onpaster.blogg.se -

#The most unknown metacritic manual#

As a part of this subtask, you need to aggregate a few values over these 3 columns. There are 3 columns in the dataframe - genre_1, genre_2, and genre_3. Subtask 3.1 Combine the Dataframe by Genres.Also, which is the most popular trio after applying the condition above? Write your answers in the markdown cell provided below.

#The most unknown metacritic manual#

You can do a manual inspection of the top 5 popular trios you have found in the previous subtask and check how many of those trios satisfy this condition. Having this condition ensures that you aren't getting any unpopular actor in your trio (since the total likes calculated in the previous question doesn't tell anything about the individual popularities of each actor in the trio.). Since in this case, actor_3_facebook_likes is 30000, which is less than half of actor_1_facebook_likes. For example, the following is a valid combo: The condition is none of the three actors' Facebook likes should be less than half of the other two. Let's add a small condition to it and make sure that all three actors are popular. In the previous subtask you found the popular trio based on the total number of facebook likes.

Subtask 2.5: Find the Most Popular Trios - II.

Sort these values in a descending order of Avg_rating and retain only the movies with a rating equal to or greater than 8 and store these movies in a new dataframe UniversalAcclaim.

Refer to this link to know how abs() funtion works.

Retain only the movies in which the absolute difference(using abs() function) between the IMDb_rating and Metacritic columns is less than 0.5.

Create a new column Avg_rating which will have the average of the MetaCritic and Rating columns.

Now, to find out the movies which have been liked by both critics and audiences alike and also have a high rating overall, you need to.

First convert the MetaCritic column to a scale of 10.

Firstly you will notice that the MetaCritic score is on a scale of 100 whereas the IMDb_rating is on a scale of 10.

This rating is determined by taking the average of hundred-thousands of ratings from the general audience.Īs a part of this subtask, you are required to find out the highest rated movies which have been liked by critics and audiences alike. Second, you also have another column IMDb_rating which tells you the IMDb rating of a movie. This is a very popular website where an average score is determined through the scores given by the top-rated critics.

You might have noticed the column MetaCritic in this dataset. Subtask 2.3: The General Audience and the Critics.7 actor_1_facebook_likes 100 non-null int64Ĩ actor_2_facebook_likes 99 non-null float64ĩ actor_3_facebook_likes 98 non-null float64ĭtypes: float64(21), int64(32), object(9)