column datatype conversion impacts whole dataframe when using df.ix indexing #8607
Description
My dataframe has a timestamp column that is encoded as unix epoch. When I convert the column using named index selection it works fine, but when I use the '.ix' syntax it coerces the whole dataframe. Example:
import pandas as pd
df = pd.DataFrame(
{'timestamp':[1413840976, 1413842580, 1413760580],
'delta':[1174, 904, 161],
'elapsed':[7673, 9277, 1470]
})
df2 = df.copy()
df['timestamp'] = pd.to_datetime(df['timestamp'], unit='s')
df2.ix[:,2] = pd.to_datetime(df['timestamp'], unit='s')
df
delta elapsed timestamp
0 1174 7673 2014-10-20 21:36:16
1 904 9277 2014-10-20 22:03:00
2 161 1470 2014-10-19 23:16:20
df2
delta elapsed timestamp
0 2014-10-20 21:36:16 1970-01-01 00:00:00.000007673 1970-01-01 00:00:01.413840976
1 2014-10-20 22:03:00 1970-01-01 00:00:00.000009277 1970-01-01 00:00:01.413842580
2 2014-10-19 23:16:20 1970-01-01 00:00:00.000001470 1970-01-01 00:00:01.413760580
I strongly suspect the difference in behavior here is problematic and should be resolved. If this is actually "how things should work," I'd greatly appreciate it if someone could explain why the different indexing styles produce these different results