Question

Q6b: Filtering Using this concept, filter df to only include rows that contain candy that is fruity or chocolate in some capacity (meaning, something that is both fruity and chocolate would be included). Store this output in df. # YOUR CODE HERE raise NotImplementedError() assert df.shape == (74, 10) assert not any(df['fruity_choco'] == 0)

          Q6b: Filtering
Using this concept, filter df to only include rows that contain
candy that is fruity or chocolate in some capacity (meaning,
something that is both fruity and chocolate would be
included).
Store this output in df.
# YOUR CODE HERE
raise NotImplementedError()
assert df.shape == (74, 10)
assert not any(df['fruity_choco'] == 0)

Q6b: Filtering
Using this concept, filter df to only include rows that contain
candy that is fruity or chocolate in some capacity (meaning,
something that is both fruity and chocolate would be
included).
Store this output in df.
# YOUR CODE HERE
raise NotImplementedError()
assert df.shape == (74, 10)
assert not any(df['fruitychoco'] == 0)

Added by Thomas M.

Computer Science and Information Technology

Trishna Knowledge Systems 2018 Edition

Instant Answer

Solved by Expert Luke Humphrey

Step 1

To do this, we can use the `isin()` method in pandas. We will create a boolean mask by checking if the values in the 'fruity' or 'chocolate' columns are True. Here's the code to filter the dataframe: ```python df = df[df['fruity'].isin([True]) | Show more…

Show all steps

Thanks for your feedback!

"Hello! I am currently self-taught pandas library using python right now, but I can not figure out the attached question. https://datascienceinpractice.github.io/assignments/D2_Pandas.html This is the link that I found this problem, so if you needed, feel free to look it up! Thank you in advance. Q6b: Filtering Using this concept, filter df to only include rows that contain candy that is fruity or chocolate in some capacity (meaning; something that is both fruity and chocolate wouldbe included): Store this output in df. # YOUR CODE HERE raise NotImplementedError() assert df. shape (74, 10) assert not any (df [ ' fruity_choco' ] == 0)"