Time for action – calculating Volume Weighted Average Price

The following are the actions that we will take:

1. Read the data into arrays.

2. Calculate VWAP:

   from __future__ import print_function
   import numpy as np
   c,v=np.loadtxt('data.csv', delimiter=',', usecols=(6,7), unpack=True)
   vwap = np.average(c, weights=v)
   print("VWAP =", vwap)

   The output is as follows:

   VWAP = 350.589549353
   

What just happened?

That wasn't very hard, was it? We just called the average() function and set its weights parameter to use the v array for weights. By the way, NumPy also has a function to calculate the arithmetic mean. This is an unweighted average with all the weights equal to 1.

The mean() function

The mean() function is quite friendly and not so mean. This function calculates the arithmetic mean of an array.

Note

The arithmetic mean is given by the following formula:

It sums the values in an array a and divides the sum by the number of elements n (see https://www.khanacademy.org/math/probability/descriptive-statistics...