Chapter 2 · Section 2 practice

Data Quality: Audit, Repair and Selection

0 of 6 answered

These questions review the examples in the companion slides. Choose an answer, then check the explanation.

Question 1

What does df.isna().sum() report by default?

  • Missing-value counts for each column
  • The number of complete rows
  • The column means
  • Only repeated observations

Question 2

What does df.dropna(subset=["price"]) retain?

  • Only rows with every column observed
  • Only columns without missing values
  • Rows where price is missing
  • Rows with an observed price, regardless of missing values in other columns

Question 3

In time-sorted data, which replacement uses the preceding observed value?

  • fillna(0)
  • dropna()
  • ffill()
  • bfill()

Question 4

Two timestamps each appear twice. How many rows does index.duplicated(keep=False) mark?

  • 1
  • 4
  • 2
  • 0

Question 5

Which expression keeps rows with price strictly between 10 and 20?

  • df.loc[(df["price"] > 10) & (df["price"] < 20)]
  • df.loc[df["price"] > 10 & df["price"] < 20]
  • df.loc[df["price"] > 20]
  • df.loc[df["price"] < 10]

Question 6

A column has a five-month gap. What should happen before replacing it with a constant?

  • Fill it because every gap must be removed
  • Assume all missing values are zero
  • Delete every column in the dataset
  • Inspect the source, gap and effect of the proposed replacement