CBSE Class 12 Informatics Practices Data Handling using Pandas Assignment Set 01

QUESTION AND ANSWER SECTION

Question. Differentiate between Pandas Series and NumPy Arrays
Answer: Differences are 
Pandas Series                                            NumPy Arrays
In series we can define our own labeled       In NumPy Arrays we can not define
index to access elements of an array.           our own labelled index to access
                                                                 elements of an array
Series require more memory                       NumPy occupies lesser memory.
The elements can be indexed in                  The indexing starts with zero for the
descending order also.                               firstelement and the index is fixed

Question. What do you mean by Pandas in Python?
Answer: PANDAS (PANel DAta) is a high-level data manipulation tool used for analyzing data. Pandas library has a very rich set of functions.
1. Series
2. DataFrame
3. Panel

Question. Name three data structures available in Pandas.
Answer: Three data structures available in Pandas are :
1. Series
2. DataFrame
3. Panel

Question. Write the code in python to create an empty Series.
Answer:
import pandas as pd
S1 = pd.Series( )
print(S1)
OR
import pandas as pd
S1 = pd.Series( None)
print(S1)
OUTPUT : Series([ ], dtype: float64)

Question. Define data structure in Python.
Answer: A data structure is a collection of data values and operations that can be applied to that data.

Question. What do you mean by Series in Python?
Answer: A Series is a one-dimensional array containing a sequence of values of any data type (int, float, list, string, etc) which by default have numeric data labels (called index) starting from zero. Example of a series containing names of students is given below:
Index Value
0 Arnab
1 Samridhi
2 Ramit
3 Divyam
4 Kritika

Question. Write command to install pandas in python.
Answer: pip install pandas

Question. 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)
Answer:
My        100
name    110
is          120
Amit      130
Gandhi   140
dtype: int64

Question. Write the output of the following :
import pandas as pd
L1=[1,"A",21]
S1 = pd.Series(data=2*L1)
print(S1)
Answer:
0  1
1  A
2  21
3  1
4  A
5  21
dtype: object

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

Question. Write a program to modify the value 5000 to 7000 in the following Series “S1”
A 25000
B 12000
C 8000
D 5000
Answer:
import pandas as pd
S1[3]=7000
print(S1)

MCQ QUESTIONS

Question. Which attribute of a dataframe is used to get number of axis?
a. T
b. Ndim
c. Empty
d. Shape
Answer: B

Question. Display first row of dataframe ‘DF’
a. print(DF.head(1))
b. print(DF[0 : 1])
c. print(DF.iloc[0 : 1])
d. All of the above
Answer: D

Question. To delete a column from a DataFrame, you may use statement.
a. remove
b. del
c. drop
d. cancel statement.
Answer: B

Question. In given code dataframe ‘Df1’ has ________ rows and _______ columns import pandas as pd
dict= [{‘a’:10, ‘b’:20}, {‘a’:5, ‘b’:10, ‘c’:20},{‘a’:7, ‘d’:10, ‘e’:20}]
Df1 = pd.DataFrame(dict)
a. 3, 3
b. 3, 4
c. 3, 5
d. None of the above
Answer: C

Question. To delete a row from a DataFrame, you may use
a. remove
b. del
c. drop
d. cancel
Answer: C

Question. In the following statement, if column ‘mark’ already exists in the DataFrame ‘Df1’ then the assignment statement will __________ Df1['mark'] = [95,98,100] #There are only three rows in DataFrame Df1
a. Return error
b. Replace the already existing values.
c.Add new column
d. None of the above
Answer: B

30 To skip first 5 rows of CSV file, which argument will you give in read_csv( ) ?
a. skip_rows = 5
b. skiprows = 5
c. skip - 5
d. noread - 5
Answer: A

Question. Which of the following statement is false:
a. DataFrame is size mutable
b. DataFrame is value mutable
c. DataFrame is immutable
d. DataFrame is capable of holding multiple types of data
Answer: C

Question. Which of the following statements is false?
a. Dataframe is size mutable
b. Dataframe is value mutable
c. Dataframe is immutable
d. Dataframe is capable of holding multiple type of data
Answer: C

Question. To delete a row, the parameter axis of function drop( ) is assigned the value______________
a. 0
b. 1
c. 2
d. 3
Answer: A

Question. Which of the following function is used to load the data from the CSV file to DataFrame?
a. read.csv( )
b. readcsv( )
c.read_csv( )
d.Read_csv( )
Answer: C

Question. Write code to delete rows those getting 5000 salary.
a. df=df.drop[salary==5000]
b. df=df[df.salary!=5000]
c. df.drop[df.salary==5000,axis=0]
d. df=df.drop[salary!=5000]
Answer: B

Question. DF1.loc[ ] method is used to ______ # DF1 is a DataFrame
a. Add new row in a DataFrame ‘DF1’
b. To change the data values of a row to a particular value
c.Both of the above
d.None of the above
Answer: C

Question. To iterate over horizontal subsets of dataframe,
a. iterate( )
b. iterrows( ) function may be used.
c. itercols( )
d. iteritems( )
Answer: B

Question. Write code to delete the row whose index value is A1 from dataframe df.
a. df=df.drop(‘A1’)
b. df=df.drop(index=‘A1’)
c. df=df.drop(‘A1,axis=index’)
d. df=df.del(‘A1’)
Answer: A

Question. A two-dimension labeled array that is an ordered collection of columns to store heterogeneous data type is
a. Series
b. Numpy array
c. Dataframe
d. Panel
Answer: C

Question. To skip 1st, 3rd and 5th rows of CSV file, which argument will you give in read_csv( ) ?
a. skiprows = 11315
b. skiprows - (1, 3, 5]
c. skiprows = [1, 5, 1]
d. Any of these
Answer: B

Question. In Pandas _______________ is used to store data in multiple columns.
a. Series
b. DataFrame
c. Both of the above
d. None of the above
Answer: B

Question. What is dataframe?
a. 2 D array with heterogeneous data
b. 1 D array with homogeneous data
c. 2 D array with homogeneous data
d. 1 D array with heterogeneous data
Answer: A

Question. In a DataFrame, Axis= 1 represents the_____________ elements
a. Row
b. Column
c. True
d. False
Answer: B

Question. Which of the following is not an attribute of a DataFrame Object ?
a. index
b. Index
c. size
d. value
Answer: B

Question. To skip 1st, 3rd and 5th rows of CSV file, which argument will you give in read_csv( ) ?
a. skiprows = 11315
b. skiprows - (1, 3, 5]
c. skiprows = [1, 5, 1]
d. Any of these
Answer: B

Question. In a DataFrame, Axis= 1 represents the_____________ elements
a. Row
b. Column
c. True
d. False
Answer: B

Question. NaN stands for:
a. Not a Number
b. None and None
c. Null and Null
d. None a Number
Answer: A

Importing/Exporting Data between CSV files and Data Frames Basics of CSV Files

Question. Fill the missing statement
import matplotlib.pyplot as plt
marks=[30,10,55,70,50,25,75,49,28,81]
plt._____(marks, bins=’auto’, color=’green’)
plt.show()
a. plot
b. bar
c. hist
d. draw
Answer: C

Question. Which module of matplotlib library is required for plotting of graph ?
a. Plot
b. Matplot
c. pyplot
d. graphics
Answer: C

Question. Identify the right type of chart using the following hints.
Hint 1: This chart is often used to visualize a trend in data over intervals of time.
Hint 2: The line in this type of chart is often drawn chronologically.
a. Line chart
b. Bar chart
c. Pie chart
d. Scatter plot
Answer: A

Question. The following code create a dataframe named ‘Df1’ with _______________ columns. import pandas as pd
Df1 = pd.DataFrame([10,20,30] )
a. 1
b. 2
c. 3
d. 4
Answer: A

Question. To delete a row from dataframe, you may use _______ statement.
a. remove()
b. del()
c. drop()
d. cancel()
Answer: B

Question. In a Data-Frame, Axis= 0 represents the elements along the______
a. Row
b. Column
c. Row and Column Both
d. None of the above
Answer: A

Question. ___________ method in Pandas can be used to change the index of rows and columns of a Series or Dataframe
a. rename()
b. reindex()
c. reframe()
d. none of these
Answer: B

Question. Write the single line command to delete the column “marks” from dataframe df using drop function.
a. df=df.drop(col=‘marks’)
b. df=df.drop(‘marks’,axis=col)
c. df=df.drop(‘marks’,axis=0)
d. df=df.drop(‘marks’,axis=1)
Answer: D

Question. Which of the following is used to give user defined column index in DataFrame?
a. index
b. column
c. columns
d. colindex
Answer: C

Question. The following statement will _________
df = df.drop(['Name', 'Class', 'Rollno'], axis = 1) #df is a DataFrame object
a. delete three columns having labels ‘Name’, ‘Class’ and ‘Rollno’
b. delete three rows having labels ‘Name’, ‘Class’ and ‘Rollno’
c. delete any three columns
d. return error
Answer: A

Question. Difference between loc() and iloc().:
a. Both are Label indexed based functions.
b. Both are Integer position-based functions.
c. loc() is label based function and iloc() integer position based function.
d. loc() is integer position based function and iloc() index position based function.
Answer: C

Question. Which command will be used to delete 3 and 5 rows of the data frame. Assuming the data frame name as DF.
a. DF.drop([2,4],axis=0)
b. DF.drop([2,4],axis=1)
c. DF.drop([3,5],axis=1)
d. DF.drop([3,5])
Answer: A

Question. What is data visualization?
a. It is the numerical representation of information and data
b. It is the graphical representation of information and data
c. It is the character representation of information and data
d. None of the above
Answer: B

Question. Which is a python package used for 2D graphics?
a. matplotlib.pyplot
b. matplotlib.pip
c. matplotlib.numpy
d. mathplotlib.pyplot
Answer: A

Question. The command used to give a heading to a graph is _________
a. plt.show()
b. plt.plot()
c. plt.xlabel()
d. plt.title()
Answer: D

Question. Using Python Matplotlib _________ can be used to count how many values fall into each interval.
a. line plot
b. bar graph
c. histogram(d. None of these
Answer: C

Question. Which of the following is/are correct statement for plot method?
a. plt.plot(x,y,color,others)
b. pl.plot(x,y)
c. pl.plot(x,y,color)
d. All the above
Answer: D 

Question. Which function can be used to export generated graph in matplotlib to png
a. savefigure ( )
b. savefig( )
c. save( )
d. export ( )
Answer: B