获取 DataFrame 的日期时间列的工作日/星期几

我有一个数据框df如下所示（摘录，“时间戳”是索引）：

Timestamp              Value
2012-06-01 00:00:00     100
2012-06-01 00:15:00     150
2012-06-01 00:30:00     120
2012-06-01 01:00:00     220
2012-06-01 01:15:00      80
...and so on.

我需要一个新专栏df['weekday']以及时间戳各自的工作日/星期几。

我怎样才能得到这个？

使用新的dt.dayofweek https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.dt.dayofweek.html#pandas-series-dt-dayofweek财产：

In [2]:

df['weekday'] = df['Timestamp'].dt.dayofweek
df
Out[2]:
            Timestamp  Value  weekday
0 2012-06-01 00:00:00    100        4
1 2012-06-01 00:15:00    150        4
2 2012-06-01 00:30:00    120        4
3 2012-06-01 01:00:00    220        4
4 2012-06-01 01:15:00     80        4

在这种情况下Timestamp是您的索引，您需要重置索引，然后调用dt.dayofweek财产：

In [14]:

df = df.reset_index()
df['weekday'] = df['Timestamp'].dt.dayofweek
df
Out[14]:
            Timestamp  Value  weekday
0 2012-06-01 00:00:00    100        4
1 2012-06-01 00:15:00    150        4
2 2012-06-01 00:30:00    120        4
3 2012-06-01 01:00:00    220        4
4 2012-06-01 01:15:00     80        4

奇怪的是，如果您尝试从索引创建一个系列，以便不重置您得到的索引NaN值与使用结果一样reset_index打电话给dt.dayofweek属性而不分配结果reset_index回到原来的df：

In [16]:

df['weekday'] = pd.Series(df.index).dt.dayofweek
df
Out[16]:
                     Value  weekday
Timestamp                          
2012-06-01 00:00:00    100      NaN
2012-06-01 00:15:00    150      NaN
2012-06-01 00:30:00    120      NaN
2012-06-01 01:00:00    220      NaN
2012-06-01 01:15:00     80      NaN
In [17]:

df['weekday'] = df.reset_index()['Timestamp'].dt.dayofweek
df
Out[17]:
                     Value  weekday
Timestamp                          
2012-06-01 00:00:00    100      NaN
2012-06-01 00:15:00    150      NaN
2012-06-01 00:30:00    120      NaN
2012-06-01 01:00:00    220      NaN
2012-06-01 01:15:00     80      NaN

EDIT

正如用户 @joris 向我指出的，您可以访问weekday索引的属性，因此以下内容将起作用并且更紧凑：

df['Weekday'] = df.index.weekday