pandas 将熊猫日期时间月份转换为字符串表示
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Convert pandas datetime month to string representation
提问by farnold
I want to have a pandas DataFrame with a timestamp column and want to create a column with just the month. I want to have the month column with string representations of the month, not with integers. I have done something like this:
我想要一个带有时间戳列的 Pandas DataFrame 并且想要创建一个只有月份的列。我想让月份列带有月份的字符串表示形式，而不是整数。我做了这样的事情：
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'))
However, this is some kind of a brute force approach and not very performant. Is there a more elegant way to convert the integer representation of the month into a string representation?
但是，这是某种蛮力方法，并且性能不高。有没有更优雅的方法将月份的整数表示形式转换为字符串表示形式？
回答by EdChum
use vectorised dt.strftimeon your datetimes:
dt.strftime在您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
回答by jezrael
For versions pandas 0.23.0+is possible use dt.month_name:
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
