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Class XII Python (Pandas) – MCQs (Set 2)
21. Which of the following creates an empty DataFrame?
A. pd.DataFrame()
B. pd.DataFrame([])
C. Both A and B
D. None of the above
Answer: C
22. What will df.size return?
A. Number of rows
B. Number of columns
C. Rows × Columns
D. Shape of DataFrame
Answer: C
23. Which function is used to rename columns?
A. df.reindex()
B. df.rename()
C. df.change()
D. df.modify()
Answer: B
24. Which parameter in read_csv() changes the column names?
A. names
B. header
C. index_col
D. columns
Answer: A
25. Which command selects multiple columns?
A. df['A','B']
B. df[['A','B']]
C. df('A','B')
D. df[A+B]
Answer: B
26. Which statement is TRUE about Series?
A. It is two-dimensional
B. It can store heterogeneous data
C. It has labeled index
D. It cannot contain NaN
Answer: C
27. Which function is used to sort data by column values?
A. df.sort()
B. df.sort_index()
C. df.sort_values()
D. df.order()
Answer: C
28. Which argument sorts data in descending order?
A. reverse=True
B. ascending=False
C. order=desc
D. desc=True
Answer: B
29. What will df.columns return?
A. Data types
B. Column names
C. Index values
D. Row data
Answer: B
30. Which command removes a column permanently?
A. df.remove()
B. df.drop()
C. del df['column']
D. Both B and C
Answer: D
31. Which function counts non-null values?
A. df.size
B. df.count()
C. df.shape
D. df.info()
Answer: B
32. Which option correctly replaces missing values with 0?
A. df.fillna(0)
B. df.replace(0)
C. df.dropna(0)
D. df.nan(0)
Answer: A
33. Which statement accesses row with index label 3?
A. df.iloc[3]
B. df.loc[3]
C. df.row(3)
D. df[3]
Answer: B
34. Which statement accesses row at position 3?
A. df.loc[3]
B. df.index[3]
C. df.iloc[3]
D. df.row(3)
Answer: C
35. Which function displays memory usage and data types?
A. df.describe()
B. df.shape
C. df.info()
D. df.memory()
Answer: C
36. Which operation adds a new column?
A. df.add()
B. df['New'] = values
C. df.insert()
D. Both B and C
Answer: D
37. Which method converts DataFrame to NumPy array?
A. df.array()
B. df.to_numpy()
C. df.numpy()
D. df.values()
Answer: B
38. Which function returns unique values?
A. df.unique()
B. df.nunique()
C. df['col'].unique()
D. df.distinct()
Answer: C
39. Which method returns number of unique values?
A. unique()
B. count()
C. nunique()
D. distinct()
Answer: C
40. Which argument skips rows while reading CSV?
A. skiprow
B. skip_rows
C. skiprows
D. rowskip
Answer: C
