Many standard methods do not work (properly) on XDataFrame with hierarchical data

[mloning]

# loading some time-series data
from io import BytesIO
from zipfile import ZipFile
from urllib.request import urlopen
from xpandas.data_container import XSeries, XDataFrame
import numpy as np
import pandas as pd

def read_data(file):
    data = file.readlines()
    rows = [row.decode('utf-8').strip().split('  ') for row in data]
    X = pd.DataFrame(rows, dtype=np.float)
    y = X.pop(0)
    ts = XSeries([row for _, row in X.iterrows()])
    X = XDataFrame({'ts1': ts, 'ts2': ts})
    return X, y

url = 'http://www.timeseriesclassification.com/Downloads/GunPoint.zip'
url = urlopen(url)
zipfile = ZipFile(BytesIO(url.read()))
file = zipfile.open('GunPoint_TRAIN.txt')
X, y = read_data(file)

X.mean() # returns empty series rather than mean of series, the same for many other methods like .std(), .median(), etc)

X.apply(np.mean) # breaks

X['ts1'].mean() # breaks 

X['ts1'].apply(np.mean) # works

X['ts1'].apply(np.percentile, args=(25,)) # breaks, does not passes on args