Python code (normal Python and not pyspark) to answer the following question.

"Social computing research at the University of Minnesota" has released moving rating data sets at different sizes at the "gouplens.org" website.

Load MovieLens 10M dataset, which consists of 10 million movie ratings.  You can download the data by going to grouplens.org, and under the "datasets" tab, upload "movieLens 10M dataset" it is 63 MB.

a) Divide the data to 5 almost equal size files and use the five files in the rest of the assignment (2 points) 

b) Sort the data from the highest rating movie to the lowest one. 

Measure how much time sorting takes. (6 points)

• Don't use the sort function, and write the sort function yourself.
• Use sort function

c). Create a histogram of the movie ratings. 

Measure how much time it takes to create the histogram. (2 points)

d). Data contains more than 10M ratings of 10681 movies by 71567 users. 

Create a histogram of the number of times each movie got rated. 

Measure how much time it takes to create the histogram. (4 points)

e). Choose the lowest three bins of histogram in part C and create a histogram of movie ratings for these three bins. Do the same thing for the top three bins of the histogram. (6 points)

Answer rating: 100% (QA)

To accomplish the tasks you described you can use Pythons standard libraries Heres a stepbystep approach a Divide the data into 5 almost equalsized files python import pandas as pd Load the MovieLens ... View the full answer