pd cut in pandas

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Rahma
01 Feb 2017
1test = pd.DataFrame({'days': [0,20,30,31,45,60]})
2
3test['range1'] = pd.cut(test.days, [0,30,60], include_lowest=True)
4#30 value is in [30, 60) group
5test['range2'] = pd.cut(test.days, [0,30,60], right=False)
6#30 value is in (0, 30] group
7test['range3'] = pd.cut(test.days, [0,30,60])
8print (test)
9   days          range1    range2    range3
100     0  (-0.001, 30.0]   [0, 30)       NaN
111    20  (-0.001, 30.0]   [0, 30)   (0, 30]
122    30  (-0.001, 30.0]  [30, 60)   (0, 30]
133    31    (30.0, 60.0]  [30, 60)  (30, 60]
144    45    (30.0, 60.0]  [30, 60)  (30, 60]
155    60    (30.0, 60.0]       NaN  (30, 60]
Mitch
17 Oct 2020
1>>> pd.qcut(range(5), 4, labels=False)
2array([0, 0, 1, 2, 3])
3
Valentina
08 Aug 2019
1>>> pd.qcut(range(5), 3, labels=["good", "medium", "bad"])
2... 
3[good, good, medium, bad, bad]
4Categories (3, object): [good < medium < bad]
5
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