rolling_apply only applicable to numeric columns

Hi everybody,

I discovered that the rolling_apply function is only applicable to numeric columns. I think this should be changed as this seems too limited to me. Let’s take the following example,

    import datetime as DT
    df = pd.DataFrame({
    'Buyer': 'Carl Mark Carl Joe Joe Carl'.split(),
    'Quantity': [1,3,5,8,9,3],
    'Date' : [
        DT.datetime(2013,9,1,13,0),
        DT.datetime(2013,9,1,13,5),
        DT.datetime(2013,10,1,20,0),
        DT.datetime(2013,10,3,10,0),
        DT.datetime(2013,12,2,12,0),                                      
        DT.datetime(2013,12,2,14,0),
        ]}).set_index('Date')

Now I want to count all new customers each 10 days.

buyers = []

def novices(x):
    new = [n for n in x if n not in buyers]

    if (len(new) > 0): buyers.extend(new) 

    return len(new)


pd.rolling_apply(df['Buyer'], 10, novices)

throws an exception “ValueError: could not convert string to float: Carl”

However, although meaningless a call with a numeric column such as:

pd.rolling_apply(df['Quantity'], 2, novices)

works.

[jreback]

would always take a PR for this

[Darel13712]

@jreback Hello is there any possibility to get rolling.apply for objects in 2018?) It still ignores objects as of 0.22.0.

idx = pd.date_range(pd.to_datetime('2017-01-01'), pd.to_datetime('2017-01-03'))
df = pd.DataFrame([[1, 's'],[2, 't'],[3, 'r']], index=idx)

	0	1
2017-01-01	1	s
2017-01-02	2	t
2017-01-03	3	r

it’s ok to ignore objects with built-in functions

df.rolling(2, min_periods=1).sum()

	0	1
2017-01-01	1	s
2017-01-02	3	t
2017-01-03	5	r

but why can’t i handle objects myself?

def const(x):
    return 5
df.rolling(2, min_periods=1).apply(const)

	0	1
2017-01-01	5	s
2017-01-02	5	t
2017-01-03	5	r

This example above is not really useful but I want to be able to apply function to a column that contains objects.

The only solution I’ve found is to create your own DataFrame/Series type https://stackoverflow.com/questions/44479384/pandas-rolling-apply-doesnt-do-anything

But I really think this should be in pandas by default.