70+ Important Questions Pandas Series Class 12 IP with Answers

Pandas Series Class 12 IP Important Questions

Q1. What do you mean by Pandas in Python?

Q2. Name three data structures available in Pandas.

Q3. Write command to install pandas in python.

Q4. What do you mean by Series in Python?

Q5. Define data structure in Python.

Q6. Write the code in python to create an empty Series.

Show Answer
Ans. 

import pandas as pd
S1 = pd.Series( )
print(S1)

OR

import pandas as pd
S1 = pd.Series( None)
print(S1)

OUTPUT : Series([ ], dtype: float64)

Q7. Name a method which is used to create Series in Python.

Q8. Write a program in Python to create a series of first five even numbers.

Show Answer
Ans. 

import pandas as pd
S1 = pd.Series([2, 4, 6, 8, 10])
print(S1)

OUTPUT : 

0     2
1     4
2     6
3     8
4    10
dtype: int64

Q9. Write a program in Python to create series of vowels.

Show Answer
Ans. 

import pandas as pd
S1 = pd.Series(["a","e","i","o","u"])
print(S1)


OUTPUT : 

0    a
1    e
2    i
3    o
4    u
dtype: object

Q10. Write a program in python to create series of given tuple : A = (11, 22, 33, 44, 55)

Show Answer
Ans. 

import pandas as pd
A = (11, 22, 33, 44, 55)
S1 = pd.Series(A)
print(S1)

OUTPUT : 

0    11
1    22
2    33
3    44
4    55
dtype: int64

Q11. Write a program in Python to create the pandas series of all the characters in the name accepted from user.

Show Answer
Ans. 

import pandas as pd
A = input("Enter your name  : ")
S1 = pd.Series(list(A))
print(S1)

OUTPUT :

Enter your name  : amit
0    a
1    m
2    i
3    t
dtype: object

Q12. Write a program in Python to create a Series in Python from the given dictionary. D = {“Jan” : 31, “Feb” : 28, “Mar” : 31}

Show Answer
Ans. 

import pandas as pd
D = {"Jan" : 31, "Feb" : 28, "Mar" : 31}
S1 = pd.Series(D)
print(S1)

OUTPUT :

Jan    31
Feb    28
Mar    31
dtype: int64

Q13. Write a program to create a series from dictionary that stores classes (6,7,8,9,10) as keys and number of students as values.

Show Answer
Ans. 

import pandas as pd
D = {6 : 140, 7 : 125, 8 : 100, 9 : 136, 10 : 200}
S1 = pd.Series(D)
print(S1)

OUTPUT : 

6     140
7     125
8     100
9     136
10    200
dtype: int64

Q14. Write the output of the following :

import pandas as pd
S1 = pd.Series(12, index = [4, 6, 8])
print(S1)

Show Answer
Ans. Output is :

4    12
6    12
8    12
dtype: int64

Q15. Write the output of the following :

import pandas as pd
S1 = pd.Series(range(1,15,3), index=[x for x in "super"])
print(S1)

Show Answer
Ans. 

s     1
u     4
p     7
e    10
r    13
dtype: int64

Pandas Series Class 12 IP Important Questions

Q16. Write the output of the following :

import pandas as pd
S1 = pd.Series(range(100, 150, 10), index=[x for x in "My name is Amit Gandhi".split()])
print(S1)

Show Answer
Ans. 

My          100
name      110
is             120
Amit        130
Gandhi    140
dtype: int64

Q17. Write the output of the following :

import pandas as pd
L1=[1,"A",21]
S1 = pd.Series(data=2*L1)
print(S1)

Show Answer
Ans. 

0     1
1     A
2    21
3     1
4     A
5    21
dtype: object

Q18. Name any two attributes of Series in Python.

Q19. Which property of series return all the index value?

Q20. Write the output of the following :

import numpy as num
import pandas as pd
arr=num.array([1,7,21])
S1 = pd.Series(arr)
print(S1)

Show Answer
Ans. 

0     1
1     7
2    21
dtype: int32

Pandas Series Class 12 IP Important Questions

Q21. Write the output of the following :

import numpy as num
import pandas as pd
arr=num.array([1,7,21])
S1 = pd.Series(arr, index = (77,777))
print(S1)

Q22. Write the output of the following :

import numpy as num
import pandas as pd
arr=num.array([31,47,121])
S1 = pd.Series(arr, index = (7,77,777))
print(S1[777])

Q23. Write the output of the following :

import numpy as num
import pandas as pd
arr=num.array([31,47,121])
S1 = pd.Series(arr)
print(S1[0])

Q24. Write the output of the following :

import pandas as pd
L1 = list("My name is Ravi Kumar")
S1 = pd.Series(L1)
print(S1[0])

Q25. Write the output of the following :

import pandas as pd
L1 = list("My name is Ravi Kumar".split( ))
S1 = pd.Series(L1)
print(S1[0])

Pandas Series Class 12 IP Important Questions

Q26. Which property of series returns the number of elements in the series?

Q27. Give an example of creating series from NumPy array.

Show Answer
Ans. 

import pandas as pd
import numpy as np
arr = np.array([1,2,3,4,5])
S1 = pd.Series(arr)
print(S1)

Q28. Which property of Series help to check whether a Series is empty or not? Explain with example

Show Answer
Ans. empty property : This property returns True if the Series is empty otherwise return False.

import pandas as pd
S1 = pd.Series()
print(S1.empty)

OUTPUT : 
True

Q29. Fill in the blanks in the given code :

import pandas as pd
____________ = ____________.Series([1, 2, 3, 4, 5])
print(S1)

Show Answer
Ans. 

import pandas as pd
S1 = pd.Series([1, 2, 3, 4, 5])
print(S1)

Q30. Fill in the blank of given code, if the output is 71.

import pandas as pd
S1 = pd.Series([10, 20, 30, 40, 71,50])
print(S1[ __________ ])

Show Answer
Ans.

import pandas as pd
S1 = pd.Series([10, 20, 30, 40, 71,50])
print(S1[ 4 ])

Pandas Series Class 12 IP Important Questions

Q31. Complete the code to get the required output :

import ______ as pd
________ = pd.Series([31, 28, 31], index = ["Jan", "Feb", "Mar"] )
print(S1["_______"])

OUTPUT :

28

Show Answer
Ans. 

import pandas as pd
S1 = pd.Series([31,28,31], index = ["Jan","Feb","Mar"])
print(S1["Feb"])

Q32. Write the output of the following code :

import pandas as pd
S1 = pd.Series([31, 28, 31, 30, 31], index = ["Jan", "Feb", "Mar", "Apr", "May"])
print("-----------")
print(S1[1:3])
print("-----------")
print(S1[:5])
print("-----------")
print(S1[3:3])
print("-----------")
print(S1["Jan":"May"])

Show Answer
Ans. 

-----------
Feb    28
Mar    31
dtype: int64
-----------
Jan    31
Feb    28
Mar    31
Apr    30
May    31
dtype: int64
-----------
Series([ ], dtype: int64)
-----------
Jan    31
Feb    28
Mar    31
Apr    30
May    31
dtype: int64

Q33. Write the output of the following code :

import pandas as pd
S1 = pd.Series([31, 28, 31, 30, 31], index = ["Jan", "Feb", "Mar", "Apr", "May"])
print(S1["Jun"])

Q34. Write the output of the following code :

import pandas as pd
S1 = pd.Series([31, 28, 31, 30, 31], index = ["Jan", "Feb", "May", "Apr", "May"])
print(S1["May"])

Show Answer
Ans. 

May    31
May    31
dtype: int64

Q35. Write the output of the following :

import pandas as pd
S1 = pd.Series([31, 28, 31, 30, 31], index = ["Jan", "Feb", "Mar", "Apr", "May"])
print(S1[ [0, 2, 4] ])

Show Answer
Ans. 

Jan    31
Mar    31
May    31
dtype: int64

Q36. Write the output of the following :

import pandas as pd
S1 = pd.Series([31, 28, 31, 30, 31], index = ["Jan", "Feb", "Mar", "Apr", "May"])
print(S1[0 : 2] * 2)

Show Answer
Ans. 

Jan    62
Feb    56
dtype: int64

Q37. Write a program to modify the value 5000 to 7000 in the following Series “S1”

A     25000
B     12000
C     8000
D     5000

Show Answer
Ans.

import pandas as pd
S1[3]=7000
print(S1)

Q38. Explain any two properties/attributes of Pandas Series.

Q39. Explain any three methods of Pandas Series.

Q40. Write the output of the following code :

import pandas as pd
S1 = pd.Series([2, 5, 7, 10])
print(S1 + 2)
print(S1 * 2)
print(S1 ** 2)
print(S1 - 2)
print(S1 > 2)

Show Answer
Ans. 


0     4
1     7
2     9
3    12
dtype: int64
0     4
1    10
2    14
3    20
dtype: int64
0      4
1     25
2     49
3    100
dtype: int64
0    0
1    3
2    5
3    8
dtype: int64
0    False
1     True
2     True
3     True
dtype: bool

Q41. Write the output of the following code :

import pandas as pd
S1 = pd.Series([2, 5, 7, 10])
S2 = pd.Series([1, 3, 5, 7])
print(S1 + S2)

Show Answer
Ans. 

0     3
1     8
2    12
3    17
dtype: int64

Q42. Write a program to display only those values greater than 200 in the given Series “S1”

0     300
1     100
2    1200
3    1700

Show Answer
Ans. 

import pandas as pd
S1 = pd.Series([300, 100, 1200, 1700])
print(S1[S1>200])

Q43. Write a program to display the following Series “S1” in descending order.

0     300
1     100
2    1200
3    1700

Show Answer
Ans. 

import pandas as pd
S1 = pd.Series([300, 100, 1200, 1700])
print(S1.sort_values(ascending=False)) #if given True then Series will arrange in ascending order

OUTPUT :

3    1700
2    1200
0     300
1     100
dtype: int64

Q44. Write the output of the following :

import pandas as pd
S1 = pd.Series([3, 1, 12, 17], index = ("a","b","c","d"))
S2 = pd.Series([4, 5, 6, 7], index = ("a","b","e","f"))
print(S1*S2)

Show Answer
Ans. 

a      12.0
b      5.0
c      NaN
d     NaN
e     NaN
f     NaN
dtype: float64

Q45. Write the output of the following :

import pandas as pd
S1 = pd.Series([3, 1, 12, 17], index = ("a", "b", "c", "d"))
S2 = pd.Series([4, 5, 6, 7], index = ("a", "b", "e", "f"))
print(S1.mul(S2, fill_value = 0))

Show Answer
Ans. 

a    12.0
b     5.0
c     0.0
d     0.0
e     0.0
f     0.0
dtype: float64

Q46. Name the methods used for multiplication and division of two Series in Python.

Q47. Differentiate between Pandas Series and NumPy Arrays.

Q48. A Series object can have duplicate index.(T/F)

Q49. A Series object always have indexes 0 to n-1. (T/F)

Q50. ________________ is a Pandas data structure that represent one dimensional array containing a sequence of values of any data type

Q51. Write a program to change the index of the following Series “S1” from (0, 1, 2, 3) to (a, b, c,d).

0    120
1     75
2     85
3     95

Show Answer
Ans.

import pandas as pd
S1 = pd.Series([120, 75, 85 ,95])
print("Initial Index Values are : ")
print(S1)
print("Final Index Values are : ")
S1.index=("a","b","c","d")
print(S1)

OUTPUT :

Initial Index Values are : 
0    120
1     75
2     85
3     95
dtype: int64
Final Index Values are : 
a    120
b     75
c     85
d     95
dtype: int64

Q52. Write the output of the following :

import pandas as pd
L1=[1, 2, 3, 4]
S1 = pd.Series(L1 * 2) 
S2 = pd.Series(S1 * 2)
print(S1)
print(S2)

Show Answer
Ans.

0    1
1    2
2    3
3    4
4    1
5    2
6    3
7    4
dtype: int64

0    2
1    4
2    6
3    8
4    2
5    4
6    6
7    8
dtype: int64

Q53. Consider the following Series object “S1” and write the output of the following statement :

0    21
1    41
2    62
3    81
4    23
5    45
6    68
7    89


 import pandas as pd
 L1=[21, 41, 62, 81, 23, 45, 68, 89]
 S1 = pd.Series(L1)
 print("1. ",S1.index)

 print("2. ",S1.values)

 print("3. ",S1.shape)

 print("4. ",S1.ndim)

 print("5. ",S1.size)

 print("6. ",S1.nbytes)

 print("7. ",S1[0])

 print("8. ",S1[2]+S1[0])

 print("9. ",S1[5]**2)

 print("10. ",S1.empty)

 print("11.\n",S1[[1, 5, 6]])

 print("12.\n",S1[5 : 7],"\n")

 print("13.\n",S1[: : -1])

 print("14.\n",S1>60)

 print("15.\n",S1[S1>60])

 print("16.\n",len(S1))

 print("17.\n",S1.count())

 print("18.\n",S1.head())

 print("19.\n",S1.tail())

 print("20.\n",S1[4:5] + S1[4:5])

Show Answer
Ans. 

 1.  RangeIndex(start=0, stop=8, step=1)
 2.  [21 41 62 81 23 45 68 89]
 3.  (8,)
 4.  1
 5.  8
 6.  64
 7.  21
 8.  83
 9.  2025
 10. False

 11.
 1    41
 5    45
 6    68
 dtype: int64

 12.
 5    45
 6    68
 dtype: int64  

 13.
 7    89
 6    68
 5    45
 4    23
 3    81
 2    62
 1    41
 0    21
 dtype: int64

 14.
 0     False
 1     False
 2     True
 3     True
 4     False
 5     False
 6     True
 7     True
 dtype: bool

15.
 2    62
 3    81
 6    68
 7    89
 dtype: int64

 16.   
8

 17.   
8

 18.
 0    21
 1    41
 2    62
 3    81
 4    23
 dtype: int64

 19.
 3    81
 4    23
 5    45
 6    68
 7    89
 dtype: int64

 20.
 4    46
 dtype: int64

Q54. Consider the following Series object “S1” and “S2” and write the output of the following code :

S1	S2
0 2 1 4 2 6 3 8 4 10	0 1 1 2 2 3 3 4 4 5

import pandas as pd
S1=pd.Series([2, 4, 6, 8, 10])
S2=pd.Series([1, 2, 3, 4, 5])
print(S1+S2)
print(S1-S2)
print(S1*S2) 
print(S1/S2) 
print(S1.mul(2)) 
print(S1*3)
print(S1+3)
print(S1-3)
print(S1.div(S2))

Show Answer
Ans. 

 0     3
 1     6
 2     9
 3    12
 4    15
 dtype: int64

 0    1
 1    2
 2    3
 3    4
 4    5
 dtype: int64

 0     2
 1     8
 2    18
 3    32
 4    50
 dtype: int64

 0    2.0
 1    2.0
 2    2.0
 3    2.0
 4    2.0
 dtype: float64

 0     4
 1     8
 2    12
 3    16
 4    20
 dtype: int64

 0     6
 1    12
 2    18
 3    24
 4    30
 dtype: int64

 0     5
 1     7
 2     9
 3    11
 4    13
 dtype: int64

 0   -1
 1    1
 2    3
 3    5
 4    7
 dtype: int64

 0    2.0
 1    2.0
 2    2.0
 3    2.0
 4    2.0
 dtype: float64
                        

Q55. Write a program to perform basic mathematical operation on two series.

Show Answer
Ans. 

import pandas as pd
S1=pd.Series([2, 4, 6, 8, 10])
S2=pd.Series([1, 2, 3, 4, 5])
print(S1+S2) #Addition
print(S1-S2) #Subtraction
print(S1*S2) #Multiplication
print(S1/S2) #Division

Q56. Write a program to create series from the given dictionary. D={ “A” : “Apple”, “B” : “Boy”, “C” : “Cat”}

Show Answer
Ans. 

import pandas as pd
D={ "A" : "Apple", "B" : "Boy", "C" : "Cat"}
S1 = pd.Series(D)
print(S1)


OUTPUT :

A    Apple
B      Boy
C      Cat
dtype: object

Q57. Write a program to create Pandas Series from the given NumPy array. A=[1,2,3,4,5,6,7]

Show Answer
Ans. 

import pandas as pd
import numpy as np
A = np.array([1,2,3,4,5,6,7])
S1 = pd.Series(A)
print(S1)

OUTPUT :

0    1
1    2
2    3
3    4
4    5
5    6
6    7
dtype: int32

Q58. Write a program to display only first n rows from the given Pandas Series ‘S1’. Accept n from the user.

0    1
1    2
2    3
3    4
4    5
5    6
6    7

Show Answer
Ans.

import pandas as pd
nt = int(input("Enter number of terms to display"))
S1 = pd.Series([1, 2, 3, 4, 5, 6, 7])
print(S1.head(nt))

OUTPUT : 

Enter number of terms to display : 4
0    1
1    2
2    3
3    4
dtype: int64

Q59. Write a program to display values greater than 250 from the given Pandas Series “S1”

0    150
1    252
2    35
3    420
4    50
5    61
6    275

Show Answer
Ans. 

import pandas as pd
S1 = pd.Series([150, 252, 35, 420, 61, 275])
print(S1[S1>250])

OUTPUT : 

1    252
3    420
5    275
dtype: int64

Q60. Write a program to count the number of values less than 200 from the given Pandas Series.

0    150
1    252
2    35
3    420
4    50
5    61
6    275

Show Answer
Ans. 

import pandas as pd
S1 = pd.Series([150, 252, 35, 420, 61, 275])
print(S1[S1<200].count( ))

OUTPUT :

3

Q61. Write a program to increase those value in the given Pandas Series by 50 which are less than 70.

0    150
1    252
2    35
3    420
4    50
5    61
6    275

Show Answer
Ans. 

import pandas as pd
S1 = pd.Series([150, 252, 35, 420, 61, 275])
S1[S1<70] = S1[S1<70] + 50
print(S1)

OUTPUT :

0    150
1    252
2     85
3    420
4    111
5    275
dtype: int64

Q62. Write a program to create a Series whose values are characters of the name accepted from the user. for example :

Enter Your Name  : Suman
Series is :
0     S
1     u
2     m
3     a
4     n

Show Answer
Ans.

import pandas as pd
nm = input("Enter your name : ")
S1 = pd.Series(list(nm))
print(S1)

OUTPUT :

Enter your name : amit
0    a
1    m
2    i
3    t
dtype: object

Q63. Write a program to arrange the given Pandas Series in increasing order.

0    150
1    252
2     85
3    420
4    111
5    275

Show Answer
Ans. 

import pandas as pd
S1 = pd.Series([150,252,85,420,111,235])
print("Original Series is : ")
print(S1)
print("New Series is : ")
print(S1.sort_values())

OUTPUT : 

 Original Series is : 
 0    150
 1    252
 2     85
 3    420
 4    111
 5    235
 dtype: int64

 New Series is : 
 2     85
 4    111
 0    150
 5    235
 1    252
 3    420
 dtype: int64

Q64. Write a program to add a new value (Accept that value from the user) in the given Pandas Series.

0    150
1    252
2     85
3    420
4    111
5    275

Show Answer
Ans. 

import pandas as pd
S1 = pd.Series([150, 252, 85, 420, 111, 235])
v = int(input("Enter any value : "))
print("Original Series is : ")
print(S1)
S1[6]=v
print("New Series is : ")
print(S1)

OUTPUT : 

 Enter any value : 677
 Original Series is : 
 0    150
 1    252
 2     85
 3    420
 4    111
 5    235
 dtype: int64

 New Series is : 
 0    150
 1    252
 2     85
 3    420
 4    111
 5    235
 6    677
 dtype: int64

Q65. Write a program to display the sum and average of all the values in the given Pandas Series.

0    15
1     2
2    8
3    4
4    1
5    5
6    14

Show Answer
Ans.

import pandas as pd
S1 = pd.Series([15, 2, 8, 4, 1, 5, 14])
print("Sum is : ", sum(S1.values))
print("Average is : ", sum(S1.values)/S1.count( ))

OUTPUT :

Sum is :  49
Average is :  7.0

Q66. Write a program to find the minimum, maximum value of given Pandas Series.

0    15
1     2
2    8
3    4
4    1
5    5
6    14

Show Answer
Ans. 

import pandas as pd
S1 = pd.Series([15,2,8,4,1,5,14])
print("Maximum value is : ",max(S1.values))
print("Minimum value is : ",min(S1.values))

OUTPUT :

Maximum value is :  15
Minimum value is :  1

Q67. Write a program to display multiple of 5 from the given Pandas Series.

0    15
1     2
2    8
3    4
4    1
5    25
6    30

Show Answer
Ans.

import pandas as pd
S1 = pd.Series([15, 2, 8, 4, 1, 25, 30])
print(S1[S1.values%5==0])

OUTPUT :

0    15
5    25
6    30
dtype: int64

Q68. Write a program in python to display all values of given pandas series with first character in upper case. for example

Original Series is  :

0     ravi
1     ram
2     sonu
3     david

Expected Output :

0     Ravi
1      Ram
2     Sonu
3    David
dtype: object

Show Answer
Ans. 

import pandas as pd
S1 = pd.Series(["ravi", "ram", "sonu", "david"])
L = S1.values
L1=[ ]
for i in L:
     L1.append(i[0].upper() + i[1:])
S2 = pd.Series(L1)
print(S2)

Q69. Write a program to display all odd numbers and its sum from the given Pandas Series.

0    15
1     2
2    8
3    4
4    1
5    25
6    30

Show Answer
Ans.

import pandas as pd
S1 = pd.Series([15, 2, 8, 4, 1, 25, 30])
print(S1[S1%2!=0])
S2=S1[S1%2!=0]
print("Sum of all odd numbers is : ", sum(S2.values))

OUTPUT :

0    15
4     1
5    25
dtype: int64

Sum of all odd numbers is :  41

Q70. Write the output of the following :

import pandas as pd
L=[1, 2]
for i in range(25, 95, 10):
L.append(i)
S1 = pd.Series(L)
print(S1)

Show Answer
Ans.

0     1
1     2
2    25
3    35
4    45
5    55
6    65
7    75
8    85
dtype: int64

Q71. Write the output of the following :

import pandas as pd
D = { }
for i in range(25, 95, 10):
D[i]=i+10
S1 = pd.Series(D)
print(S1)

Show Answer
Ans.

25    35
35    45
45    55
55    65
65    75
75    85
85    95
dtype: int64

Q72. Write the output of the following :

import pandas as pd
S1 = pd.Series(range(1, 20, 3))
print(S1)

Show Answer
Ans.

0     1
1     4
2     7
3    10
4    13
5    16
6    19
dtype: int64

Pandas Series Class 12 IP Important Questions

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Important Points to Remember about Pandas Series

NumPy, Pandas and Matplotlib are Python libraries for scientific and analytical use. 

pip install pandas is the command to install Pandas library.

A data structure is a collection of data values and the operations that can be applied to that data. It enables efficient storage, retrieval and  modification to the data. 

Two main data structures in Pandas library are Series and DataFrame. To use these data structures, we first need to import the Pandas library.

A Series is a one-dimensional array containing a sequence of values. Each value has a data label associated with it also called its index. 

The two common ways of accessing the elements of a series are Indexing and Slicing.

There are two types of indexes: positional index and labelled index. Positional index takes an integer value that corresponds to its position in the series starting from 0, whereas labelled index takes any user-defined label as index 

When positional indices are used for slicing, the value at end index position is excluded, i.e., only (end - start) number of data values of the series are extracted. However with labelled indexes the value at the end index label is also included in the output. 

All basic mathematical operations can be performed on Series either by using the operator or by using appropriate methods of the Series object. 

While performing mathematical operations index matching is implemented and if no matching indexes are found during alignment, Pandas returns NaN so that the operation does not fail.