Fun with Pandas `rolling_apply` and TypeError

Question

I\'m really struggling with the Pandas rolling_apply function. I\'m trying to apply a filter to some time series data like below and make a new series for outliers.

Answer 1

It's less than a helpful message, but I believe the error is happening because rolling_apply currently expects a like typed return array (may even have to be float). But, if you break your three operations (mean, std, outlier logic) into steps, it should work ok.

ts.name = 'value'

df = pd.DataFrame(ts)

def trimmed_apply(arr, alpha, f):
    np.sort(arr)
    n = len(arr)
    k = int(round(n*float(alpha))/2)
    return f(arr[k+1:n-k])

df['trimmed_mean'] = pd.rolling_apply(df['value'], window, trimmed_apply, args=(alpha, np.mean))
df['trimmed_std'] = pd.rolling_apply(df['value'], window, trimmed_apply, args=(alpha, np.std))

df['outlier'] = np.abs(arr - df['trimmed_mean']) < 3 *  df['trimmed_std'] + gamma