MCQOPTIONS
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MCQOPTIONS
This section includes 8 Mcqs, each offering curated multiple-choice questions to sharpen your Data Science knowledge and support exam preparation. Choose a topic below to get started.
| 1. |
Raw data in the real-world is tidy and properly formatted. |
| A. | True |
| B. | False |
| Answer» B. False | |
| 2. |
tidyr is a reframing of _______ designed to accompany the tidy data framework. |
| A. | reshape5 |
| B. | dplyr |
| C. | reshape2 |
| D. | all of the mentioned |
| Answer» D. all of the mentioned | |
| 3. |
Which of the following is the most common problem with messy data? |
| A. | Column headers are values |
| B. | Variables are stored in both rows and columns |
| C. | A single observational unit is stored in multiple tables |
| D. | All of the mentioned |
| Answer» E. | |
| 4. |
Strange binary file generated from machines is an example of tidy data. |
| A. | True |
| B. | False |
| Answer» C. | |
| 5. |
Which of the following process involves structuring datasets to facilitate analysis? |
| A. | Data tidying |
| B. | Data mining |
| C. | Data booting |
| D. | All of the mentioned |
| Answer» B. Data mining | |
| 6. |
Which of the following package is used for tidy data? |
| A. | tidyr |
| B. | souryr |
| C. | NumPy |
| D. | all of the mentioned |
| Answer» B. souryr | |
| 7. |
Which of the following is a trait of tidy data? |
| A. | each variable in one column |
| B. | each observation in different row |
| C. | one table for each kind of variable |
| D. | none of the mentioned |
| Answer» C. one table for each kind of variable | |
| 8. |
Which of the following is an example of tidy data? |
| A. | complicated JSON from facebook API |
| B. | complicated JSON from Twitter API |
| C. | unformatted excel file |
| D. | all of the mentioned |
| Answer» E. | |