getting unique values and counting amounts

[Truman]

#  getting unique ngrams out of duplicates and counting how many times ngram appears
import requests
from bs4 import BeautifulSoup
import re
import string
from collections import OrderedDict

def cleanInput(input):
	input = re.sub('\n', " ", input)
	input = re.sub('\[[0-9]*\]', "", input)
	input = re.sub(' +', " ", input)
	input = bytes(input, "UTF-8")
	input = input.decode("ascii", "ignore")
	input = input.upper()
	cleanInput = []
	input = input.split(' ')
	for item in input:
		item = item.strip(string.punctuation)
		if len(item) > 1 or (item.lower() == 'a' or item.lower() == 'i'):
			cleanInput.append(item)
	return cleanInput

def getNgrams(input, n):
	input = cleanInput(input)
	output = dict()
	for i in range(len(input)-n+1):
		newNGram = " ".join(input[i:i+n])
		if newNGram in output:
			output[newNGram] += 1
		else:
			output[newNGram] = 1
	return output

html = requests.get("http://en.wikipedia.org/wiki/Python_(programming_language)")
bsObj = BeautifulSoup(html.content, 'html.parser')
content = bsObj.find("div", {"id": "mw-content-text"}).get_text()
ngrams = getNgrams(content, 2)
ngrams = OrderedDict(sorted(ngrams.items(), key=lambda t: t[1], reverse=True))
print(ngrams)
print("2-grams count is: "+str(len(ngrams)))

I'm working on this example of n-gram extraction in the book of web scraping. What surprised me is that program didn't find any duplicate, for each n-gram that consists of two words there is number '1'. In the book the given output is much different. For example,

Output:
('of the', 38)

is sorted first, therefore I'm wondering if I'm doing something wrong.
Could you also give me an explanation of this line:

ngrams = OrderedDict(sorted(ngrams.items(), key=lambda t: t[1], reverse=True))

Particulary this chunk: key=lambda t: t[1]
Don't understand what is it for...