text: #!/usr/bin/python
  # Deepak Ramanath
  
  # Pandas tutorial with Pandas Series
  
  import sys
  import os
  import pandas as pd
  import numpy as np
  import matplotlib.pyplot as plt
  
  # List of maximim temperature for a particular week
  temp = [18, 24, 22, 17, 20, 27, 30]
  days = ['Mon', 'Tue', 'Wed', 'Thu', 'Fri', 'Sat', 'Sun']
  
  # Creating basic Pandas Series
  seriesTemp = pd.Series(temp)
  print seriesTemp
  
  # Pandas core class
  print type(seriesTemp)
  
  # Pandas core values
  print seriesTemp.values
  
  # Pandas core values are nothing but Numpy ndarray
  print type(seriesTemp.values)
  
  # Creating a new Pandas Series. Here, we index with days
  tempDays = pd.Series(temp, index = days)
  
  # Specifing names to Pnadas Series
  tempDays.name = 'Maximum Temperature'
  tempDays.index.name = 'Weekday'
  print tempDays
  
  # Creating a dictionary using exisiting lists
  dictTempDays = dict(zip(days, temp))
  print dictTempDays
  
  # We can create a Pnadas Series directly from a dictionary
  tempDays2 = pd.Series(dictTempDays)
  print tempDays2
  
  # Numpy arrays are homogeneous. One float values, makes the entire series float
  temp1 = [18, 24.2, 22, 17, 20, 27, 30]
  tempDays3 = pd.Series(temp1, index=days)
  print tempDays3
  
  # Looping over the Series using enumerate
  print "Looping using enumerate"
  for i, v in enumerate(tempDays3):
  	print "index: %s, value: %s" % (i, v)
  
  # Lopping over the Series using iteritems
  print "Looping using iteritems"
  for j, k in tempDays3.iteritems():
  	print "key: %s, value: %s" % (j, k)
  
  #Some simple vectorised operations
  print "Vector operation 1"
  tempDays4 = tempDays3 * 2
  print tempDays4
  
  print "Vector operation 2"
  tempDays5 =  tempDays3**2
  print tempDays5
  