I'm trying to get all records where the mean of the last 3 rows is greater than the overall mean for all rows in a filtered set.
_filtered_d_all = _filtered_d.iloc[:, 0:50].loc[:, _filtered_d.mean()>0.05]
_last_n_records = _filtered_d.tail(3)
Something like this
_filtered_growing = _filtered_d.iloc[:, 0:50].loc[:, _last_n_records.mean() > _filtered_d.mean()]
However, the problem here is that the value length is incorrect. Any tips?
ValueError: Series lengths must match to compare
Sample Data
This has an index on the year and month, and 2 columns.
Col1 Col2
year month
2005 12 0.533835 0.170679
12 0.494733 0.198347
2006 3 0.440098 0.202240
6 0.410285 0.188421
9 0.502420 0.200188
12 0.522253 0.118680
2007 3 0.378120 0.171192
6 0.431989 0.145158
9 0.612036 0.178097
12 0.519766 0.252196
2008 3 0.547705 0.202163
6 0.560985 0.238591
9 0.617320 0.199537
12 0.343939 0.253855
Why not just boolean index directly on your filtered DataFrame with
df[df.tail(3).mean() > df.mean()]
Demo
>>> df
0 1 2 3 4
0 4 8 2 4 6
1 0 0 0 2 8
2 5 3 0 9 3
3 7 5 5 1 2
4 9 7 8 9 4
>>> df[df.tail(3).mean() > df.mean()]
0 1 2 3 4
0 4 8 2 4 6
1 0 0 0 2 8
2 5 3 0 9 3
3 7 5 5 1 2
Update example for MultiIndex edit
The same should work fine for your MultiIndex sample, we just have to mask a bit differently of course.
>>> df
col1 col2
2005 12 -0.340088 -0.574140
12 -0.814014 0.430580
2006 3 0.464008 0.438494
6 0.019508 -0.635128
9 0.622645 -0.824526
12 -1.674920 -1.027275
2007 3 0.397133 0.659467
6 0.026170 -0.052063
9 0.835561 0.608067
12 0.736873 -0.613877
2008 3 0.344781 -0.566392
6 -0.653290 -0.264992
9 0.080592 -0.548189
12 0.585642 1.149779
>>> df.loc[:,df.tail(3).mean() > df.mean()]
col2
2005 12 -0.574140
12 0.430580
2006 3 0.438494
6 -0.635128
9 -0.824526
12 -1.027275
2007 3 0.659467
6 -0.052063
9 0.608067
12 -0.613877
2008 3 -0.566392
6 -0.264992
9 -0.548189
12 1.149779