human
Give me a code to 3 given the following:
3.2.1
Using 2 reducers: What are the top 50 most frequent terms in your word count analysis? 
Present the top 50 terms and their frequency and their relative frequency. Present the top 50 terms and their frequency and their relative frequency. If there are ties please sort the tokens in alphanumeric/string order. Present bottom 10 tokens (least frequent items). Please use a combiner.
HW3.3. Shopping Cart Analysis
Product Recommendations: The action or practice of selling additional products or services 
to existing customers is called cross-selling. Giving product recommendation is 
one of the examples of cross-selling that are frequently used by online retailers. 
One simple method to give product recommendations is to recommend products that are frequently
browsed together by the customers.
For this homework use the online browsing behavior dataset located at: 
   https://www.dropbox.com/s/zlfyiwa70poqg74/ProductPurchaseData.txt?dl=0

Each line in this dataset represents a browsing session of a customer. 
On each line, each string of 8 characters represents the id of an item browsed during that session. 
The items are separated by spaces.
Here are the first few lines of the ProductPurchaseData 
FRO11987 ELE17451 ELE89019 SNA90258 GRO99222 
GRO99222 GRO12298 FRO12685 ELE91550 SNA11465 ELE26917 ELE52966 FRO90334 SNA30755 ELE17451 FRO84225 SNA80192 
ELE17451 GRO73461 DAI22896 SNA99873 FRO86643 
ELE17451 ELE37798 FRO86643 GRO56989 ELE23393 SNA11465 
ELE17451 SNA69641 FRO86643 FRO78087 SNA11465 GRO39357 ELE28573 ELE11375 DAI54444 
Do some exploratory data analysis of this dataset guided by the following questions:. 
How many unique items are available from this supplier?
Using a single reducer: Report your findings such as number of unique products.
largest basket.
report the top 50 most frequently purchased items,  their frequency,  and their relative frequency (break ties by sorting the products alphabetical order) etc. using Hadoop Map-Reduce."
Please write code following the instructions in jupyter notebook style.
assistant
#Here is code to 3.

!head -n 10 Temp_data/ProductPurchaseData.txt

%%writefile ProductPurchaseStats.py

from mrjob.job import MRJob
from mrjob.step import MRStep
import sys
import heapq

class TopList(list):
    def __init__(self, max_size):
        """
        Just like a list, except the append method adds the new value to the 
        list only if it is larger than the smallest value (or if the size of 
        the list is less than max_size). If each element of the list is an int
        or float, uses that value for comparison. If the first element is a 
        list or tuple, uses the first element of the list or tuple for the 
        comparison.
        """
        self.max_size = max_size
        
    def _get_key(self, x):
        return x[0] if isinstance(x, (list, tuple)) else x
        
    def append(self, val):
        key=lambda x: x[0] if isinstance(x, (list, tuple)) else x
        if len(self) < self.max_size:
            heapq.heappush(self, val)
        elif self._get_key(self[0]) < self._get_key(val):
            heapq.heapreplace(self, val)
            
    def final_sort(self):
        return sorted(self, key=self._get_key, reverse=True)

class ProductPurchaseStats(MRJob):
    
    def mapper_init(self):
        self.largest_basket = 0
        self.total_items = 0
    
    def mapper(self, _, lines):
        products = lines.split()
        n_products = len(products)
        self.total_items += n_products
        if n_products > self.largest_basket:
            self.largest_basket = n_products
        for prod in products:
            yield (prod, 1)
            
    def mapper_final(self):
        self.increment_counter("product stats", "largest basket", self.largest_basket)
        yield ("*** Total", self.total_items)
        
    def combiner(self, keys, values):
        yield keys, sum(values)
        
    def reducer_init(self):
        self.top50 = TopList(50)
        self.total = 0
        
    def reducer(self, key, values):
        value_count = sum(values)
        
        if key == "***...