Q8a: sort_values Specifically, df is currently sorted in alphabetical order by competitor name (candy). What if we were most curious about the sugar percentile of where the candy falls within the dataset? Arrange the rows in df such that the candy with the highest sugarpercent is displayed first and the lowest sugarpercent last. Store this in df. Also, note that when using sort_values , the original indices are retained. So, also reset the index of df so that the highest sugarpercent candy is index 0. I # YOUR CODE HERE df = df.sort_values (by=['sugarpercent'], inplace True) %3D I assert df.loc[0,'competitorname'] != '100 Grand' assert np.allclose(df.loc[0,'sugarpercent'], 0.988) AttributeError Traceback (most recent call last) in ----> 1 assert df.loc[0,'competitorname'] != '100 Grand' 2 assert np.allclose(df.loc[0,'sugarpercent'], 0.988) AttributeError: 'NoneType' object has no attribute 'loc'
Q8a: sort_values Specifically, df is currently sorted in alphabetical order by competitor name (candy). What if we were most curious about the sugar percentile of where the candy falls within the dataset? Arrange the rows in df such that the candy with the highest sugarpercent is displayed first and the lowest sugarpercent last. Store this in df. Also, note that when using sort_values , the original indices are retained. So, also reset the index of df so that the highest sugarpercent candy is index 0. I # YOUR CODE HERE df = df.sort_values (by=['sugarpercent'], inplace True) %3D I assert df.loc[0,'competitorname'] != '100 Grand' assert np.allclose(df.loc[0,'sugarpercent'], 0.988) AttributeError Traceback (most recent call last) in ----> 1 assert df.loc[0,'competitorname'] != '100 Grand' 2 assert np.allclose(df.loc[0,'sugarpercent'], 0.988) AttributeError: 'NoneType' object has no attribute 'loc'
Computer Networking: A Top-Down Approach (7th Edition)
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Use python to solve the following
![Q8a: sort_values
Specifically, df is currently sorted in alphabetical order by competitor name (candy). What if we
were most curious about the sugar percentile of where the candy falls within the dataset?
Arrange the rows in df such that the candy with the highest sugarpercent is displayed first
and the lowest sugarpercent last. Store this in df.
Also, note that when using sort_values , the original indices are retained. So, also reset the
index of df so that the highest sugarpercent candy is index 0.
I # YOUR CODE HERE
df
df.sort_values (by=['sugarpercent'], inplace
True)
%3D
I assert df.loc[0,'competitorname'] != '100 Grand'
assert np.allclose(df.loc[0,'sugarpercent'], 0.988)
AttributeError
Traceback (most recent call last)
<ipython-input-41-81415551f891> in <module>
-> 1 assert df.loc[0,'competitorname'] != '100 Grand'
2 assert np.allclose(df.loc[0,'sugarpercent'], 0.988)
---
AttributeError: 'NoneType' object has no attribute 'loc'](/v2/_next/image?url=https%3A%2F%2Fcontent.bartleby.com%2Fqna-images%2Fquestion%2F3200e892-7b83-4670-8aa5-c4c84f2a6adb%2F43006247-300e-4a5b-8a4d-f8a088c30502%2Fi3pi93e_processed.png&w=3840&q=75)
Transcribed Image Text:Q8a: sort_values
Specifically, df is currently sorted in alphabetical order by competitor name (candy). What if we
were most curious about the sugar percentile of where the candy falls within the dataset?
Arrange the rows in df such that the candy with the highest sugarpercent is displayed first
and the lowest sugarpercent last. Store this in df.
Also, note that when using sort_values , the original indices are retained. So, also reset the
index of df so that the highest sugarpercent candy is index 0.
I # YOUR CODE HERE
df
df.sort_values (by=['sugarpercent'], inplace
True)
%3D
I assert df.loc[0,'competitorname'] != '100 Grand'
assert np.allclose(df.loc[0,'sugarpercent'], 0.988)
AttributeError
Traceback (most recent call last)
<ipython-input-41-81415551f891> in <module>
-> 1 assert df.loc[0,'competitorname'] != '100 Grand'
2 assert np.allclose(df.loc[0,'sugarpercent'], 0.988)
---
AttributeError: 'NoneType' object has no attribute 'loc'
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