Lesson 5

We will be taking a brief look at the stack and unstack functions.



In [1]:

    
# Import libraries
import pandas as pd
import sys



In [2]:

    
print 'Python version ' + sys.version
print 'Pandas version: ' + pd.__version__









    



Python version 2.7.5 |Anaconda 2.1.0 (64-bit)| (default, Jul  1 2013, 12:37:52) [MSC v.1500 64 bit (AMD64)]
Pandas version: 0.15.2



In [3]:

    
# Our small data set
d = {'one':[1,1],'two':[2,2]}
i = ['a','b']

# Create dataframe
df = pd.DataFrame(data = d, index = i)
df



In [4]:

    
df.index









    Out[4]:





Index([u'a', u'b'], dtype='object')



In [5]:

    
# Bring the columns and place them in the index
stack = df.stack()
stack









    Out[5]:





a  one    1
   two    2
b  one    1
   two    2
dtype: int64



In [6]:

    
# The index now includes the column names
stack.index









    Out[6]:





MultiIndex(levels=[[u'a', u'b'], [u'one', u'two']],
           labels=[[0, 0, 1, 1], [0, 1, 0, 1]])



In [7]:

    
unstack = df.unstack()
unstack









    Out[7]:





one  a    1
     b    1
two  a    2
     b    2
dtype: int64



In [8]:

    
unstack.index









    Out[8]:





MultiIndex(levels=[[u'one', u'two'], [u'a', u'b']],
           labels=[[0, 0, 1, 1], [0, 1, 0, 1]])

We can also flip the column names with the index using the T (transpose) function.



In [9]:

    
transpose = df.T
transpose



In [10]:

    
transpose.index









    Out[10]:





Index([u'one', u'two'], dtype='object')

Author: David Rojas