Python Programming for Quantitative Economics

This website presents a set of lectures on python programming for quantitative economics, designed and written by Thomas J. Sargent and John Stachurski.

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A python program for neural network trained with backpropagation with sigmoid function

import numpy as np
def nonlin(x,deriv=False):
if(deriv==True):
return x*(1-x)
return 1/(1+np.exp(-x))
X = np.array([ [0,0,1],
[0,1,1],
[1,0,1],
[1,1,1] ])
y = np.array([[0,0,1,1]]).T
np.random.seed(1)
syn0 = 2*np.random.random((3,1)) - 1
for iter in range(10000):
l0 = X
l1 = nonlin(np.dot(l0,syn0))
l1_error = y - l1
l1_delta = l1_error * nonlin(l1,True)
syn0 += np.dot(l0.T,l1_delta)
print ("Output After Training:")
print (l1)

Pong - Python Game Tutorial

A Pong clone game tutorial for beginners using Python 3

First Come First Serve Process scheduling using python

process = []
total_waiting_time = 0
n = int(raw_input('Enter the total no of processes: '))
for i in xrange(n):
    process.append([])
    process[i].append(raw_input('Enter process name: '))
    process[i].append(int(raw_input('Enter process arrival time : ')))
    total_waiting_time += process[i][1]
    process[i].append(int(raw_input('Enter process  burst time: ')))
    print ''

process.sort(key = lambda process:process[1])

print 'Process Name\tArrival Time\tBurst Time'
for i in xrange(n):
    print process[i][0],'\t\t',process[i][1],'\t\t',process[i][2]
   
print 'Total waiting time: ',  total_waiting_time
print 'Average waiting time: ',(total_waiting_time/n)

Python Any Where - Host, run, and code Python in the cloud

Basic plan gives you access to machines with a full Python environment already installed for free. You can develop and host your website or any other code directly from your browser without having to install software or manage your own server.

Python Any Where