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Welcome to the Data Analysis with Python MCQs Page

Dive deep into the fascinating world of Data Analysis with Python with our comprehensive set of Multiple-Choice Questions (MCQs). This page is dedicated to exploring the fundamental concepts and intricacies of Data Analysis with Python, a crucial aspect of Data Science. In this section, you will encounter a diverse range of MCQs that cover various aspects of Data Analysis with Python, from the basic principles to advanced topics. Each question is thoughtfully crafted to challenge your knowledge and deepen your understanding of this critical subcategory within Data Science.

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Check out the MCQs below to embark on an enriching journey through Data Analysis with Python. Test your knowledge, expand your horizons, and solidify your grasp on this vital area of Data Science.

Note: Each MCQ comes with multiple answer choices. Select the most appropriate option and test your understanding of Data Analysis with Python. You can click on an option to test your knowledge before viewing the solution for a MCQ. Happy learning!

Data Analysis with Python MCQs | Page 3 of 7

Q21.
Which of the following is used to compute the percent change over a given number of periods?
Discuss
Answer: (a).pct_change
Discuss
Answer: (c).For Series and DataFrame objects, var normalizes by N-1 to produce unbiased estimates
Q23.
Which of the following object has a method cov to compute covariance between series?
Discuss
Answer: (a).Series
Q24.
Which of the following specifies the required minimum number of observations for each column pair in order to have a valid result?
Discuss
Answer: (a).min_periods
Discuss
Answer: (c).lxml does not make any guarantees about the results of it’s parse
Q26.
Which of the following is implemented on DataFrame to compute the correlation between like-labeled Series contained in different DataFrame objects?
Discuss
Answer: (a).corrwith
Q27.
rolling_count function gives the number of non-null observations.
Discuss
Answer: (b).False
Q28.
Which of the following method produces a data ranking with ties being assigned the mean of the ranks for the group?
Discuss
Answer: (a).rank
Q29.
Which of the following can potentially change the dtype of a series?
Discuss
Answer: (a).reindex_like
Q30.
cov and corr supports the optional min_periods keyword.
Discuss
Answer: (a).True
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