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AssertionError Traceback (most re in 1 assert news_df.isna(). sum().sum() (18731, 3) ----> 2 assert news_df.shape == AssertionFrror:

AssertionError Traceback (most re in 1 assert news_df.isna(). sum().sum() (18731, 3) ----> 2 assert news_df.shape == AssertionFrror:

Database System Concepts
Database System Concepts
7th Edition
ISBN:9780078022159
Author:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan
Publisher:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan
Chapter1: Introduction
Section: Chapter Questions
Problem 1PE
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Python AssertionError?

category subject message 16150 politics,National Crime Survey,"Well, I droppe... NaN NaN 256 politics,Re: Europe vs. Muslim Bosnians,"I lik... NaN NaN 8355 recreational,Re: wife wants convertible,": :.. NaN NaN 9609 religion,"Re: After 2000 years, can we say tha... NaN NaN 8288 recreational,Re Aftermarket A/C units,"| I loo.. NaN NaN I assert isinstance(news_df, pd.DataFrame) assert len(news_df) == 18773 assert list(news_df.columns) == ['category', 'subject', 'message'] 1b) Remove null observations Given that we are carrying out a classification/prediction task, we're going to drop null values from the dataframe. Drop any rows containing null values in any of the three columns of news df . Store this back into news df . I # YOUR CODE HERE news_df.dropna(axis = 0, how = 'any', thresh = None, subset = None, inplace news df = False) %3D news_df.dropna() news_df category subject message I assert news_df.isna().sum().sum() == 0 assert news_df.shape (18731, 3) == AssertionError Traceback (most recent call last) <ipython-input-8-3f29b6a44f79> in <module> 1 assert news_df.isna().sum().sum() (18731, 3) == 0 ----> 2 assert news_df.shape == AssertionError:
Transcribed Image Text:category subject message 16150 politics,National Crime Survey,"Well, I droppe... NaN NaN 256 politics,Re: Europe vs. Muslim Bosnians,"I lik... NaN NaN 8355 recreational,Re: wife wants convertible,": :.. NaN NaN 9609 religion,"Re: After 2000 years, can we say tha... NaN NaN 8288 recreational,Re Aftermarket A/C units,"| I loo.. NaN NaN I assert isinstance(news_df, pd.DataFrame) assert len(news_df) == 18773 assert list(news_df.columns) == ['category', 'subject', 'message'] 1b) Remove null observations Given that we are carrying out a classification/prediction task, we're going to drop null values from the dataframe. Drop any rows containing null values in any of the three columns of news df . Store this back into news df . I # YOUR CODE HERE news_df.dropna(axis = 0, how = 'any', thresh = None, subset = None, inplace news df = False) %3D news_df.dropna() news_df category subject message I assert news_df.isna().sum().sum() == 0 assert news_df.shape (18731, 3) == AssertionError Traceback (most recent call last) <ipython-input-8-3f29b6a44f79> in <module> 1 assert news_df.isna().sum().sum() (18731, 3) == 0 ----> 2 assert news_df.shape == AssertionError:
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