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B. Fill in the blanks.
1. The function is used to plot a pie chart.

2. Microsoft is a popular spreadsheet software that allows users to create a variety of charts.
3. A pair plot shows plots for every pair of numerical variables in a dataset.
4. The submodule provides a MATLAB-like interface.

5. Spelling and errors can make your data unclear or misleading.
6. Every dataset consists of and .
7. can be as simple as a list of numbers or as complex as images, audio, and videos.
8. values can cause errors in calculations.

9. is one of the most popular programming languages for data analysis and visualization.
10. Python helps us quickly identify patterns, trends, and in the data.

C. State whether the following statement is true or false.
1. Python cannot be used for data visualization.
2. Using too many features in a dataset can lead to the curse of dimensionality.

3. LDA focuses on maximising class separability, commonly used in classification tasks.
4. Each attribute or feature represents a dimension.
5. The bar graph is best suited to represent categorical data.

6. The xlabel () function adds title to the chart.
7. The scatter plot chart is best suited to represent categorical data.
8. Histogram is the simplest method for visualising data distributions.

SECTION B (Subjective Type Questions)
A. Short answer type questions.

1. Why is data visualization important in today’s world?
2. What is Seaborn? Write the steps to install seaborn.
3. Describe any two types of chart.
4. What is multi-dimensional data visualization, and how does it help in understanding complex datasets?

5. What is the curse of dimensionality in data science, and what challenges does it present as the number of
dimensions increases?

6. State any four functions of Matplotlib library with their descriptions.
7. What is data cleaning process?
8. Write the steps to replace irrelevant data with meaningful data.
9. List the functions that can be used to Standardise data.
10. What do you understand by outliers?

B. Long answer type questions.
1. Describe any three tools commonly used for data visualization.

2. Write the steps to remove duplicate entries in Excel.
3. Describe any five graph types for multi-dimensional data visualization.
4. What is dimensionality reduction in data science, and why is it important?

Data Visualization 189