#getttsburg addresss analysis
#count words, unique words, common wrods
#here we want to do word frequence analysis of the addresss
import string
import numpy
import pylab
def processLine(line,wcDict):
	#cut the whitespace before and after everyline
	#sitll use strip method to seperate different words
	wordlist=line.strip().split()
	for word in wordlist:
		if word !="--":
			word=word.lower()
			word=word.strip()
			word=word.strip(string.punctuation)
			addword(word,wcDict)
def addword(w,wcDict):
	if w in wcDict:
		wcDict[w]+=1
	else:
		wcDict[w]=1
def prettyPrint(wcDict):
	valkeyList=[]
	for key,val in wcDict.items():
		valkeyList.append((val,key))
	valkeyList.sort(reverse=True)
	print '%-10s%10s'%('word','count')
	print '-'*21
	for val,key in valkeyList:
		if (len(key) >3) and (val>2) :
			print '%-12s %3d'%(key,val)
def barGraph(wcDict):
 wordlist=[]
 for key,val in wcDict.items():
 if val>2 and len(key)>3:
 wordlist.append((key,val))
 wordlist.sort()
 keylist=[key for key,val in wordlist]
 vallist=[val for key,val in wordlist]
 barwidth=0.5
 xVal=numpy.arange(len(keylist))
 pylab.xticks(xVal+barwidth/2.0,keylist,rotation=45)
 pylab.bar(xVal,vallist,width=barwidth,color='y')
 pylab.show()
#main programe
wcDict={}
fObj=open("gettysburg.txt",'r')
for line in fObj:
 processLine(line,wcDict)
print 'Length of the wcDict is:', len(wcDict)
prettyPrint(wcDict)
barGraph(wcDict)