python - 使用日期时间索引的 Pandas 过滤

Question

使用 Pandas 数据框的日期时间索引，很容易获得日期范围:

df[datetime(2018,1,1):datetime(2018,1,10)]

过滤也很简单:

df[ (df['column A'] = 'Done') & (df['column B'] < 3.14 )]

但是同时按日期范围和任何其他非日期条件进行过滤的最佳方法是什么？

Answer 1

3 个 bool 条件

c0 = df.index.to_series().between('2018-01-01', '2018-01-10')
c1 = df['column A'] == 'Done'
c2 = df['column B'] < 3.14

df[c0 & c1 & c2]

           column A  column B
2018-01-04     Done  2.533385
2018-01-06     Done  2.789072
2018-01-08     Done  2.230017

设置

np.random.seed([3, 1415])
df = pd.DataFrame({
    'column A': ['Done', 'Not Done'] * 10,
    'column B': np.random.randn(20) + np.pi
}, pd.date_range('2017-12-25', periods=20))

df

            column A  column B
2017-12-25      Done  1.011868
2017-12-26  Not Done  1.873127
2017-12-27      Done  1.171093
2017-12-28  Not Done  0.882538
2017-12-29      Done  2.792306
2017-12-30  Not Done  3.114638
2017-12-31      Done  3.457829
2018-01-01  Not Done  3.490375
2018-01-02      Done  3.856957
2018-01-03  Not Done  3.912356
2018-01-04      Done  2.533385
2018-01-05  Not Done  3.493983
2018-01-06      Done  2.789072
2018-01-07  Not Done  2.725724
2018-01-08      Done  2.230017
2018-01-09  Not Done  2.999055
2018-01-10      Done  3.888432
2018-01-11  Not Done  1.637436
2018-01-12      Done  3.752955
2018-01-13  Not Done  3.541812