Copying Behavior in DataFrame.rename

example.ipy

In [44]: df
Out[44]:
   a  b
0  1  2
1  2  3
2  3  4

In [45]: renamed = df.rename(columns={'b': 'c'})

In [46]: renamed.iloc[0, 0] = 1000

In [47]: renamed
Out[47]:
      a  c
0  1000  2
1     2  3
2     3  4

In [48]: df  # renamed has a copy of the data, so mutating it doesn't affect the parent.
Out[48]:
   a  b
0  1  2
1  2  3
2  3  4

In [49]: renamed_no_copy = df.rename(columns={'b': 'c'}, copy=False)  # Passing copy=False avoids copies when possible.

In [50]: renamed_no_copy.iloc[0, 0] = 1000

In [51]: renamed_no_copy
Out[51]:
      a  c
0  1000  2
1     2  3
2     3  4

In [52]: df  # Changes to the child now propagate to the parent, because they share the same underlying data.
Out[52]:     # This is good when you care about saving memory, but can be a source of bugs if you're not expecting
      a  b   # it, which is (I assume) why it's not the default behavior.
0  1000  2
1     2  3
2     3  4