Data Science Data Wrangling and Preprocessing 4

Question 1

Two rows have identical values across all columns. What wrangling step removes them?

Accepted Answer

Deduplication (drop_duplicates)

Answer

Imputation

Answer

Normalization

Answer

Pivoting

Question 2

A 'state' column contains 'CA', 'Ca', 'calif.', and 'California' for the same state. This is an example of what problem?

Accepted Answer

Inconsistent categorical values needing standardization

Answer

Missing data

Answer

Outliers

Answer

Multicollinearity

Question 3

Using the IQR method, an outlier is typically a value beyond which boundary?

Accepted Answer

Below Q1 - 1.5*IQR or above Q3 + 1.5*IQR

Answer

Below the mean

Answer

Above the median

Answer

More than 1 standard deviation away

Question 4

You have monthly sales spread across 12 separate columns (Jan...Dec). Reshaping into a single 'month' column and 'sales' column is called what?

Accepted Answer

Melting / unpivoting to long format

Answer

Pivoting to wide format

Answer

Joining

Answer

Binning

Question 5

Converting a continuous 'age' feature into groups like 'child', 'adult', 'senior' is known as what?

Accepted Answer

Binning (discretization)

Answer

Standardization

Answer

One-hot encoding

Answer

Normalization

Question 6

Why is it risky to drop an entire column that has 60% missing values without investigation?

Accepted Answer

The missingness itself may carry predictive signal

Answer

It always improves accuracy

Answer

Columns can never be dropped

Answer

It changes the row count

Question 7

Which pandas operation would you use to apply a custom cleaning function to every element of a Series?

Accepted Answer

Series.apply() / map()

Answer

Series.merge()

Answer

Series.pivot()

Answer

Series.concat()