#!/usr/bin/env python
# coding: utf-8

# # Hoisting dataframes to the module.
# 
# Creating modules from data is different than software
# In practice, I really like to tidy up dataframes with specific features cleaned in each notebook.  This approach avoids long and difficult to debug notebooks.

# In[1]:


from pandas import util; df = util.testing.makeDataFrame()


# All of the columns in the namespace

# In[2]:


globals().update(dict(df.items()))


# Add dataframe operations to our module

# In[3]:


import IPython


# Hosting attributes.

# In[4]:


with IPython.utils.capture.capture_output(): globals().update({x: getattr(df, x) for x in dir(df)})


# In[6]:


Ø = __name__ == '__main__'
if Ø: from deathbeds import __Dataframes_and_modules


# In[7]:


if Ø: assert isinstance(__Dataframes_and_modules, __import__('types').ModuleType)
Ø and __Dataframes_and_modules.sample(2)