.norm(x, ord=None, axis=None, keepdims=False)[source]¶



参考链接：

https://docs.scipy.org/doc/numpy/reference/generated/numpy.linalg.norm.html#numpy.linalg.norm

numpy.sum(， axis)

参考链接：

numpy.mean()

参考链接：

numpy.power(a, n)

计算a的n次方

numpy.sqrt(a)

计算a的平方根