maks-ivanov

from datetime import datetime
match_wip['date'] = match_wip.date.map(lambda t: datetime.strptime(t, "%Y-%m-%d %H:%M:%S"))
match_wip.date

maks-ivanov

import numpy as np
import pandas as pd
from datetime import datetime
from fastparquet import write 



def compute_vwap(df):
    q = df['foreignNotional']
    p = df['price']

maks-ivanov

import numpy as np
from numba import jit
from numba import float64
from numba import int64

@jit((float64[:], int64), nopython=True, nogil=True)
def _ewma(arr_in, window):
    r"""Exponentialy weighted moving average specified by a decay ``window``
    to provide better adjustments for small windows via: