Parameters --- x : array-like The input array to be binned. Must be 1-dimensional.#输入的待离散化的数据必须是1维的! bins : int, sequence of scalars, or IntervalIndex The criteria to bin by. * int : Defines the number of equal-width bins in the range of `x`. The range of `x`...
python ValueError：“p”必须是一维的问题是p是一个概率数组，而您要将1 - array和array传入该参数。
data : Sequence of objectsThe scalars inside `data` should be instances of thescalar type for `dtype`. It's expected that `data`represents a 1-dimensional array of data.When `data` is an Index or Series, the underlying arraywill be extracted from `data`.dtype : str, np.dtype, or Ext...
array(tup, dtype=object) print(arr) # Output: [[1, 2] [3]] print(type(arr)) # Output: <class 'numpy.ndarray'> print(arr.dtype) # Output: object Nested tuple to Multi-Dimensional Arrays If the tuple contains nested tuples, the numpy.array() method creates a multi-dimensional array...
For example, you could have three or four dimensional arrays. 例如,可以有三维或四维数组。 With multi-dimensional arrays, you can use the colon character in place of a fixed value for an index, which means that the array elements corresponding to all values of that particular index will be ...
Basics of an Array NumPy is the fundamental package for numerical computing in Python, offering a powerful array object and a suite of functions for working efficiently with these arrays. The advantages of Numpy are: •Multidimensional:Supports more than just one-dimensional arrays. ...
What that means, instead of using numbers,I could also be choosing one out of several strings. 让我们看看这是怎么回事。 So let’s see how that might work. 我要回到我的清单上。 I’m going to go back to my list. 我只想在这里包括三个短字符串。 I’m just going to include three shor...
array_like Input array to be binned. Prior to NumPy 1.10.0, this array had to be 1-dimensional, but can now have any shape. bins : 输入升序或降序数组, 注意:必须为升序或降序,否则会报错。可以为浮点型/整型混合 array_like Array of bins. It has to be 1-dimensional and monotonic. ...
我想连接一个包含不同元素大小的数组python作为用户输入不幸的是,它不能与用户输入一起工作,我得到了以下错误“值错误:Zero-dimensional数组不能连接”我不明白它是如何正常工作的,但与用户输入不工作? import numpy as np #lst_2=np.concatenate([[1],[2],np.repeat(3,3),[2]]) lst_2=input("PLEASE ...
arrays. However, only 1, and 2 dimensional arrays are supported. This function is very efficient, so large arrays should not be a problem. If the second argument is set to 1, the array is deep-copied from from numpy. This is not as efficient as the default behavior ...