The code block shown contains an error. The code block is intended to return a new DataFrame where column sqft from DataFrame storesDF has had its missing values replaced with the value 30,000…

Question

Options

• AThe argument to the subset parameter of fill() should be a string column name or a list of string
• BThe na.fill() operation does not work and should be replaced by the dropna() operation.
• Che argument to the subset parameter of fill() should be a the numerical position of the column
• DThe na.fill() operation does not work and should be replaced by the nafill() operation.
• EThe na.fill() operation does not work and should be replaced by the fillna() operation.

• A
  91% (51)
• C
  5% (3)
• D
  2% (1)
• E
  2% (1)

Explanation

The na.fill(value, subset) method's subset parameter must be a string column name or a list of string column names - it does not accept a Spark Column object. The code storesDF.na.fill(30000, col("sqft")) passes col("sqft") (a Column object) as the subset argument, which will raise a TypeError. The correct call is storesDF.na.fill(30000, ["sqft"]) or storesDF.na.fill(30000, "sqft"). Option A correctly identifies this error. Options B and D are wrong because na.fill() is a valid and working method. Option C is wrong because position-based column identification is not how fill() works. Option E is wrong because na.fill() and fillna() are equivalent aliases in Spark - one does not need to replace the other.

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