Deepcopy pandas DataFrame containing python objects (such as lists)

Question

Need help understanding variable assignment, pointers, ...

The following is reproducible.

import pandas as pd

df          


        

Answer 1

When you run

df['listDataSort'] = df['listData']

All you do is copy the references of the lists to new columns. This means only a shallow copy is performed and both columns reference the same lists. So any change to one column will likely affect another.

You can use a list comprehension with sorted which returns a copy of the data. This should be the easiest option for you.

df['listDataSort'] = [sorted(x) for x in df['listDataSort']]
df

             listData        listDataSort
0  [c, f, d, a, e, b]  [a, b, c, d, e, f]
1     [5, 2, 1, 4, 3]     [1, 2, 3, 4, 5]

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Now, when it comes to the problem of making a copy of the entire DataFrame, things are a little more complicated. I would recommend deepcopy:

import copy
df2 = df.apply(copy.deepcopy)