Class 12 IP: Python Pandas 50 MCQs Online Practice Test (Instant Result)

Class XII - Informatics Practices (065)

Python Pandas – I & II | 50 Important MCQs Test

📋 Total Questions: 50 🎯 Full Marks: 50 ⏱️ CBSE Board Prep 2026-27

1. Which of the following is the correct way to import Pandas?

A. import pandas as pd B. import pd as pandas C. include pandas D. import panda

2. Which Pandas data structure is one-dimensional and labelled?

A. DataFrame B. Series C. Array D. Tuple

3. Which Pandas data structure is two-dimensional?

A. Series B. List C. DataFrame D. Dictionary

4. Which function is used to create a Series?

A. pd.series() B. pd.Series() C. pd.createSeries() D. pd.SeriesData()

5. Which function is used to create a DataFrame?

A. pd.Frame() B. pd.dataframe() C. pd.DataFrame() D. pd.createFrame()

6. By default, how many rows are displayed by head()?

A. 3 B. 5 C. 7 D. 10

7. Which function displays the last five rows of a DataFrame by default?

A. start() B. last() C. tail() D. bottom()

8. Which function is used to read a CSV file in Pandas?

A. pd.open_csv() B. pd.read_csv() C. pd.get_csv() D. pd.csv_read()

9. Which method is used to save a DataFrame as a CSV file?

A. save_csv() B. write_csv() C. to_csv() D. export_csv()

10. In a Series, labels associated with values are called:

A. Columns B. Indexes C. Fields D. Headers

11. What does df.shape return?

A. Only number of rows B. Only number of columns C. Rows and columns as a tuple D. Data types

12. What does df.columns return?

A. Row labels B. Column labels C. Data values D. Data types

13. What does df.index return?

A. Column names B. Row labels/index C. Number of rows D. Data types

14. Which attribute displays the data types of columns?

A. df.type B. df.dtype C. df.dtypes D. df.datatype

15. Which argument is commonly used in drop() to specify a column?

A. axis=0 B. axis=1 C. column=1 D. col=True

16. Which value commonly represents a missing value in Pandas?

A. NULL B. 0 C. NaN D. EMPTY

17. Which of the following creates a Series with values 10, 20 and 30?

A. pd.Series([10,20,30]) B. pd.series(10,20,30) C. pd.Series(10,20,30) D. pd.create([10,20,30])

18. What is the default index of pd.Series([10,20,30])?

A. 1,2,3 B. 0,1,2 C. 10,20,30 D. a,b,c

19. What is the output of s[1] if s = pd.Series([10,20,30])?

A. 10 B. 20 C. 30 D. Error

20. Which expression selects elements from position 1 up to but not including 4?

A. s[1:4] B. s[1,4] C. s[0:4] D. s[1::4]

21. Which statement creates a Series from a dictionary?

A. pd.Series({'A':10,'B':20}) B. pd.Series(A=10,B=20) C. pd.DictionarySeries({'A':10}) D. pd.SeriesDict({'A':10})

22. When a scalar is used to create a Series, what is required?

A. A CSV file B. An index C. A DataFrame D. A column name

23. Which statement is correct for scalar Series creation?

A. pd.Series(5, index=['A','B']) B. pd.Series([5], index='A') C. pd.Series.scalar(5) D. pd.scalarSeries(5)

24. Which operator can be used for element-wise addition of two compatible Series?

A. + B. // C. ** D. <>

25. Which method returns the maximum value of a Series?

A. largest() B. max() C. maximum() D. top()

26. Which method returns the minimum value of a Series?

A. min() B. minimum() C. smallest() D. bottom()

27. Which method returns the sum of values in a Series?

A. total() B. add() C. sum() D. plus()

28. Which statement creates a DataFrame from a dictionary of lists?

A. pd.DataFrame({'Name':['A','B'],'Marks':[80,90]}) B. pd.Frame({'Name':['A']}) C. pd.DataFrame(Name='A',Marks=80) D. pd.createFrame(['A',80])

29. Which statement creates a DataFrame from a list of dictionaries?

A. pd.DataFrame([{'Name':'A','Marks':80}]) B. pd.DataFrame({'Name':'A','Marks':80}) C. pd.ListFrame([80]) D. pd.DataFrameList({'A':80})

30. How can a new column 'Grade' be added to df?

A. df.add('Grade') B. df['Grade'] = values C. df.column('Grade') D. df.new('Grade')

31. Which statement selects the Marks column from df?

A. df(Marks) B. df['Marks'] C. df.Marks() D. df.select(Marks)

32. Which statement selects two columns Name and Marks?

A. df['Name','Marks'] B. df[['Name','Marks']] C. df[Name,Marks] D. df.columns('Name','Marks')

33. Which statement deletes a column named Marks?

A. df.delete('Marks') B. df.remove('Marks') C. df.drop('Marks', axis=1) D. df.erase('Marks')

34. Which statement renames Marks to Score?

A. df.rename({'Marks':'Score'}) B. df.rename(columns={'Marks':'Score'}) C. df.change('Marks','Score') D. df.column_rename('Marks','Score')

35. What does axis=1 generally refer to in DataFrame operations?

A. Rows B. Columns C. Index values only D. Cells

36. What does axis=0 generally refer to in DataFrame operations?

A. Columns B. Rows/index C. Cells D. Headers only

37. Which expression filters rows where Marks are greater than 80?

A. df['Marks'] > 80 B. df[df['Marks'] > 80] C. df.filter(Marks>80) D. df[Marks > 80]

38. What type of selection is df[df['Marks'] > 80]?

A. Sequential indexing B. Boolean indexing C. String indexing D. Random indexing

39. Which command displays the first 3 rows?

A. df.head(3) B. df.top(3) C. df.first(3) D. df.start(3)

40. Which command displays the last 3 rows?

A. df.end(3) B. df.tail(3) C. df.last(3) D. df.bottom(3)

41. What does df.info() provide?

A. Only first row B. Summary information about the DataFrame C. Only column names D. A graph

42. Which statement reads student.csv into a DataFrame named df?

A. df = pd.csv('student.csv') B. df = pd.read_csv('student.csv') C. df = pd.open('student.csv') D. df = read.pandas('student.csv')

43. Which statement saves df to student.csv without writing the index?

A. df.to_csv('student.csv', index=False) B. df.save_csv('student.csv', index=False) C. df.csv('student.csv', index=False) D. df.write('student.csv', index=False)

44. If df has 4 rows and 3 columns, what is df.shape?

A. (4,3) B. (3,4) C. 4,3 D. [4,3]

45. What is the output type of df.shape?

A. String B. Tuple C. List D. Dictionary

46. Which code gives rows where Marks are equal to 90?

A. df[df['Marks'] = 90] B. df[df['Marks'] == 90] C. df[df['Marks'] := 90] D. df.where('Marks'=90)

47. Which operator means 'not equal to' in Python?

A. <> B. != C. =! D. NOT=

48. Which of the following is a valid DataFrame column assignment?

A. df['Total'] = df['Maths'] + df['IP'] B. df['Total'] == df['Maths'] + df['IP'] C. df.Total <- df.Maths + df.IP D. df.addcolumn Total

49. Which Pandas structure is best suited for tabular data with rows and columns?

A. Series B. DataFrame C. Scalar D. Tuple

50. Which of the following is NOT a Pandas operation?

A. Filtering B. Reading CSV C. Creating DataFrame D. Creating a Python class automatically

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