将pandas datetime month转换为字符串表示形式

Question

我想要一个带有时间戳列的pandas DataFrame,并希望创建一个只有月份的列.我希望月份列包含月份的字符串表示,而不是整数.我做过这样的事情:

df['Dates'] = pd.to_datetime(df['Dates'])
df['Month'] = df.Dates.dt.month
df['Month'] = df.Month.apply(lambda x: datetime.strptime(str(x), '%m').strftime('%b'))

然而,这是一种蛮力方法,并不是非常高效.有没有更优雅的方法将月份的整数表示转换为字符串表示？

Answer 1

dt.strftime在你的日期时间使用矢量化:

In [43]:
df = pd.DataFrame({'dates':pd.date_range(dt.datetime(2016,1,1), dt.datetime(2017,2,1), freq='M')})
df

Out[43]:
        dates
0  2016-01-31
1  2016-02-29
2  2016-03-31
3  2016-04-30
4  2016-05-31
5  2016-06-30
6  2016-07-31
7  2016-08-31
8  2016-09-30
9  2016-10-31
10 2016-11-30
11 2016-12-31
12 2017-01-31

In [44]:    
df['month'] = df['dates'].dt.strftime('%b')
df

Out[44]:
        dates month
0  2016-01-31   Jan
1  2016-02-29   Feb
2  2016-03-31   Mar
3  2016-04-30   Apr
4  2016-05-31   May
5  2016-06-30   Jun
6  2016-07-31   Jul
7  2016-08-31   Aug
8  2016-09-30   Sep
9  2016-10-31   Oct
10 2016-11-30   Nov
11 2016-12-31   Dec
12 2017-01-31   Jan

Answer 2

对于版本pandas 0.23.0+可以使用dt.month_name：

df['month'] = df['dates'].dt.month_name()
print (df)

        dates      month
0  2016-01-31    January
1  2016-02-29   February
2  2016-03-31      March
3  2016-04-30      April
4  2016-05-31        May
5  2016-06-30       June
6  2016-07-31       July
7  2016-08-31     August
8  2016-09-30  September
9  2016-10-31    October
10 2016-11-30   November
11 2016-12-31   December
12 2017-01-31    January