In this book, we will try to use as many varied datasets as possible. This depends on the availability of the data. Unfortunately, this means that the subject of the data might not exactly match your interests. Every dataset has its own quirks, but the general skills you acquire in this book should transfer to your own field. In this chapter, we will load a number of Comma-separated Value (CSV) files into NumPy arrays in order to analyze the data.

To load the data, we will use the NumPy loadtxt() function as follows:

import numpy as np
from scipy.stats import scoreatpercentile

data = np.loadtxt("mdrtb_2012.csv", delimiter=',', usecols=(1,), skiprows=1, unpack=True)

print "Max method", data.max()
print "Max function", np.max(data)

print "Min method", data.min()
print "Min function", np.min(data)

print "Mean method", data.mean()
print "Mean function", np.mean(data)

print...