Lesson 5

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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 3.5.1 |Anaconda custom (64-bit)| (default, Feb 16 2016, 09:49:46) [MSC v.1900 64 bit (AMD64)]
Pandas version: 0.20.1

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

Out[3]:

	one	two
a	1	2
b	1	2

In [4]:

df.index

Out[4]:

Index(['a', '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=[['a', 'b'], ['one', '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=[['one', 'two'], ['a', '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

Out[9]:

	a	b
one	1	1
two	2	2

In [10]:

transpose.index

Out[10]:

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

This tutorial was created by HEDARO

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