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
call to 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”.
budget_lookup[budget_lookup.index.str.startswith('A')].sort_index()[[0]]
title
A Bag of Hammers 2000000
dtype: int64
budget_lookup[budget_lookup.index.str.startswith('B')].sort_index()[[-1]]
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
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