Lesson 6

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Lets take a look at the groupby function.

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':[1,1,1,1,1],
     'two':[2,2,2,2,2],
     'letter':['a','a','b','b','c']}

# Create dataframe
df = pd.DataFrame(d)
df

Out[3]:

In [4]:

# Create group object
one = df.groupby('letter')

# Apply sum function
one.sum()

Out[4]:

In [5]:

letterone = df.groupby(['letter','one']).sum()
letterone

Out[5]:

In [6]:

letterone.index

Out[6]:

MultiIndex(levels=[['a', 'b', 'c'], [1]],
           labels=[[0, 1, 2], [0, 0, 0]],
           names=['letter', 'one'])

You may want to not have the columns you are grouping by become your index, this can be easily achieved as shown below.

In [7]:

letterone = df.groupby(['letter','one'], as_index=False).sum()
letterone

Out[7]:

In [8]:

letterone.index

Out[8]:

Int64Index([0, 1, 2], dtype='int64')

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