7. Consider tow objects x and y. x is a list whereas y is a Series. Both have values 20, 40, 90, 110.
What will be the output of following two statements considering that the above objects have been created already ?
(i) print ( x * 2) (ii) print (y * 2)
Justify your answer. [CBSE Sample Paper 20-21]
Ans : Output
(i) print( x * 2)
[20, 40, 90, 110, 20, 40, 90, 110]
(ii) print( y * 2)
| 0 | 40 |
| 1 | 80 |
| 2 | 180 |
| 3 | 220 |
Reason:
- List does not support vectorized operation, while Series support vectorized operation.
- * is work as replication operator with the List while * is work as multiplication operator with Series.
8. Given a dataframe df as shown below
| A | B | D | |
| 0 | 15 | 17 | 19 |
| 1 | 16 | 18 | 20 |
| 2 | 20 | 21 | 22 |
What will be the Result of following code statements?
(a) df [‘C’] = np.NaN (b) df [‘C’] = [2, 5]
(c) df[‘C’]= [12, 15, 27]
Ans: Creating a DataFrame:
df = pd.DataFrame({‘A’: [15,16,20], ‘B’:[17,18,21], ‘D’:[19,20,22]})
(a) df[‘C’] = np.NaN # It will add one column ‘C’ with NaN value
df
A B D C
0 15 17 19 NaN
1 16 18 20 NaN
2 20 21 22 NaN
(b) df[‘C’]=[2,5]
Its raise a ValueError “Length of values does not match length of index”
(c) df[‘C’]= [12,15,27]
df
A B D C
0 15 17 19 12
1 16 18 20 15
2 20 21 22 27
It will update the value of column ‘C’.
9. Write code statements to list the following, from a dataframe namely sales.
(a) List only columns ‘Item’ and ‘Revenue’.
(b) List rows from 3 to 7.
(c) List the value of cell in 5th row, ‘Item’ column.
Ans:
(a) Sales[[‘Item’, ‘Revenue’]]
(b) Sales.iloc[2:7]
# 3rd Row means 2nd Index and 7th Row means 6th Index position
(c) Sales.Item[5]
or
Sales.at[4, ‘Item’]
# 5th row means 4th index position
10. Hitesh wants to display the last four rows of the dataframe df and has written the following code:
df.tail( )
But last 5 rows are being displayed. Identify the error and rewrite the correct code so that last 4 rows get displayed. [CBSE Sample Paper 2019-20]
Ans: tail( ) function by default returns the last / bottom five rows, if you have not given any integer argument.
Use df.tail(4) , to display the last four rows of the dataframe.
