How to select column and rows in pandas without column or row names?

Question

I have a pandas dataframe(df) like this

                         Close      Close     Close Close       Close
Date                                                                 
2000-01-03 00:00:00        NaN        NaN       NaN   NaN   -0.033944
2000-01-04 00:00:00        NaN        NaN       NaN   NaN   0.0351366
2000-01-05 00:00:00  -0.033944        NaN       NaN   NaN  -0.0172414
2000-01-06 00:00:00  0.0351366  -0.033944       NaN   NaN -0.00438596
2000-01-07 00:00:00 -0.0172414  0.0351366 -0.033944   NaN   0.0396476

in R If I want to select fifth column

five=df[,5]

and without 5th column

rest=df[,-5]

How can I do similar operations with pandas dataframe

I tried this in pandas

five=df.ix[,5]

but its giving this error

 File "", line 1
    df.ix[,5]
           ^
SyntaxError: invalid syntax

Answer 1

Use iloc. It is explicitly a position based indexer. ix can be both and will get confused if an index is integer based.

df.iloc[:, [4]]

For all but the fifth column

slc = list(range(df.shape[1]))
slc.remove(4)

df.iloc[:, slc]

or equivalently

df.iloc[:, [i for i in range(df.shape[1]) if i != 4]]

Answer 2

If you want the fifth column:

df.ix[:,4]

Stick the colon in there to take all the rows for that column.

To exclude a fifth column you could try:

df.ix[:, (x for x in range(0, len(df.columns)) if x != 4)]