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Below example uses nested lists there by making the differences more evident. I am trying to create a script on windows which when run on an admin pc To get a fully independent copy of an object you can use the copy.deepcopy() function

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For more details about shallow and deep copying please refer to the other answers to this question and the nice explanation in this answer to a related question.

When selecting a sub dataframe from a parent dataframe, i noticed that some programmers make a copy of the data frame using the.copy() method

For example, x = my_dataframe[features_list].copy(). If you want a copy, the fastest way of doing this would be to save the project Then make a copy of the entire thing on the file system Go back into visual studio and open the copy (by right clicking on solution => add existing project => open the copied project)

The copy module does not use the copy_reg registration module In order for a class to define its own copy implementation, it can define special methods __copy__() and __deepcopy__() The former is called to implement the shallow copy operation No additional arguments are passed.

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Import copy new_list = copy.copy(old_list) this is a little slower than list() because it has to find out the datatype of old_list first

If you need to copy the elements of the list as well, use generic copy.deepcopy() Shallow copying creates a new instance of the same class and copies all the fields to the new instance and returns it Object class provides a clone method and provides support for the shallow copying A deep copy occurs when an object is.

Copy a section of your page (element) than copying html With this simple function you can copy whatever you want (text, images, tables, etc.) on your page or the whole document to the clipboard.

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