python - Pandas 按应用于列的功能分组

Question

在 Groupby 文档中，我只看到按应用于轴 0 索引或列标签的函数进行分组的示例。我没有看到任何示例讨论如何按从将函数应用于列派生的标签进行分组。我认为这可以使用 apply 来完成。下面的示例是执行此操作的最佳方法吗？

df = pd.DataFrame({'name' : np.random.choice(['a','b','c','d','e'], 20), 
               'num1': np.random.randint(low = 30, high=100, size=20),
               'num2': np.random.randint(low = -3, high=9, size=20)})

df.head()

  name  num1 num2
0   d   34  7
1   b   49  6
2   a   51  -1
3   d   79  8
4   e   72  5

def num1_greater_than_60(number_num1):
    if number_num1 >= 60:
        return 'greater'
    else:
        return 'less'

df.groupby(df['num1'].apply(num1_greater_than_60))

Answer 1

来自 DataFrame.groupby() 文档:

by : mapping, function, str, or iterable
    Used to determine the groups for the groupby.
    If ``by`` is a function, it's called on each value of the object's
    index. If a dict or Series is passed, the Series or dict VALUES
    will be used to determine the groups (the Series' values are first
    aligned; see ``.align()`` method). If an ndarray is passed, the
    values are used as-is determine the groups. A str or list of strs
    may be passed to group by the columns in ``self``

所以我们可以这样做:

In [35]: df.set_index('num1').groupby(num1_greater_than_60)[['name']].count()
Out[35]:
         name
greater    15
less        5