Rank中文叫做順序,專業叫法是”秩”。

rank 表示在這個數在原來的Series中排第幾名，有相同的數，取其排名平均（默認）作為值。

①在scipy模塊中

>>> from scipy import rank

>>> help(rank)

Help on function rank in module numpy.core.fromnumeric:

rank(a)

Return the number of dimensions of an array.

If `a` is not already an array, a conversion is attempted.

Scalars are zero dimensional.

.. note::

This function is deprecated in NumPy 1.9 to avoid confusion with

`numpy.linalg.matrix_rank`. The ``ndim`` attribute or function

should be used instead.

Parameters

----------

a : array_like

Array whose number of dimensions is desired. If `a` is not an array,

a conversion is attempted.

Returns

-------

number_of_dimensions : int

The number of dimensions in the array.

See Also

--------

ndim : equivalent function

ndarray.ndim : equivalent property

shape : dimensions of array

ndarray.shape : dimensions of array

Notes

-----

In the old Numeric package, `rank` was the term used for the number of

dimensions, but in NumPy `ndim` is used instead.

Examples

--------

>>> np.rank([1,2,3])

1

>>> np.rank(np.array([[1,2,3],[4,5,6]]))

2

>>> np.rank(1)

0

②在pandas中：

總結

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