pandas 月中的天数
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Numbers of Day in Month
提问by FooBar
I have a data frame with a date time index, and I would like to multiply some columns with the number of days in that month.
我有一个带有日期时间索引的数据框，我想将一些列与该月的天数相乘。
TUFNWGTP TELFS t070101 t070102 t070103 t070104
TUDIARYDATE
2003-01-03 8155462.672158 2 0 0 0 0
2003-01-04 1735322.527819 1 0 0 0 0
2003-01-04 3830527.482672 2 60 0 0 0
2003-01-02 6622022.995205 4 0 0 0 0
2003-01-09 3068387.344956 1 0 0 0 0
Here, I would like to multiply all the columns starting with twith 31. That is, expected output is
在这里，我想将所有t以 31开头的列相乘。也就是说，预期输出是
TUFNWGTP TELFS t070101 t070102 t070103 t070104
TUDIARYDATE
2003-01-03 8155462.672158 2 0 0 0 0
2003-01-04 1735322.527819 1 0 0 0 0
2003-01-04 3830527.482672 2 1680 0 0 0
2003-01-02 6622022.995205 4 0 0 0 0
2003-01-09 3068387.344956 1 0 0 0 0
I know that there are some ways using calendaror similar, but given that I'm already using pandas, there must be an easier way - I assume.
我知道有一些使用calendar或类似的方法，但鉴于我已经在使用pandas，必须有一种更简单的方法 - 我假设。
There is no such datetimeproperty, but there is an offsetM- but I don't know how I would use that without massive inefficiency.
没有这样的datetime属性，但有一个偏移量M- 但我不知道我将如何使用它而不会导致效率低下。
回答by Eric Ness
There is now a Series.dt.daysinmonthattribute for datetime series. Here is an example based on Jeff's answer.
现在有一个Series.dt.daysinmonth日期时间系列的属性。这是一个基于杰夫回答的例子。
In [3]: df = pd.DataFrame({'date' : pd.date_range('20120101',periods=15,freq='M') })
In [4]: df['year'] = df['date'].dt.year
In [5]: df['month'] = df['date'].dt.month
In [6]: df['days_in_month'] = df['date'].dt.daysinmonth
In [7]: df
Out[7]:
date year month days_in_month
0 2012-01-31 2012 1 31
1 2012-02-29 2012 2 29
2 2012-03-31 2012 3 31
3 2012-04-30 2012 4 30
4 2012-05-31 2012 5 31
5 2012-06-30 2012 6 30
6 2012-07-31 2012 7 31
7 2012-08-31 2012 8 31
8 2012-09-30 2012 9 30
9 2012-10-31 2012 10 31
10 2012-11-30 2012 11 30
11 2012-12-31 2012 12 31
12 2013-01-31 2013 1 31
13 2013-02-28 2013 2 28
14 2013-03-31 2013 3 31
回答by Jeff
pd.tslib.monthrangeis an unadvertised / undocumented function that handles the days_in_month calculation (adjusting for leap years). This could/should prob be added as a property to Timestamp/DatetimeIndex.
pd.tslib.monthrange是处理 days_in_month 计算（调整闰年）的未公开/未记录的函数。这可以/应该 prob 作为属性添加到Timestamp/DatetimeIndex.
In [34]: df = DataFrame({'date' : pd.date_range('20120101',periods=15,freq='M') })
In [35]: df['year'] = df['date'].dt.year
In [36]: df['month'] = df['date'].dt.month
In [37]: df['days_in_month'] = df.apply(lambda x: pd.tslib.monthrange(x['year'],x['month'])[1], axis=1)
In [38]: df
Out[38]:
date year month days_in_month
0 2012-01-31 2012 1 31
1 2012-02-29 2012 2 29
2 2012-03-31 2012 3 31
3 2012-04-30 2012 4 30
4 2012-05-31 2012 5 31
5 2012-06-30 2012 6 30
6 2012-07-31 2012 7 31
7 2012-08-31 2012 8 31
8 2012-09-30 2012 9 30
9 2012-10-31 2012 10 31
10 2012-11-30 2012 11 30
11 2012-12-31 2012 12 31
12 2013-01-31 2013 1 31
13 2013-02-28 2013 2 28
14 2013-03-31 2013 3 31
回答by su79eu7k
import pandas as pd
from pandas.tseries.offsets import MonthEnd
df['dim'] = (pd.to_datetime(df.index) + MonthEnd(0)).dt.day
You can omit pd.to_datetime(), if your index is already DatetimeIndex.
pd.to_datetime()如果您的索引已经是 ，则可以省略DatetimeIndex。
回答by Christian
Here is a little clunky hand-made method to get the number of days in a month
这是一个有点笨拙的手工制作方法来获得一个月的天数
import datetime
def days_in_month(dt):
next_month = datetime.datetime(
dt.year + dt.month / 12, dt.month % 12 + 1, 1)
start_month = datetime.datetime(dt.year, dt.month, 1)
td = next_month - start_month
return td.days
For example:
例如：
>>> days_in_month(datetime.datetime.strptime('2013-12-12', '%Y-%m-%d'))
31
>>> days_in_month(datetime.datetime.strptime('2013-02-12', '%Y-%m-%d'))
28
>>> days_in_month(datetime.datetime.strptime('2012-02-12', '%Y-%m-%d'))
29
>>> days_in_month(datetime.datetime.strptime('2012-01-12', '%Y-%m-%d'))
31
>>> days_in_month(datetime.datetime.strptime('2013-11-12', '%Y-%m-%d'))
30
I let you figure out how to read your table and do the multiplication yourself :)
我让你弄清楚如何阅读你的表格并自己做乘法:)
