Python for Data Science (3150713) CHAPTER WISE IMP Questions | SEM 5 GTU IMP's | GTU Medium

 Chapter - 1 

1. List Advantages of Python.

2. Explain Data Types of Python with suitable example.

3. Explain List in Python with suitable example.

4. Explain Set in Python with suitable example.

5. Explain Tuple in Python with suitable example.

6. Explain Dictionary Python with suitable example.

7. Explain expression evaluation in Python with suitable example.

8. Explain functions in Python with suitable example.

9. List and Explain String functions in Python.

10. Explain String Slicing in python with Example.

11. Explain String Formatting in python with example.

12. List and Explain all Data Structures in Python.

13. Explain Loops in Python with suitable example.

Chapter - 2

1. Justify why python is most suitable language for Data Science.

2. Explain Core competencies of a data scientist.

3. Explain steps of Data Science Pipeline.

4. Explain different programming styles (programming paradigms) in python.

5. Explain Factors affecting Speed of Execution.

Chapter - 3

1. List different IDE of Pythons. Explain advantages and disadvantages of each.

2. Write a short note on Jupyter notebooks.

3. Explain Basic IO operations in Python.

4. Write a short note on Data Conditioning.

5. Write a short note on Data Shaping.

6. Differentiate Numpy and Pandas

7. Explain Numpy Array with example.

8. Differentiate rand and randn function in Numpy.

9. List and Explain Numpy Aggregation functions with example.

10 Explain Series in Pandas with example.

11 Explain DataFrame in Pandas with example.

12 Explain Multi-Index DataFrame in pandas with example.

13. Explain Cross Section in DataFrame with Example.

14. Explain how to deal with missing data in Pandas.

15. Explain Groupby function in pandas with example.

16. Explain join function in pandas with example.

17. Explain merge function in pandas with example.

18. Diffrentiate join and merge functions in pandas.

19. Explain read_csv function in pandas with example.

20 Explain read_excel function in pandas with example.

21. Explain Web Scrapping with Example using Beautiful Soup library.

22. Explain Bag of Word model.

Chapter - 4

1. Write a short note on Data Visualization.

2. Write a short note of MatPlotLib.

3. Explain Axes, Ticks and Grid in MatPlotLib with example.

4. List and Exaplain different line appearance in MatPlotLib.

5. Explain Labels, Annotation and Legends in MatPlotLib.

6. List and Explain different graphs in MatPlotLib.

7. Write a program in Python for creating a Histogram/ piechart/ bar chart/ boxplot/ scatterplot

Chapter - 5

1. Write a short note on Data Wrangling.

2. Write a short note on Exploring Data Analysis/ Exploratory Data Analysis (EDA).

3. Differentiate Numerical Data and Categorical Data with suitable example. Also explain how to handle such data types.

4. Write a short note on Classes in Scikit-learn library.

5. Diffrentiate Supervised and Unsupervised learning.

6. Explain Hasing Trick in python with example.

7. Explain timeit magic command in Jupyter Notebook with example.

8. Explain Memory Profiler in Python.

9. Write a program in Python to perform DIFFERENT STATSTICAL OPERATIONS.