获取DataFrame的Datetime列的工作日/星期几

Question

我有一个df类似于以下的DataFrame （摘录，“ Timestamp”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.

我需要一个新列df['weekday']，分别包含时间戳记的星期几/星期几。

我怎么能得到这个？

Answer 1

使用新dt.dayofweek属性：

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Timestamp索引是的情况下，您需要重置索引，然后调用该dt.dayofweek属性：

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序列以不重置索引，您将NaN像使用的结果reset_index调用dt.dayofweek属性那样获得值，而没有将结果reset_index赋回原始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

编辑

正如用户@joris向我指出的那样，您只能访问weekday索引的属性，因此以下内容将有效并且更加紧凑：

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