Pandas (0.18) Rank: unexpected behavior for method = 'dense' and pct = True

I find the behavior of rank function with method = ‘dense’ and pct = True unexpected as it looks like, in order to calculate percentile ranks, the function is using the total number of observations instead of the number of distinct observations.

Code Sample, a copy-pastable example if possible

import pandas as pd
n_rep = 2
ts = pd.Series([1,2,3,4] * n_rep )
output = ts.rank(method = 'dense', pct = True)

Problem description

ts.rank(method = 'dense', pct = True)
Out[116]: 
0    0.125
1    0.250
2    0.375
3    0.500
4    0.125
5    0.250
6    0.375
7    0.500

Expected Output

Something similar to:

pd.Series([1,2,3,4] * 2).rank(method = 'dense', pct = True) * n_rep 
Out[118]: 
0    0.25
1    0.50
2    0.75
3    1.00
4    0.25
5    0.50
6    0.75
7    1.00

Also, I would expected the result above to be invariant to n_rep. i.e. I would expect a “mapping” {value -> pct_rank} that would not depend on how many times the value is repeated, while it is not the case here.

[shoyer]

I agree with @FXLab91 that this is very strange behavior, and I can’t see why anyone would want it. So I would be inclined to treat it as a bug and fix it for the next release.

[rouzazari]

Restating @dsm054’s question (and asking a few of my own), should all other method’s return a “dense percentage” on a 100% basis when pct=True?

As @dsm054 noted, Series([1,2,2]).max(method='min', pct=True) will return [1/3, 2/3, 2/3]. Should this return [1/2, 2/2, 2/2]?

Now if method=‘max’, Series([1,2,2]).max(method='max', pct=True) will return [1/3, 3/3, 3/3]. Is that is the desired output or should it again be [1/2, 2/2, 2/2]?

#15639 will fix the method='dense' case, but we need to address other methods as well.