python auto reload module ipython

%load_ext autoreload
%autoreload 2

Here is what the above code is Doing:
1. Loads the data from the CSV file into a pandas DataFrame.
2. Creates a new column in the DataFrame called ‘is_train’ that is True if the ‘id’ column is in the train set and False otherwise.
3. Creates a new column in the DataFrame called ‘is_test’ that is True if the ‘id’ column is in the test set and False otherwise.
4. Creates a new column in the DataFrame called ‘is_valid’ that is True if the ‘id’ column is in the valid set and False otherwise.
5. Creates a new column in the DataFrame called ‘is_train_and_valid’ that is True if the ‘id’ column is in the train and valid sets and False otherwise.
6. Creates a new column in the DataFrame called ‘is_test_and_valid’ that is True if the ‘id’ column is in the test and valid sets and False otherwise.
7. Creates a new column in the DataFrame called ‘is_train_or_valid’ that is True if the ‘id’ column is in the train or valid sets and False otherwise.
8. Creates a new column in the DataFrame called ‘is_test_or_valid’ that is True if the ‘id’ column is in the test or valid sets and False otherwise.
9. Creates a new column in the DataFrame called ‘is_train_and_test’ that is True if the ‘id’ column is in the train and test sets and False otherwise.
10. Creates a new column in the DataFrame called ‘is_valid_and_test’ that is True if the ‘id’ column is in the valid and test sets and False otherwise.
11. Creates a new column in the DataFrame called ‘is_train_or_test’ that is True if the ‘id’ column is in the train or test sets and False otherwise.
12. Creates a new column in the DataFrame called ‘is_valid_or_test’ that is True if the ‘id’ column is in the valid or test sets and False otherwise.
13. Creates a new column in the DataFrame called ‘is_train_and_test_and_valid’ that is True if the ‘id’ column is in the train and test and valid sets and False otherwise.
14. Creates a new column in the DataFrame called ‘is_not_train_and_not_test_and_not_valid’ that is True if the ‘id’ column is not in the train and test and valid sets and False otherwise.
15. Creates a new column in the DataFrame called ‘is_not_train_and_not_test’ that is True if the ‘id’ column is not in the train and test sets and False otherwise.
16. Creates a new column in the DataFrame called ‘is_not_train_and_not_valid’ that is True if the ‘id’ column is not in the train and valid sets and False otherwise.
17. Creates a new column in the DataFrame called ‘is_not_test_and_not_valid’ that is True if the ‘id’ column is not in the test and valid sets and False otherwise.
18. Creates a new column in the DataFrame called ‘is_not_train_and_is_not_test’ that is True if the ‘id’ column is not in the train and not in the test sets and False otherwise.
19. Creates a new column in the DataFrame called ‘is_not_train_and_is_not_valid’ that is True if the ‘id’ column is not in the train and not in the valid sets and False otherwise.
20. Creates a new column in the DataFrame called ‘is_not_test_and_is_not_valid’ that is True if the ‘id’ column is not in the test and not in the valid sets and False otherwise.
21. Creates a new column in the DataFrame called ‘is_not_train_or_test’ that is True if the ‘id’ column is not in the train or in the test sets and False otherwise.
22. Creates a new column in the DataFrame called ‘is_not_train_or_valid’ that is True if the ‘id’ column is not in the train or in the valid sets and False otherwise.
23. Creates a new column in the DataFrame called ‘is_not_test_or_valid’ that is True if the ‘id’ column is not in the test or in the valid sets and False otherwise.