How to copy/paste DataFrame from Stack Overflow into Python

Question

In questions and answers, users very often post an example DataFrame which their question/answer works with:

In []: x
Out[]: 
   bar  foo
0    4    1
1    5    2
2    6    3

It'd be really useful to be able to get this DataFrame into my Python interpreter so I can start debugging the question, or testing the answer.

How can I do this?

Answer 1

Pandas is written by people that really know what people want to do.

Since version 0.13 there's a function pd.read_clipboard which is absurdly effective at making this "just work".

Copy and paste the part of the code in the question that starts bar foo, (i.e. the DataFrame) and do this in a Python interpreter:

In [53]: import pandas as pd
In [54]: df = pd.read_clipboard()

In [55]: df
Out[55]: 
   bar  foo
0    4    1
1    5    2
2    6    3

Caveats

• Don't include the iPython In or Out stuff or it won't work
• If you have a named index, you currently need to add engine='python' (see this issue on GitHub). The 'c' engine is currently broken when the index is named.
• It's not brilliant at MultiIndexes:

Try this:

                      0         1         2
level1 level2                              
foo    a       0.518444  0.239354  0.364764
       b       0.377863  0.912586  0.760612
bar    a       0.086825  0.118280  0.592211

which doesn't work at all, or this:

              0         1         2
foo a  0.859630  0.399901  0.052504
    b  0.231838  0.863228  0.017451
bar a  0.422231  0.307960  0.801993

Which works, but returns something totally incorrect!

Answer 2

pd.read_clipboard() is nifty. However, if you're writing code in a script or a notebook (and you want your code to work in the future) it's not a great fit. Here's an alternative way to copy/paste the output of a dataframe into a new dataframe object that ensures that df will outlive the contents of your clipboard:

import pandas as pd

d = '''0   1   2   3   4
A   Y   N   N   Y
B   N   Y   N   N
C   N   N   N   N
D   Y   Y   N   Y
E   N   Y   Y   Y
F   Y   Y   N   Y
G   Y   N   N   Y'''

df = pd.read_csv(pd.compat.StringIO(d), sep='\s+')

A few notes:

• The triple-quoted string preserves the newlines in the output.
• StringIO wraps the output in a file-like object, which read_csv requires.
• Setting sep to \s+ makes it so that each contiguous block of whitespace is treated as a single delimiter.