1，功能:將數(shù)據(jù)進(jìn)行離散化

pandas.cut(x,bins,right=True,labels=None,retbins=False,precision=3,include_lowest=False)

???? 參數(shù)說(shuō)明:

? ? ?x???:進(jìn)行劃分的一維數(shù)組

???? bins : 1,整數(shù)---將x劃分為多少個(gè)等間距的區(qū)間

???????? In[1]:pd.cut(np.array([0.2,1.4,2.5,6.2,9.7,2.1]),3,retbins=True)

? ? ? ? Out[1]: ([(0.19, 3.367], (0.19, 3.367], (0.19, 3.367], (3.367,6.533], (6.533,9.7], (0.19, 3.367]] Categories (3, interval[float64]): [(0.19,3.367] < (3.367, 6.533] < (6.533, 9.7]],array([ 0.1905??? ,?3.36666667,? 6.53333333,? 9.7 ]))

? ? ? ? ? ? ? ? 2,序列—將x劃分在指定的序列中，若不在該序列中，則是NaN

???? ???? ?In[2]:pd.cut(np.array([0.2,1.4,2.5,6.2,9.7,2.1]),[1,2,3],retbins=True)

? ? ? ? ? ?Out[2]: ([NaN, (1, 2], (2, 3], NaN, NaN, (2, 3]] Categories(2, interval[int64]): [(1, 2] < (2, 3]], array([1, 2, 3]))

???? right :是否包含右端點(diǎn)

???? labels :是否用標(biāo)記來(lái)代替返回的bins

???????? ?In[3]:pd.cut([1,2,3,4],4,labels=['one','two','three','four'])

???????? ?Out[3]: [one, two, three, four]Categories (4, object): [one

???? precision:精度

???? include_lowest:是否包含左端點(diǎn)

???? 返回值:

???? 如果retbins = False 則返回x中每個(gè)值對(duì)應(yīng)的bin的列表，否者則返回x中每個(gè)值對(duì)應(yīng)的bin的列表和對(duì)應(yīng)的bins