月中的天数 [英] Numbers of Day in Month
问题描述
我有一个带有日期时间索引的数据框，我想将某些列乘以该月的天数.
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.
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
在这里，我想将以t开头的所有列乘以31.也就是说，预期输出是
Here, I would like to multiply all the columns starting with t with 31. That is, expected output is
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
我知道有些使用calendar或类似方法的方法，但是鉴于我已经在使用pandas，肯定有一种更简单的方法-我想.
I know that there are some ways using calendar or similar, but given that I'm already using pandas, there must be an easier way - I assume.
没有这样的datetime属性，但是有一个偏移量 M-但我不知道如何在没有效率低下的情况下使用它.
There is no such datetime property, but there is an offset M - but I don't know how I would use that without massive inefficiency.
推荐答案
There is now a Series.dt.daysinmonth attribute for datetime series. Here is an example based on Jeff's answer.
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
这篇关于月中的天数的文章就介绍到这了，希望我们推荐的答案对大家有所帮助，也希望大家多多支持IT屋！
