MS-DS Master of Data science FREE MS-DS Master of Data science Data Wrangling and Preprocessing Questions and Answers 2

Question 1

Which pandas method is most appropriate for combining two DataFrames that share a common key column?

Accepted Answer

merge()

Answer

The merge() function performs database-style joins on DataFrames using one or more common key columns.

Question 2

What is the primary purpose of one-hot encoding in data preprocessing?

Accepted Answer

Converting categorical variables into binary columns

Answer

One-hot encoding transforms each category of a categorical variable into a separate binary column indicating presence or absence.

Question 3

When dealing with a heavily right-skewed numerical feature, which transformation is commonly applied to reduce skewness?

Accepted Answer

Log transformation

Answer

Log transformation compresses the range of large values and spreads out smaller values, effectively reducing right skewness.

Question 4

What does the pandas melt() function accomplish in data wrangling?

Accepted Answer

Converts wide-format data to long-format

Answer

The melt() function unpivots a wide-format DataFrame into a longer format by turning column headers into row values.

Question 5

Which strategy for handling missing data is most likely to introduce bias when data is not missing completely at random?

Accepted Answer

Listwise deletion

Answer

Listwise deletion removes entire rows with any missing values, which can systematically exclude certain subgroups and introduce bias when missingness depends on observed or unobserved data.

MS-DS Master of Data science Practice Test

MS-DS Master of Data science Practice Test

MS-DS Master of Data science FREE MS-DS Master of Data science Data Wrangling and Preprocessing Questions and Answers 2