When assigning to a column in a DataFrame, If I assign an existing column, the assignment works:
In [36]: df = pd.DataFrame({'a':[1,2,12], 'b':['a','b','a']})
In [37]: df.b = df.a
In [38]: print df
a b
0 1 1
1 2 2
2 12 12
[3 rows x 2 columns]
but assigning to a new column fails silently:
In [40]:df = pd.DataFrame({'a':[1,2,12], 'b':['a','b','a']})
In [41]:df.c = df.a
In [42]:print df
a b
0 1 a
1 2 b
2 12 a
[3 rows x 2 columns]
Comment From: jreback
see as #5904 (prob best to issue a warning if their is a name clash)
you are assigning not a column here, but just an attribute
e.g. people do this df.name = 'foo' this does not create a column nor should it
you can make a case for what you are suggesting to work , but the attribute access is really geting only (unless its a reassignment).
I personally think we should bank the reassignment actually.
Comment From: cancan101
I would be fine not allowing this at all. What confuses me is that I can use it for reassignment, but then if I forget and try to use for assignment, it just fails without telling me.
Comment From: jreback
yeh...I don't know when the reassignment was allowed...
try taking it out and see what breaks
I don't think its a big deal to break the API...but let's see
Comment From: TomAugspurger
Closing in favor of https://github.com/pandas-dev/pandas/issues/7175 (warn on setting)