Class 12 Informatics Practices Data Handling using Python Pandas-I MCQs Set 3

Class 12 Informatics Practices


Multiple Choice Questions


Data Handling Using Pandas – I MCQs

Data Handling Using Python Pandas – 1 (Set 3)


Topics Covered : Series [Set – 3]


41. In the given code , a series is created from ______ values.

>>> import numpy as np

>>> import pandas as pd

>>> list1 = np.array([1, 2, 3, 4] )

>>> ser1 = pd.Series(list1)

a. Scalar Value

b. List

c. NumPy Array

d. Dictionary

Answer: c. NumPy Array

42. When index labels are passed with the array, then the length of the index and array must be of the __________.

a. same size

b. same value

c. same type

d. None of these

Answer: a. same size

43. Identify the error generated by following code :-

>>> ser1 = pd.Series ( [1, 2, 3, 4, 5, 6], index = [5.5, 7.6, 9.8, 1.3] )

a. KeyError

b. ValueError

c. TypeError

d. LengthError

Answer: b. ValueError

44. Can you create a Series object using Dictionary ?

a. Yes

b. No

Answer: a. Yes

45. A value from dictionary can be accessed easily by using _______.

a. key

b. index

c. value

d. None of these

Answer: a. key

46. Dictionary _______ can be used to construct an index for a Series.

a. Values

b. Keys

c. Index

d. None of these

Answer: b. Keys

Direction: On the basis of given code, answer the Question Number 47 to 49.

47. What is the index of series S1.

a. [0,1,2,3]

b. [‘a’, ‘b’, ‘c’, ‘d’]

c. [‘India’, ‘Japan’, ‘Bihar’]

d. [‘New Delhi’, ‘Tokyo’, ‘Patna’]

Answer: c. [‘India’, ‘Japan’, ‘Bihar’]

48. What is the output of statement- print(S1[‘India’])

a. New Delhi

b. Japan

c. India

d. Error – KeyError will raise.

Answer: c. [‘India’, ‘Japan’, ‘Bihar’]

49. What is the output of statement- print(S1)

a.

b.

c.

d. None of these

Answer: a.

Direction: On the basis of given code, answer the Question Number 50 to 52.

import pandas as pd
series1 = pandas.Series(range(5)
print(series1)

50. What is the index values of series1.

a. 0, 1, 2, 3, 4

b. 1, 2, 3, 4, 5

c. a, b, c, d, e

d. None of these

Answer: a. 0, 1, 2, 3 , 4

51. What is the values of series1.

a. 0, 1, 2, 3, 4

b. 1, 2, 3, 4, 5

c. a, b, c, d, e

d. None of these

Answer: a. 0, 1, 2, 3 , 4

52. What is the data type of series1.

a. int8

b. int16

c. int32

d. int64

Answer: d. int64

53. >>> import pandas as pd

>>> series1 = pd.Series( range(1,18,3), index = {x for x in ‘python’} )

Write the index value of series1.

a. ‘p’, ‘y’, ‘t’, ‘h’, ‘o’, ‘n’

b. 0, 1, 2, 3, 4, 5

c. 1, 2, 3, 4, 5, 6

d. Error

Answer: a. ‘p’, ‘y’, ‘t’, ‘h’, ‘o’, ‘n’

54. _________ is use to indicate missing or null values in pandas.

a. NULL

b. EMPTY

c. NaN

d. None

Answer: c. NaN

55. NaN is _______ data type value..

a. Integer

b. Float

c. Boolena

d. String

Answer: b. Float

56. NaN is an attribute of _______ library.

a. pandas

b. matplotlib

c. numpy

d. None

Answer: c. numpy

57. Write a statement to create a series with given value [1.5, 5.6, Missing Value, 9.0]. (Assume pandas is imported as pd and numpy is imported as np).

a. series1 = pd.Series( 1.5, 5.6, ‘np.NaN’, 9.0)

b. series = pd.Series([ 1.5, 5.6, ‘np.NaN’, 9.0 ] )

c. series = pd.Series([ 1.5, 5.6, NaN, 9.0 ] )

d. series = pd.Series([ 1.5, 5.6, np.NaN, 9.0 ] )

Answer: d. series = pd.Series([ 1.5, 5.6, np.NaN, 9.0 ] )

58. Identify the error in the given statement: (assume pandas is imported as pd)

>>> series1 = pd.Series( [2, 5, 6, 8], index = [‘a’, ‘v’, ‘d’] )

a. KeyError – Length of values must be equal to length of index

b. ValueError – Length of values must be equal to length of index

c. No Error

d. None of these

Answer: b. ValueError – Length of values must be equal to length of index

59. Identify the error in the given statement: (assume pandas is imported as pd)

>>> series1 = pd.Series( 200, index = [‘a’, ‘v’, ‘d’] )

a. KeyError – Length of values must be equal to length of index

b. ValueError – Length of values must be equal to length of index

c. No Error

d. None of these

Answer: c. No Error

60. What is the output of given code: (assume pandas is imported as pd)

>>> series1 = pd.Series( 200, index = [‘a’, ‘v’, ‘d’] )

>>> print(series1)

a. a    200
   v    200
   d    200
   dtype: int64
b.  a    200
    v    NaN
    d    NaN
    dtype: int64
c. a  200
   dtype: int64

d. None of these

Answer: a.

a   200
v   200
d   200
dtype: int64


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