Now use the aggregation framework to calculate the author with the greatest number of comments. Check all that apply. You need to group twice to solve this problem. You will be using the zip code collection data set, which you will find in the ‘handouts’ link in this page. Your task is to calculate the class with the best average student performance. Some students have three homework assignments, etc.

Prefered Cities to Live! The documents look like this: In this assignment you will use the aggregation framework to find the most frequent author of comments on your blog. You need to group twice to solve this problem. Please use the Aggregation pipeline to solve this problem. In this problem you will calculate the number of people who live in a zip code in the US where the city starts with one of the following characthers:.

You need to group twice to solve this problem. To be clear, each student’s average includes only exams and homework grades. Your task is to calculate the class with the best average student performance.

# Mongodb homework

In this assignment you will use the aggregation framework to find the most frequent author of comments on your blog. For this problem, we have used a subset of the data you previously used in zips. Mongoxb use the Aggregation pipeline to solve this problem. Some students have three homework assignments, etc. Who’s the easiest grader on campus?

The documents look like this: The answer for CT and NJ using this data set is Also, you will need a filtering step to get rid of all documents where the city does not start with the select set of initial characters. Once you’ve generated your aggregation query and found your answer, select it from the choices below.

Using homewokr aggregation framework, calculate the sum total of people who are living in a zip code where the city starts with one of those possible first characters. We will take these are the prefered cities to live in chosen by this instructor, given is special affection to this set of characters!

Try for your self. At the end I just want to say if you want to learn mongoDB, First practice with youself.

This involves calculating an average for each student in each class of all non-quiz assessments and then averaging those numbers to get a class average. Then import into your homewok database as follows:.

## FacultÃ© des Lettres et des Sciences Humaines ben M’Sik Casablanca –

If you notice that while importing, there are a few duplicates fear not, this is expected and will not affect your answer. Check all that apply. Import it into your mongod using the following command from the command line:.

You will be homwork the zip code collection data set, which you will find in the ‘handouts’ link in this page.

# MongodbChamps: MJ: MongoDB for Java Developers Homework

Different states might have the same city name. You will need to probably change your projection to send more info through than just that first character.

After that, you just need to sort. Don’t include their quiz scores in the calculation.

For this set, there are only documents and zip codesand all of them are in New York, Connecticut, New Jersey, and California. Friday, 8 September Week 5: Those students achieved a class average of Crunching the Zipcode dataset Please calculate the average population of cities in California abbreviation CA and New York NY taken together with populations over 25, You must figure out the GPA that mongoodb student has achieved in ho,ework class and then average those numbers to get a mmongodb average.

For this problem, assume that a city name that appears in more than one state represents two separate cities. We will be using a data set similar to ones we’ve used before. Please choose your answer below for the most prolific comment author:.

To help you verify your work before submitting, the author with the fewest comments is Mariela Sherer and she commented times. For example, to extract the first character from the city field, you could write this pipeline:. Homswork use the aggregation framework to calculate the author with the greatest number of comments.