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3. You are analysing financial data from two companies. One uses `100.00 and the other uses Rs.100 format.
What would you do to standardise the currency values for analysis?
Ans. I would use replace() to convert “Rs.” to “`” and make sure all amounts follow the `100.00 format. I will
also convert text values to float for easier calculations and comparisons.
Assertion and Reasoning Questions:
Direction: Questions 4-5, consist of two statements – Assertion (A) and Reasoning (R). Answer these questions
by selecting the appropriate option given below:
a. Both A and R are true and R is the correct explanation of A.
b. Both A and R are true but R is not the correct explanation of A.
c. A is true but R is false.
d. A is false but R is true.
4. Assertion (A): Data cleaning is optional before building a machine learning model.
Reason (R): Models can learn from data even if it contains missing and duplicate values.

5. Assertion (A): Z-score normalization is useful when features have different scales.
Reason (R): It adjusts the data to a standard format with mean 0 and standard deviation 1.
Ans. 4. c 5. a
Statement-Based Questions:
Direction: Questions 6-7, two statements are given: Statement 1 and Statement 2. Examine the statements
and mark the correct option:
a. Statement 1 is true, Statement 2 is true
b. Statement 1 is false, Statement 2 is false
c. Statement 1 is true, Statement 2 is false
d. Statement 1 is false, Statement 2 is true
6. Statement 1: The drop_duplicates() function in Pandas removes rows with missing values.

Statement 2: The dropna() function is used to remove rows with missing data.
7. Statement 1: Standardising data formats helps in better comparison and analysis.
Statement 2: Z-score normalization converts text data into lowercase.
Ans. 6. d 7. c

Unsolved Questions
SECTION A (Objective Type Questions)
AI QUIZ
A. Tick (ü) the correct option.
1. Identify the main goal of data cleaning.
a. To create charts b. To remove errors and fix data issues

c. To build a machine learning model d. To print the data
2. Which of the following is NOT a part of the data cleaning process?
a. Filling missing values b. Fixing spelling mistakes

c. Creating pie charts d. Removing duplicates
3. Choose the function that is used to remove duplicate rows in a DataFrame.

a. remove_duplicates() b. drop()
c. drop_duplicates() d. clean_duplicates()

236 Touchpad Artificial Intelligence - XI