Pandas dataframe 带日期时间索引，按月和年排序记录

Question

I have a problem with pandas dataframe indexed with datetime values, my dataframe temps looks like this:

                 column      column
Index        | land_temps | ocean_temps
1861-01-01   |     -5     |    15
1861-02-01   |      0     |    17
1861-03-01   |      6     |    18
                   .
                   .
                   .
2015-11-01   |      2     |    17
2015-12-01   |     -1     |    14

So to sum up, I have a pandas dataframe with date as datatimeindexes, and floats (temperatures) as columns. I would like to sort rekords of this dataframe by monts of measurement, to achieve sth like this:

Index        | land_temps | ocean_temps
1861-01-01   |     -5     |    15
1862-02-01   |     -4     |    13
1863-03-01   |     -6     |    14
                   .
                   .
                   .
2014-12-01   |     -2     |    13
2015-12-01   |     -1     |    14

How to do that? I have tried:

temps.sort_values(by=temps.index.month, axis='index')

but it does not work like that I guess, so is there any way to do thay using build in sorting/groupby panadas methods (or similar).

Thanks in advance:).

Answer 1

You can create two additional columns (you can drop them later) and then you can sort according to those columns

temps['month'] = temps.index.month
temps['year'] = temps.index.year
temps.sort_values(['month', 'year']).drop(columns=['month', 'year'])