Practice Recommendation : Problem data dataset

recommendation_engin

#1

Hello all,
problem_data dataset has many missing data. I tried to understand the relationship between level_type and tags with the points and I found a small strange thing. For example: when the level_type is: B and tags is: implementation the points differ from a problem_id to another.

The first question: why would the points differ even though the level type and the tag is the same ?
The second question: for level types above H ( from I to N), all the points are missing. how can we get an idea about the points ? for the other types ( A to H ) we at least can see the mean and median which gives us an idea about them.

Thank you


#2

Please, put some data to see , we can’t give you proper answers if there are no data to examine.
At least put a link to the dataset or upload some pictures.


#3

Thank you for your response. The dataset is from this link: practice-problem-recommendation-engine . its name is: problem_data.csv

I attached a photo showing that the level types from I to N doesn’t have any values. I made an assumption, for each level there is a constant number of points as the following:

1- for level type: A the points is: 500
2- for level type: B the points is: 1000
3- for level type: C the points is: 1500
4- for level type: D the points is: 2000
5- for level type: E the points is: 2500
6- for level type: F the points is: 3000
7- for level type: G the points is: 3500
8- for level type: H the points is: 3750
9- for level type: I the points is: 4000
10- for level type: J the points is: 4500
11- for level type: K the points is: 5000
12- for level type: L the points is: 5500
13- for level type: M the points is: 6000
14- for level type: N the points is: 6500

If my assumption was right that means the points are related to level type no matter what the tags are.