如何理解sklearn工具函数column_or_1d()?检测数据并转换

import numpy as np
a = np.array([["苏"],["南"],["大"],["叔"]])
print(np.ravel(a))                 #  ['苏' '南' '大' '叔']

import numpy as np
a = np.array([["苏"],["南"],["大"],["叔"]])
import sklearn;
b = sklearn.utils.column_or_1d(a)   # ['苏' '南' '大' '叔']
print(b)

import numpy as np
a = [["苏"],["南"],["大"],["叔"]]
a = np.array([["苏"],["南"],["大"],["叔"]])

a = np.array([[["苏"]],[["南"]],[["大"]],[["叔"]]])   
# ValueError: Found array with dim 3. None expected <= 2.
a = np.array([[["苏","南"]],[["大","叔"]]])           
# ValueError: Found array with dim 3. None expected <= 2.
a = np.array([["苏","南","大","叔"]])                 
# ValueError: y should be a 1d array, got an array of shape (1, 4) instead.

import sklearn;
b = sklearn.utils.column_or_1d(a)
print(b)

import numpy as np
a = np.array(["苏","南","大","叔"])  
a = ["苏","南","大","叔"]              
a = np.array([["苏"],["南"],["大"],["叔"]])             # DataConversionWarning
a = [["苏"],["南"],["大"],["叔"]]                       # DataConversionWarning
import sklearn;
b = sklearn.utils.column_or_1d(a,warn=True)            # ['苏' '南' '大' '叔']
print(b)

DataConversionWarning: A column-vector y was passed when a 1d array was expected. Please change the shape of y to (n_samples, ), for example using ravel().

import numpy as np

a = ["苏","南"]
a = [["苏"],["南"]]
a = [["苏","南"]]

if(type(a)==np.ndarray):
    print(a.ndim,a.shape)
else:
    tmp = np.array(a)
    print(tmp.ndim,tmp.shape)
    pass

import sklearn;
b = sklearn.utils.column_or_1d(a,warn=True)            # ['苏' '南' '大' '叔']
print(b,type(b))