如何使用 pandas 按月，日，年过滤 [英] How to filter by month, day, year with Pandas

问题描述

我使用以下方法创建DataFrame:

I create the DataFrame with:

df = pandas.read_csv("data.csv", sep=';', parse_dates = 1, dayfirst = True)

然后我得到以下结果:

                   Qty     System_created             Total
0                   2  2014-10-14 08:13:46.000         21.76  
1                   1  2014-10-14 08:13:46.000          4.16  
2                   2  2014-10-14 08:30:46.000         27.90  
3                   1  2014-10-14 08:30:46.000          4.95  
4                   1  2014-10-14 08:30:46.000          4.95  
5                   2  2014-11-05 11:15:47.000         21.76  
6                   1  2014-11-05 11:15:48.000          3.32  

但是我不知道如何按月份(或年份，日期，小时等)进行过滤.像df[df["System_created"].day]这样的东西将是理想的.有可能吗?

But I do not know how to filter by month(or year, day, hour etc...). Something like df[df["System_created"].day] would be ideal. Is that possible?

推荐答案

只要您的熊猫版本为0.15或更高版本，那么假设您的dtype已经是日期时间，以下操作将起作用:

So long as your pandas version is 0.15 or higher then the following would work assuming your dtype is already a datetime:

In [167]:

df[df.System_created.dt.day == 5]
Out[167]:
       Qty      System_created  Total
index                                
5        2 2014-11-05 11:15:47  21.76
6        1 2014-11-05 11:15:48   3.32

因此，基本上dt属性允许您访问日期时间的组成部分以执行您希望过滤的比较

So basically the dt attribute allows you to access the components of your datetime to perform the comparisons you desire for filtering

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