5.4. Filtering the Data¶
Let’s start by only looking at films that cost over a million dollars to make.
Create a variable called
budget_df that contains all columns for the movies
whose budget was over a million dollars.
budget_df =  budget_df.shape
With this more manageable list of 7000+ movies, I’d like to have a way to look up the budget of a particular movie.
Create a Series object called
budget_lookup such that you are able to use a
budget_lookup['Dead Presidents'] to find the budget of that movie.
budget_lookup =  budget_lookup['Dead Presidents']
I have figured out that the first (alphabetically) movie whose title starts with an “A” is “A Bag of Hammers” and the last movie that starts with a “B” is “Byzantium”.
title A Bag of Hammers 2000000 dtype: int64
title Byzantium 10000000 dtype: int64
Use that knowledge to create a series that contains budget informations for all
the movies that start with an “A” or a “B”. Hint: No need to use
startswith like I did above, just use the movie titles to do a slice.
budget_lookup_as_and_bs =  budget_lookup_as_and_bs.shape
During this lesson I was primarily in my...
- 1. Comfort Zone
- 2. Learning Zone
- 3. Panic Zone
Completing this lesson took...
- 1. Very little time
- 2. A reasonable amount of time
- 3. More time than is reasonable
Based on my own interests and needs, the things taught in this lesson...
- 1. Don't seem worth learning
- 2. May be worth learning
- 3. Are definitely worth learning
For me to master the things taught in this lesson feels...
- 1. Definitely within reach
- 2. Within reach if I try my hardest
- 3. Out of reach no matter how hard I try