1. How do you handle missing values when reading a CSV file into a Pandas DataFrame?

2. How do you rename the index of a DataFrame?

3. How do you pivot a DataFrame based on multiple columns?

4. How do you apply a custom function to each element in a DataFrame?

5. How do you handle categorical data in Pandas?

6. How do you merge two DataFrames with different column names?

7. How do you perform left, right, inner, and outer joins on DataFrames?

8. How do you perform groupby operations on multiple columns?

9. How do you perform aggregation on grouped data in Pandas?

10. How do you convert a datetime string column to a datetime object in Pandas?

11. How do you extract year, month, day, etc., from a datetime column in a DataFrame?

12. How do you convert a string column to lowercase or uppercase in a DataFrame?

13. How do you handle timezone-aware datetime objects in Pandas?

14. How do you handle large datasets in Pandas efficiently?

15. How do you apply a rolling window calculation on a column in a DataFrame?

16. How do you calculate cumulative sum, mean, max, etc., in Pandas?

17. How do you handle hierarchical indexing (MultiIndex) in Pandas?

18. How do you merge DataFrames on multiple columns with different data types?

19. How do you handle duplicate indices when appending DataFrames?

20. How do you concatenate DataFrames with different columns and indexes?

21. How do you interpolate missing values in a DataFrame?

22. How do you perform forward and backward filling of missing values in Pandas?

23. How do you convert a wide DataFrame to a long format (and vice versa)?

24. How do you perform cross-tabulation (crosstab) in Pandas?

25. How do you convert categorical data to numerical data in Pandas?

26. How do you handle outliers in a numerical column of a DataFrame?

27. How do you normalize or standardize numerical data in Pandas?

28. How do you apply a function element-wise across multiple columns in a DataFrame?

29. How do you apply conditional logic across multiple columns in a DataFrame?

30. How do you create custom bins for numerical data in Pandas?

31. How do you apply a function to groups within a DataFrame using apply()?

32. How do you efficiently iterate over rows in a DataFrame?

33. How do you efficiently append rows to a DataFrame?

34. How do you efficiently drop rows based on a condition in Pandas?

35. How do you efficiently calculate percentage change in a column in Pandas?

36. How do you efficiently handle large categorical datasets in Pandas?

37. How do you handle datetime operations across different time zones in Pandas?

38. How do you efficiently handle string operations across a DataFrame?

39. How do you efficiently convert between different data types in Pandas?

40. How do you efficiently handle memory usage optimization in Pandas?

41. How do you handle scientific notation in numerical columns of a DataFrame?

42. How do you efficiently calculate cumulative statistics (e.g., cumulative sum) in Pandas?

43. How do you efficiently merge multiple DataFrames stored in a list?

44. How do you efficiently handle complex data transformations using Pandas?

45. How do you efficiently export a DataFrame to a database using Pandas?

46. How do you efficiently read data from a database into a Pandas DataFrame?

47. How do you efficiently handle complex data cleaning tasks in Pandas?

48. How do you efficiently handle data validation and error checking in Pandas?

49. How do you efficiently handle time series data manipulation in Pandas?

50. How do you efficiently handle data aggregation across multiple dimensions in Pandas?