Informatics Practices
Consider the following DataFrame df and answer any four questions from (i)-(v):
| rollno | name | UT1 | UT2 | UT3 | UT4 |
|---|---|---|---|---|---|
| 1 | Prerna Singh | 24 | 24 | 20 | 22 |
| 2 | Manish Arora | 18 | 17 | 19 | 22 |
| 3 | Tanish Goel | 20 | 22 | 18 | 24 |
| 4 | Falguni Jain | 22 | 20 | 24 | 20 |
| 5 | Kanika Bhatnagar | 15 | 20 | 18 | 22 |
| 6 | Ramandeep Kaur | 20 | 15 | 22 | 24 |
Which of the following statement/s will give the exact number of values in each column of the dataframe ?
(I) print(df.count())
(II) print(df.count(0))
(III) print(df.count)
(IV) print((df.count(axis = 'index')))
Choose the correct option :
(a) both (I) and (II)
(b) only (II)
(c) (I), (II) and (III)
(d) (I), (II) and (IV)
Answer
(I), (II) and (IV)
Explanation
In pandas, the statement df.count() and df.count(0) calculate the number of non-null values in each column of the DataFrame df. The statement df.count(axis='index') specifies the axis parameter as 'index', which is equivalent to specifying axis=0. This means it will count non-null values in each column of the DataFrame df.
Related Questions
Consider the following DataFrame df and answer any four questions from (i)-(v):
rollno name UT1 UT2 UT3 UT4 1 Prerna Singh 24 24 20 22 2 Manish Arora 18 17 19 22 3 Tanish Goel 20 22 18 24 4 Falguni Jain 22 20 24 20 5 Kanika Bhatnagar 15 20 18 22 6 Ramandeep Kaur 20 15 22 24 Write down the command that will give the following output :
roll no 6 name Tanish Goel UT1 24 UT2 24 UT3 24 UT4 24 dtype : object(a) print(df.max)
(b) print(df.max())
(c) print(df.max(axis = 1))
(d) print(df.max, axis = 1)
Consider the following DataFrame df and answer any four questions from (i)-(v):
rollno name UT1 UT2 UT3 UT4 1 Prerna Singh 24 24 20 22 2 Manish Arora 18 17 19 22 3 Tanish Goel 20 22 18 24 4 Falguni Jain 22 20 24 20 5 Kanika Bhatnagar 15 20 18 22 6 Ramandeep Kaur 20 15 22 24 The teacher needs to know the marks scored by the student with roll number 4. Help her identify the correct set of statement/s from the given options:
(a) df1 = df[df['rollno'] == 4]
print(df1)(b) df1 = df[rollno == 4]
print(df1)(c) df1 = df.[df.rollno = 4]
print(df1)(d) df1 = df[df.rollno == 4]
print(df1)Consider the following DataFrame df and answer any four questions from (i)-(v):
rollno name UT1 UT2 UT3 UT4 1 Prerna Singh 24 24 20 22 2 Manish Arora 18 17 19 22 3 Tanish Goel 20 22 18 24 4 Falguni Jain 22 20 24 20 5 Kanika Bhatnagar 15 20 18 22 6 Ramandeep Kaur 20 15 22 24 Which of the following command will display the column labels of the DataFrame ?
(a) print(df.columns())
(b) print(df.column())
(c) print(df.column)
(d) print(df.columns)
Consider the following DataFrame df and answer any four questions from (i)-(v):
rollno name UT1 UT2 UT3 UT4 1 Prerna Singh 24 24 20 22 2 Manish Arora 18 17 19 22 3 Tanish Goel 20 22 18 24 4 Falguni Jain 22 20 24 20 5 Kanika Bhatnagar 15 20 18 22 6 Ramandeep Kaur 20 15 22 24 Ms. Sharma, the class teacher wants to add a new column, the scores of Grade with the values, 'A', 'B', 'A', 'A', 'B', 'A' , to the DataFrame.
Help her choose the command to do so :
(a) df.column = ['A', 'B', 'A', 'A', 'B', 'A']
(b) df['Grade'] = ['A', 'B', 'A', 'A', 'B', 'A']
(c) df.loc['Grade'] = ['A', 'B', 'A', 'A', 'B', 'A']
(d) Both (b) and (c) are correct