Pandas "Consecutive"/Rolling Percent Rank

How can I create a "consecutive"/rolling percent rank on a pandas df series with a rolling window that grows as the data frame row count grows- as opposed to being a fixed window. rolling() requires an integer for the window size.

I basically want the ranking to be consecutively calculated as opposed to running the ranking function across the entire series and outputting the results. First row would have a rank just on that one row. By the end of the data frame, the rank would be calculated across the entire series.

Desired dataframe output:

My thinking:

df['len']=range(len(df))
df['rank']=df['value'].rolling(df['len']).rank(pct=True)

Example

df = pd.DataFrame([6, 3, 4, 100, 1], columns=['value'])

df

    value
0	6
1	3
2	4
3	100
4	1

Code

df.assign(rank=df['value'].expanding().rank(ascending=False).astype('int'))

output:

    value	rank
0	6	    1
1	3	    2
2	4	    2
3	100	    1
4	1	    5

if you want pct rank use following code

df.assign(rank_pct=df['value'].expanding().rank(ascending=False, pct=True))

output:

value	rank_pct
0	6	1.000000
1	3	1.000000
2	4	0.666667
3	100	0.250000
4	1	1.000000