True / False For Python Pandas 2 Class 12 Informatics Practices

True / False For Python Pandas 2 Class 12 Informatics Practices

1. max() function is an example of an aggregate function.
2. The functions rsub() and radd() stand for right-side subtraction and right-side addition in Pandas.
3. The mode() returns the average value of requested axis.
4. The quantile of a value is the fraction of observations less than or equal to the values.
5. In Pandas, groupby() function allows us to rearrange the data by utilizing them on real-world datasets and split the data into various groups, based on the same criteria.
6. Sorting refers to arranging values in a particular order.
7. Transform function can be split with dataframe easily.
8. If you pass a single value function, then apply function will behave like applymap() function.
9. You cannot apply functions on multiple columns of a dataframe.
10. pivot() function returns the result in the form of newly-created data frame.
11. pivot() function cannot deal with duplicate values for one index/columns.
12. When you create a dataframe object, it gets its row numbers and column labels automatically.
13. Pivoting is allowed in Pandas but without filtering.
14. Apart from the available dataset, pivoting can be successfully implemented by importing a .csv file as well.
15. The iteritems() iterates over the rows of a dataframe.
16. The iteritems() iterates over the columns of a dataframe.
17. The result produced by the functions sub() and rsub() is the same.
18. The result produced by the functions add() and radd() is the same.
19. The result produced by the functions div() and rdiv() is the same.
20. The info() and describe() list the same information about a dataframe.
21. Function add() and operator + give the same result.
22. Function rsub() and operator - give the same result.
23. The minus - operator's result is same as sub() and rsub().
24. Python integer datatype can store NaN values.
25. Functions sum() and cumsum() produce the same result.
26. Functions pivot() and pivot_table() are identical functions.
27. Function pivot() can work with unique data only.
28. Function pivot_table() can work with unique data.
29. Function pivot_table() can work with duplicate data.
30. By default, hist() will create histogram for all numeric columns of a dataframe.
31. The fillna() can also fill individual missing values for difficult columns.
32. To drop missing values from a dataframe, the function used is delna( ).
33. The merge() and concat() work identically.
34. With merge( ), you can specify the merging field.


Answer :-


1. True
2. True
3. False
4. True
5. True
6. True
7. False
8. True
9. False
10. True
11. True
12. True
13. False
14. True
15. FALSE
16. TRUE
17. FALSE
18. TRUE
19. FALSE
20. FALSE
21. TRUE
22. TRUE
23. FALSE
24. FALSE
25. FALSE
26. FALSE
27. TRUE
28. TRUE
29. TRUE
30. TRUE
31. TRUE
32. FALSE
33. FALSE
34. TRUE