在多索引数据框中删除行？

Question

我有这个 df:

temp = pd.DataFrame({'tic': ['IBM', 'AAPL', 'AAPL', 'IBM', 'AAPL'],
               'industry': ['A', 'B', 'B', 'A', 'B'],
                'price': [np.nan, 5, 6, 11, np.nan],
                'shares':[100, 60, np.nan, 100, np.nan],
                'dates': pd.to_datetime(['1990-01-01', '1990-01-01', '1990-04-01', 
                                             '1990-04-01', '1990-08-01'])
                })

temp.set_index(['tic', 'dates'], inplace=True)
temp.sort_index(inplace=True)

产生：

                industry  price  shares
tic  dates                             
AAPL 1990-01-01        B    5.0    60.0
     1990-04-01        B    6.0     NaN
     1990-08-01        B    NaN     NaN
IBM  1990-01-01        A    NaN   100.0
     1990-04-01        A   11.0   100.0

如何在数据框中创建一个 new column 来显示每个抽动点的观察次数。因此，新专栏将如下所示：

        New column
AAPL    ... 3
        ... 3
        ... 3
IBM     ... 2
        ... 2

Answer 1

你可以使用.groupby(level=0) and .filter()方法：

In [79]: temp.groupby(level=0).filter(lambda x: len(x) >= 3)
Out[79]:
                industry  price  shares
tic  dates
AAPL 1990-01-01        B    5.0    60.0
     1990-04-01        B    6.0     NaN
     1990-08-01        B    NaN     NaN

回答你的第二个问题：

In [83]: temp['new'] = temp.groupby(level=0)['industry'].transform('size')

In [84]: temp
Out[84]:
                industry  price  shares  new
tic  dates
AAPL 1990-01-01        B    5.0    60.0    3
     1990-04-01        B    6.0     NaN    3
     1990-08-01        B    NaN     NaN    3
IBM  1990-01-01        A    NaN   100.0    2
     1990-04-01        A   11.0   100.0    2

在多索引数据框中删除行？

Dropping rows in a multi-index data frame?

python

multi-index

pandas