Question 1

How can missing values in a DataFrame be handled in Pandas?

Options :

A : Removing the rows with missing values

B : Interpolating missing values

C : Replacing missing values with a specific value

D : All of the above

Answer: D

Question 2

How do you load a CSV file into a Pandas Data Frame?

Options :

A : pd.csv_load()

B : pd.open_csv()

C : pd.load_csv()

D : pd.read_csv()

Answer: D

Question 3

What is the output of the following code snippet? import numpy as np arr = np.array([1, 2, 3, 4, 5]) result = arr[arr > 2]

Options :

A : [3, 4, 5]

B : [2, 3, 4, 5]

C : [1, 2, 3, 4, 5]

D : [1]

Answer: A

Question 4

Which of the following is NOT a data structure supported by Pandas?

Options :

A : Array

B : DataFrame

C : Panel

D : Series

Answer: A

Question 5

What is the function used to read a CSV file in Pandas?

Options :

A : read_json()

B : read_csv()

C : read_excel()

D : read_sql()

Answer: B