Apply custom function to Rolling Dataframe - pandas

Question

I have a function (let's call it) RBSA(df) (that I'm currently treating the function as a blackbox) that takes a dataframe
DATE RETURN STYLE1 STYLE2 STYLE3 STYLE4
2020-09-01 0.01 100 251 300 211
2020-09-02 0.04 106 248 310 210
2020-09-03 0.03 104 251 308 211
2020-09-03 0.02 110 258 306 212
...
and returns a dataframe like this
DATE STYLE1 STYLE2 STYLE3 STYLE4 R2
2020 0.01 85 10 4.99 68
Now I want to be able to apply that function on a rolling basis with a window of 30 to the initial database so that the dataframe looks something like this.
DATE STYLE1 STYLE2 STYLE3 STYLE4 R2
2020-09 0.01 85 10 4.99 68 #applied date range would be 09-01 to 09-30
2020-09 0.99 80 15 4.01 77 #applied date range would be 09-02 to 10-01
2020-09 3.93 80 10 6.07 89 #applied date range would be 09-03 to 10-02
So far I've tried using df.rolling(30).apply(RBSA) however from what I can tell the rolling.apply function applies the function by turning each window into a numpy.ndarray. However since I'm treating the RBSA() function as a black box, I would rather not change the RBSA() function to have a numpy.ndarray as it's input.
My second idea was to create a for loop that append() each dataframe to a, initially, empty dataframe. However, i'm not really sure how to emulate a rolling window using a while loop.
def rolling30(df):
count = len(count) - 30
ret = []
while (count > 0):
count = count - 1
df2 = df[count:count + 30]
df2 = style(df2)
ret.append(df2)
However unlike when I manually append the dataframes together, for some reason when I'm appending the dataframes together it seems to create an output that looks like this (notice the comma)
DATE STYLE1 STYLE2 STYLE3 STYLE4 R2
2020-09 0.01 85 10 4.99 68, DATE STYLE1 STYLE2 STYLE3 STYLE4 R2
2020-09 0.99 80 15 4.01 77, DATE STYLE1 STYLE2 STYLE3 STYLE4 R2
2020-09 3.93 80 10 6.07 89, DATE STYLE1 STYLE2 STYLE3 STYLE4 R2
Right now it feels like I'm closest when coming to a solution with the while loop. Though it doesn't feel as elegant as using rolling.apply
UPDATE: just did a isinstance(rolling30(df), pd.DataFrame) and it returned Falseso I assume the problem is that somewhere it's reverting it into something thats not a dataframe.

Answer 1

So I figured out the solution to my while loop probem. Realized the initial retwas a list and changed that to ret = pd.DataFrame() and then the append to call back to ret
def rolling30(df):
count = len(count) - 30
ret = pd.DataFrame()
while (count > 0):
count = count - 1
df2 = df[count:count + 30]
df2 = style(df2)
ret = ret.append(df2)
I would still like to see what methods other people had to this problem since I feel like the deployment of the While Loop isn't a elegant solution here.