This post contains very important objective questions for Data handling using python pandas. It covers all concepts of python Dataframe mcq. This post is not only helpful for Informatics Practices student, but for all of them learning Python Programming and Data Science etc.
Pandas is one of the most important and useful open source Python’s library for Data Science. It is basically used for handling complex and large amount of data efficiently and easily. Pandas has derived it’s name from Panel Data System where panel represent a 3D data structure. It was developed by Wes McKinney. Basically it uses Series and Dataframe data structure for data handling.
Dataframe is 2D (Two Dimensional) data structure used to manage large and complex data in tabular format. It contains both rows and columns and hence have both row and column indexes. It is one of the most commonly used data structure similar to spreadsheet.
Contents
Python DataFrame MCQ Set-1 (Q1-Q25)
- Which of the following is not true about dataframe?
a. A dataframe object can be created by passing dictionaries.
b. A dataframe is size immutable.
c. A dataframe index can be string.
d. A column of dataframe can have data of different types.
Show Answer
b. A dataframe is size immutable
- Which of the following statement for creating dataframe is valid?
a. df = pd.dataframe(dict1)
b. df = pd.Dataframe(dict1)
c. df = pd.dataFrame(dict1)
d. df = pd.DataFrame(dict1)
Show Answer
d. df = pd.DataFrame(dict1)
- What will be output of the following code?
School = {‘class1’:{‘Rollno’:1,’Name’:’Amar’}, ‘class2’:{‘Rollno’:2,’Name’:’Sultan’}}
Df = pd.DataFrame(School)
Print(Df)
(a)
Name Rollno
Class1 Amar 1
Class2 Sultan 2
(b)
Rollno Name
Class1 1 Amar
Class2 2 Sultan
(c)
Class1 Class2
Name Amar Sultan
Rollno 1 2
(d)
Class1 Class2
Rollno 1 2
Name Amar Sultan
Show Answer
(d)
Class1 Class2
Rollno 1 2
Name Amar Sultan
- Select the command to display both row and column index label of dataframe ‘exp’.
a. print(exp.index)
b. print(exp.index())
c. print(exp.axes())
d. print(exp.axes)
Show Answer
d. print(exp.axes)
- Rohit has declared a Numpy array:
n = np.array([150,160],[80,90])
He wants to make a dataframe with his own column name and index name. Help him to select correct code.
a. df = pd.DataFrame(n, index = [‘A’,’B’], column = [‘C1’,’C2’])
b. df = pd.DataFrame(index = [‘A’,’B’], column = [‘C1’,’C2’], n)
c. df = pd.DataFrame(n, column = [‘C1’,’C2’] , index = [‘A’,’B’])
d. All are correct
Show Answer
d. All are correct
- Sandesh has written following code to create dataframe with boolean index:
df = pd.DataFrame([1,2,3],index =[true, false, true])
When executing this code, he is getting key error. Suggest him for correction:
a. df = pd.DataFrame([1,2,3],index =[‘true’, ‘false’, ’true’])
b. df = pd.DataFrame([1,2,3],index =[‘True’, ‘False’, ’True’])
c. df = pd.DataFrame([1,2,3],index =[ True, False , True])
d. df = pd.DataFrame([1,2,3],index =[‘0’,’1’,’0’])
Show Answer
c. df = pd.DataFrame([1,2,3],index =[ True, False , True])
- Which of the following is correct statement?
a. inplace argument of rename function is set to False, than original dataframe is changed with new index/columns.
b. del statement of dataframe can be used to delete rows.
c. When a dataframe object is created, all the columns are sorted automatically.
d. While specifying your own index sequence in DataFrame() function, Python doesn’t care about length of index.
Show Answer
c. When a dataframe object is created, all the columns are sorted automatically.
- When a dataframe is created using 2D dictionary, column labels are formed by:
a. Key of outer dictionary
b. Key of inner dictionary
c. Value of outer dictionary
d. Value of inner dictionary
Show Answer
a. Key of outer dictionary
- (i) When dataframe is created with list of dictionaries, the columns are created from dictionary names.
(ii) When dataframe is created with 2D list, column and index are labeled to 0, 1, 2… By default
a. (i) False (ii) True
b. (i) True (ii) False
c. Both are true
d. Both are False
Show Answer
c. Both are true
- To access value of dataframe using column label we can use:
a. loc
b. <dataframe object>.<column label>
c. Both
d. None
Show Answer
c. Both
- What will be output of following code:
import pandas as pd
L = [so, no, go, do, to])
df = pd.DataFrame(L)
print(df[-2:]
(a) 2 go (b) 3 do (c) 4 to (d) 0 so
1 no 4 to 3 do 1 no
0 so 2 go
Show Answer
(b) 3 do
4 to
- To access individual item from a dataframe ‘df’ which of the following is not correct:
a. df.at[row_index, column_index]
b. df.iat[row_index, column_index]
c. df.<column label>[row_index]
d. df.iloc[row_index, column_index]
Show Answer
a. df.at[row_index, column_index]
- Which of the following is not an attribute of dataframe:
a. axes
b. empty
c. transpose
d. Size
Show Answer
c. transpose
- To count total no of elements in a dataframe we use
a. size
b. len
c. count
d. values
Show Answer
a. size
- Identify the correct statement:
a. A dataframe can only store homogeneous elements
b. empty of dataframe counts NaN or NA values
c. The index of dataframe can be number, letter or string.
d. Size of dataframe returns total no of rows.
Show Answer
c. The index of dataframe can be number, letter or string
- To extract the first three rows and three columns of a dataframe ‘exp’ which of the following is True:
a. exp.iloc[0:2,0:2]
b. exp.iloc[0:3,0:3]
c. exp.iloc[1:3,1:3]
d. exp.iloc[1:4,1:4]
Show Answer
b. exp.iloc[0:3,0:3]
17. Considering following dataframe ‘class’
boys girls subject awards
class1 24 16 5 8
class2 20 20 5 10
class3 18 33 6 13
class4 21 19 6 9
Which of the following is not correct?
a. print(class.loc[:,’girls’:’subject’])
b. print(class.loc[‘class1’:’class2’,’girls’:’subject’]
c. Print(class.loc[[‘class1’,’class2’],[‘girls’,’subject’]]
d. Print(class.loc[‘class’,’girls’]
Show Answer
d. Print(class.loc[‘class’,’girls’]
- A dataframe object can be created using:
a. Python Dictionary
b. Python List
c. Panda Series
d. All
Show Answer
d. All
- What will be output of
print(df.loc[:])
a. Display ‘Error’
b Display all rows
c. Display all columns
d. Display all rows and columns
Show Answer
d. Display all rows and columns
- Which of the following can be used to add a new column in existing dataframe:
a. loc
b. <dataframe_object>.<column_lable>
c. at
d. iloc
Show Answer
b. dataframe_object.column_lable
- A dataframe has two axes, where axes = 0 represents
a. Row
b. Column
c. Index
d. Values
Show Answer
a. Row
- Sameer wants to access ‘Author’ column from ‘Book’ dataframe. Suggest him to correct statement:
a. print(Book.Author)
b. print(Book[‘Author’])
c. Both are true
d. (a) True (b) False
Show Answer
c. Both are true
- Consider the dataframe ‘emp’ given below. What will be output of following code you execute?
emp[‘sal’] = 2000
print(emp)
ename dept e1 a.k. om e2 m.s. ee (a) ename dept sal e1 a.k. om 2000 e2 m.s. ee NaN (b) ename dept sal e1 a.k. om 2000 e2 m.s. ee 2000 (c) ename dept e2 m.s. ee sal 2000 2000 (d) Error
Show Answer
(b) ename dept sal e1 a.k. om 2000 e2 m.s. ee 2000
- To count total no of rows of dataframe ‘df’ which of the following command can be written:
a. len(df)
b. df.len
c. df.len()
d. All are correct
Show Answer
a. len(df)
- What the following statement will display?
df.iloc[2 : 7, : 3]
a. Display 2nd to 7th row and first three columns.
b. Display 3rd to 7th row and first three columns.
c. Display 2nd to 7th row and first four columns.
d. Display 3rd to 7th row and first four columns.
Show Answer
b. Display 3rd to 7th row and first three columns.