How to select column and rows in pandas without column or row names?
<p>I have a pandas dataframe(df) like this</p>

<pre><code>                         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
</code></pre>

<p>in <code>R</code> If I want to select fifth column</p>

<pre><code>five=df[,5]
</code></pre>

<p>and without 5th column</p>

<pre><code>rest=df[,-5]
</code></pre>

<p>How can I do similar operations with pandas dataframe</p>

<p>I tried this in pandas</p>

<pre><code>five=df.ix[,5]
</code></pre>

<p>but its giving this error</p>

<pre><code> File "", line 1
    df.ix[,5]
           ^
SyntaxError: invalid syntax
</code></pre>

<p>To select filter column by index:</p>

<pre><code>In [19]: df
Out[19]: 
                 Date     Close   Close.1   Close.2  Close.3   Close.4
0  2000-01-0300:00:00       NaN       NaN       NaN      NaN -0.033944
1  2000-01-0400:00:00       NaN       NaN       NaN      NaN  0.035137
2  2000-01-0500:00:00 -0.033944       NaN       NaN      NaN -0.017241
3  2000-01-0600:00:00  0.035137 -0.033944       NaN      NaN -0.004386
4  2000-01-0700:00:00 -0.017241  0.035137 -0.033944      NaN  0.039648

In [20]: df.ix[:, 5]
Out[20]: 
0   -0.033944
1    0.035137
2   -0.017241
3   -0.004386
4    0.039648
Name: Close.4, dtype: float64

In [21]: df.icol(5)
/usr/bin/ipython:1: FutureWarning: icol(i) is deprecated. Please use .iloc[:,i]
  #!/usr/bin/python2
Out[21]: 
0   -0.033944
1    0.035137
2   -0.017241
3   -0.004386
4    0.039648
Name: Close.4, dtype: float64

In [22]: df.iloc[:, 5]
Out[22]: 
0   -0.033944
1    0.035137
2   -0.017241
3   -0.004386
4    0.039648
Name: Close.4, dtype: float64
</code></pre>

<p>To select all columns except index:</p>

<pre><code>In [29]: df[[df.columns[i] for i in range(len(df.columns)) if i != 5]]
Out[29]: 
                 Date     Close   Close.1   Close.2  Close.3
0  2000-01-0300:00:00       NaN       NaN       NaN      NaN
1  2000-01-0400:00:00       NaN       NaN       NaN      NaN
2  2000-01-0500:00:00 -0.033944       NaN       NaN      NaN
3  2000-01-0600:00:00  0.035137 -0.033944       NaN      NaN
4  2000-01-0700:00:00 -0.017241  0.035137 -0.033944      NaN
</code></pre>

python pandas