How to calculate all aggregations at once without using a loop over indices?

Question

How to calculate all aggregations at once without using a loop over indices?

%%time
import random
random.seed(1)
df = pd.DataFrame({'val':random.sample(range(10), 10)})

for j in range(10):
    for i in df.index:
        df.loc[i,'mean_last_{}'.format(j)] = df.loc[(df.index < i) & (df.index >= i - j),'val'].mean()
        df.loc[i,'std_last_{}'.format(j)] = df.loc[(df.index < i) & (df.index >= i - j),'val'].std()
        df.loc[i,'max_last_{}'.format(j)] = df.loc[(df.index < i) & (df.index >= i - j),'val'].max()
        df.loc[i,'min_last_{}'.format(j)] = df.loc[(df.index < i) & (df.index >= i - j),'val'].min()
        df.loc[i,'median_last_{}'.format(j)] = df.loc[(df.index < i) & (df.index >= i - j),'val'].median()

Answer 1

You could use the rolling method, see for example:

df = pd.DataFrame({'val': np.random.random(100)})
for i in range(10):
    agg = df["val"].rolling(i).aggregate(['mean', 'median'])
    df[[f"mean_{i}", f"median_{i}"]] = agg.values