按特定月份切片

Question

我有以下格式的数据框。

              1            2           3           4  
Data                                                                            
2001-07-30      0.363354   27.428261   14.639130   6.763423         
...                  ...         ...         ...        ...           
2015-06-15      0.039085   28.562948   14.000722   8.605911         

我希望逐月切片。因此，例如，我想仅选择第5个月的数据并将其存储在新变量中。我找到了类似问题的几个答案。然而，这些并未提供预期的结果。

该领域的问题和答案示例：

1. Pandas DataFrame slicing by day/hour/minute
2. python pandas dataframe slicing by date conditions
3. pandas, python - how to select specific times in timeseries

我不熟悉Python和Pandas的时间序列分析，所以任何推动正确方向或阅读材料都将受到赞赏。

Answer 1

datetimeindex具有要访问的属性month，您可以使用它来过滤df：

In [132]:
df = pd.DataFrame(index=pd.date_range(dt.datetime(2015,1,1), dt.datetime(2015,5,1)))
df.loc[df.index.month==2]

Out[132]:
Empty DataFrame
Columns: []
Index: [2015-02-01 00:00:00, 2015-02-02 00:00:00, 2015-02-03 00:00:00, 2015-02-04 00:00:00, 2015-02-05 00:00:00, 2015-02-06 00:00:00, 2015-02-07 00:00:00, 2015-02-08 00:00:00, 2015-02-09 00:00:00, 2015-02-10 00:00:00, 2015-02-11 00:00:00, 2015-02-12 00:00:00, 2015-02-13 00:00:00, 2015-02-14 00:00:00, 2015-02-15 00:00:00, 2015-02-16 00:00:00, 2015-02-17 00:00:00, 2015-02-18 00:00:00, 2015-02-19 00:00:00, 2015-02-20 00:00:00, 2015-02-21 00:00:00, 2015-02-22 00:00:00, 2015-02-23 00:00:00, 2015-02-24 00:00:00, 2015-02-25 00:00:00, 2015-02-26 00:00:00, 2015-02-27 00:00:00, 2015-02-28 00:00:00]

月份索引为1，因此5为May