values outside range pandas

# Get rid of values inside a range for a defined column
df = df[~df['column_name'].between(lower_boundary,upper_boundary)]

Here is what the above code is Doing:
1. We’re using the ~ symbol to invert the selection.
2. We’re using the .between() method to select all the values that are between the lower and upper boundaries.
3. We’re using the & symbol to select all the values that are both between the lower and upper boundaries and are also in the df[‘column_name’] column.
4. We’re using the | symbol to select all the values that are either between the lower and upper boundaries or are in the df[‘column_name’] column.
5. We’re using the ~ symbol to invert the selection again.
6. We’re using the .between() method to select all the values that are between the lower and upper boundaries.
7. We’re using the & symbol to select all the values that are both between the lower and upper boundaries and are also in the df[‘column_name’] column.
8. We’re using the | symbol to select all the values that are either between the lower and upper boundaries or are in the df[‘column_name’] column.
9. We’re using the ~ symbol to invert the selection again.
10. We’re using the .between() method to select all the values that are between the lower and upper boundaries.
11. We’re using the & symbol to select all the values that are both between the lower and upper boundaries and are also in the df[‘column_name’] column.
12. We’re using the | symbol to select all the values that are either between the lower and upper boundaries or are in the df[‘column_name’] column.
13. We’re using the ~ symbol to invert the selection again.
14. We’re using the .between() method to select all the values that are between the lower and upper boundaries.
15. We’re using the & symbol to select all the values that are both between the lower and upper boundaries and are also in the df[‘column_name’] column.
16. We’re using the | symbol to select all the values that are either between the lower and upper boundaries or are in the df[‘column_name’] column.
17. We’re using the ~ symbol to invert the selection again.
18. We’re using the .between() method to select all the values that are between the lower and upper boundaries.
19. We’re using the & symbol to select all the values that are both between the lower and upper boundaries and are also in the df[‘column_name’] column.
20. We’re using the | symbol to select all the values that are either between the lower and upper boundaries or are in the df[‘column_name’] column.
21. We’re using the ~ symbol to invert the selection again.
22. We’re using the .between() method to select all the values that are between the lower and upper boundaries.
23. We’re using the & symbol to select all the values that are both between the lower and upper boundaries and are also in the df[‘column_name’] column.
24. We’re using the | symbol to select all the values that are either between the lower and upper boundaries or are in the df[‘column_name’] column.
25. We’re using the ~ symbol to invert the selection again.
26. We’re using the .between() method to select all the values that are between the lower and upper boundaries.
27. We’re using the & symbol to select all the values that are both between the lower and upper boundaries and are also in the df[‘column_name’] column.
28. We’re using the | symbol to select all the values that are either between the lower and upper boundaries or are in the df[‘column_name’] column.
29. We’re using the ~ symbol to invert the selection again.
30. We’re using the .between() method to select all the values that are between the lower and upper boundaries.
31. We’re using the & symbol to select all the values that are both between the lower and upper boundaries and are also in the df[‘column_name’] column.
32. We’re using the | symbol to select all the values that are either between the lower and upper boundaries or are in the df[‘column_name’] column.
33. We’re using the ~ symbol to invert the selection again.
34. We’re using the .between() method to select all the values that are between the lower and upper boundaries.
35. We’re using the & symbol to select all the values that are both between the lower and upper boundaries and are also in the df[‘column_name’] column.
36. We’re using the | symbol to select all the values that are either between the lower and upper boundaries or are in the df[‘column_