Q.1
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
Q.2
Point out the correct statement.
  • a) Nearly 80% of data analysis is spent on wrangling data
  • b) Nearly 20% of data analysis is spent on data dredging
  • c) Nearly 80% of data analysis is spent on the cleaning and preparing data
  • d) None of the mentioned
Q.3
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
Q.4
Which of the following package is used for tidy data?
  • a) tidyr
  • b) souryr
  • c) NumPy
  • d) all of the mentioned
Q.5
Point out the wrong statement.
  • a) Tidy datasets are all alike but every messy dataset is messy in its own way
  • b) Most statistical datasets are data frames made up of rows and columns
  • c) Tidy datasets provide a standardized way to link the structure of a dataset with its semantics
  • d) None of the mentioned
Q.6
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
Q.7
Strange binary file generated from machines is an example of tidy data.
  • a) True
  • b) False
Q.8
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
Q.9
tidyr is a reframing of _______ designed to accompany the tidy data framework.
  • a) reshape5
  • b) dplyr
  • c) reshape2
  • d) all of the mentioned
Q.10
Raw data in the real-world is tidy and properly formatted.
  • a) True
  • b) False
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