如何使用pandas.cut对数据进行分组？

Question

raw_data='''
82   68   86   94   89   63   77   76   84    89
75   78   81   82   76   99   80   84   89    88
60   83   72   83   85   56   86   68   75   100
90   84   75   86   74   77   95   63   80    76
100   43  76   81   79   74   96   52   69    86'''

How to use pandas.cut to group my data and output it as pandas.DataFrame in the following format?

  interval numbers
1   (0,60]       4
2  (60,70]       5
3  (70,80]      16
4  (80,90]      19
5 (90,100]       6

Answer 1

You can cut and then call describe :

>>> nums = pd.Series(raw_data.split(), dtype=int)
>>> ncut = pd.cut(nums, [0, 60, 70, 80, 90, 100])
>>> d = ncut.describe()
>>> d
           counts  freqs
levels                  
(0, 60]         4   0.08
(60, 70]        5   0.10
(70, 80]       16   0.32
(80, 90]       19   0.38
(90, 100]       6   0.12

[5 rows x 2 columns]

Or if you're very particular:

>>> d = d.reset_index().drop("freqs", axis=1)
>>> d = d.rename(columns={"levels": "interval", "counts": "numbers"})
>>> d
    interval  numbers
0    (0, 60]        4
1   (60, 70]        5
2   (70, 80]       16
3   (80, 90]       19
4  (90, 100]        6

[5 rows x 2 columns]