Data Science with Python Certification Data Science with Python Data Cleaning and Preparation 3

Question 1

What does `df.duplicated(keep='last')` return?

Accepted Answer

True for all duplicates except the last occurrence

Answer

keep='last' marks all duplicate occurrences as True except the final one, which is kept.

Question 2

Which technique is most appropriate for detecting outliers in a non-normally distributed dataset?

Accepted Answer

IQR (Interquartile Range) method

Answer

The IQR method is robust to skewed distributions because it relies on quartiles rather than mean and standard deviation.

Question 3

When using `pd.get_dummies()`, what does setting `dtype=int` accomplish?

Accepted Answer

Outputs 0/1 integers instead of True/False booleans

Answer

By default get_dummies returns bool dtype in newer pandas; dtype=int forces 0/1 integer output.

Question 4

What is the purpose of `sklearn.preprocessing.RobustScaler`?

Accepted Answer

Scales features using statistics that are robust to outliers (median and IQR)

Answer

RobustScaler centers data on the median and scales by IQR, reducing the influence of outliers compared to StandardScaler.

Question 5

Which pandas method efficiently applies a custom cleaning function to every element in a Series?

Accepted Answer

Series.map()

Answer

Series.map() applies a function element-wise to a Series and is the idiomatic pandas choice for element-level transformation.

Data Science with Python Certification Practice Test