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 3.7.4 (default, Aug 9 2019, 18:34:13) [MSC v.1915 64 bit (AMD64)] Pandas version: 1.0.5
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([('a', 'one'),
('a', 'two'),
('b', 'one'),
('b', 'two')],
)
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([('one', 'a'),
('one', 'b'),
('two', 'a'),
('two', 'b')],
)
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')
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