Has anyone used org-mode with the python pandas package? Pandas is in a certain way an alternative to R, but with the (for me) familiar syntax of python. See: http://pandas.pydata.org/
Pandas is very much built to be used interactively, and it outputs its data in space separated tabular format. E.g. in ipython: In [1]: import pandas as pd In [2]: import numpy as np In [3]: pd.DataFrame(np.random.random((4,3)), columns=['A','B','C']) Out[3]: A B C 0 0.628365 0.424279 0.619791 1 0.799666 0.527572 0.132928 2 0.837255 0.138906 0.408233 3 0.388080 0.146212 0.575346 Unfortunately this doesn't output as nicely when used from org-mode: #+BEGIN_SRC python import pandas as pd import numpy as np return pd.DataFrame(np.random.random((4,3)), columns=list('ABC')) #+END_SRC #+RESULTS: : A B C : 0 0.827817 0.664009 0.089161 : 1 0.170031 0.729214 0.110918 : 2 0.575918 0.863924 0.757536 : 3 0.682722 0.774445 0.992041 while I would like to have: | | A | B | C | |---+----------+----------+----------| | 0 | 0.827817 | 0.664009 | 0.089161 | | 1 | 0.170031 | 0.729214 | 0.110918 | | 2 | 0.575918 | 0.863924 | 0.757536 | | 3 | 0.682722 | 0.774445 | 0.992041 | The question is how to get this? Here are a few ideas: 1. Write a general filter in the org-mode elisp than uses heuristics to recognize ascii aligned tables and change these to org-tables. 2. Add to pandas the option of globally influencing the text formatting so that it outputs something more parsable by org-mode. 3. Create a special language "pandas" that recognize the ascii aligned tables and saves the need to import pandas and np? 4. And the obvious approach of writing a python function that writes a org-mode parsable table and always call it as part of the return. Which is the preferable approach? Any other ideas? Regards, Dov