pandas 每排返回下一个星期日 [英] Pandas return the next Sunday for every row

问题描述

在适用于Python的Pandas中，我有一个数据集，其中包含一列日期时间。我需要创建一个新列，其中每一行的日期都为下一个星期日。

我尝试了各种尝试使用迭代的方法，然后弄清楚一周中的哪一天，并添加一天直到一天是7，但是还没有工作，我什至不知道如何返回日期，而不只是日期。我也不认为最好使用迭代法。

从日期列返回下一个星期日的列的最佳方法是什么？

解决方案

使用熊猫的日期偏移量，例如：

 >> pd.to_datetime（'2019-04-09'）+ pd.offsets.Week（weekday = 6）
 Timestamp（'2019-04-14 00:00:00'）
  

例如，这会在一周内更改提供的 datetime 。这是矢量化的，因此您可以针对以下系列运行它：

  temp ['sunday_dates'] = temp ['our_dates '] + pd.offsets.Week（weekday = 6）
  

  our_dates random_data sunday_dates 
 0 2010-12-31 4012 2011-01-02 
 1 2007-12-31 3862 2008-01-06 
 2 2006- 12-31 3831 2007-01-07 
 3 2011-12-31 3811 2012-01-01 
  

Nb Week（weekday = INT）参数在星期一索引为0，其值从0到6（包括0和6）。因此，传递0将在每个星期一产生收益，传递1将在所有星期二产生收益，依此类推。如此一来，您就可以在一周中的任意一天完成所有操作。

N.b。如果您想去最后一个周日，只需将 + 换成-即可返回。

Nb （请注意，有很多好处）有关时间序列功能的特定文档可以在以下位置找到： https://pandas.pydata.org/pandas-docs/stable/user_guide/timeseries.html

In Pandas for Python, I have a data set that has a column of datetimes in it. I need to create a new column that has the date of the following Sunday for each row.

I've tried various methods trying to use iterrows and then figure out the day of the week, and add a day until the day is 7, but it hasn't worked and I'm not even sure how I'd return the date instead of just the day number then. I also don't feel like iterrows would be the best way to do it either.

What is the best way to return a column of the following Sunday from a date column?

解决方案

Use the Pandas date offsets, e.g.:

>>> pd.to_datetime('2019-04-09') + pd.offsets.Week(weekday=6)
Timestamp('2019-04-14 00:00:00')

For example, this changes the provided datetime over a week. This is vectorised, so you can run it against a series like so:

temp['sunday_dates'] = temp['our_dates'] + pd.offsets.Week(weekday=6)

    our_dates  random_data sunday_dates
0  2010-12-31         4012   2011-01-02
1  2007-12-31         3862   2008-01-06
2  2006-12-31         3831   2007-01-07
3  2011-12-31         3811   2012-01-01

N.b. The Week(weekday=INT) parameter is 0 indexed on Monday and takes values from 0 to 6 (inclusive). Thus, passing 0 yields all Mondays, 1 yields all Tuesdays, etc. Using this, you can make everything any day of the week you would like.

N.b. If you want to go to the last Sunday, just swap + to - to go back.

N.b. (Such note, much bene) The specific documentation on time series functionality can be found here: https://pandas.pydata.org/pandas-docs/stable/user_guide/timeseries.html

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