Here’s a tricky problem I faced recently.
Problem: Group By 2 columns of a pandas dataframe. Then visualize the aggregate data using a bar plot.
Tip: Use of the keyword ‘unstack’
Code:
# -*- coding: utf-8 -*-
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Created on Tue Dec 01 12:13:42 2015
@author: agoswami
Reference(s):
[1] http://chrisalbon.com/python/pandas_apply_operations_to_groups.html
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import pandas as pd
import matplotlib.pyplot as plt
import numpy as np
raw_data = {
‘regiment’: [‘Nighthawks’, ‘Nighthawks’, ‘Nighthawks’, ‘Nighthawks’, ‘Dragoons’, ‘Dragoons’, ‘Dragoons’, ‘Dragoons’, ‘Scouts’, ‘Scouts’, ‘Scouts’, ‘Scouts’],
‘bucket’: [‘0’, ‘1’, ‘0’, ‘0’, ‘1’, ‘1’, ‘0’, ‘0’,’0′, ‘1’, ‘2’, ‘2’],
‘name’: [‘Miller’, ‘Jacobson’, ‘Ali’, ‘Milner’, ‘Cooze’, ‘Jacon’, ‘Ryaner’, ‘Sone’, ‘Sloan’, ‘Piger’, ‘Riani’, ‘Ali’],
‘clicks’: [4, 24, 31, 2, 3, 4, 24, 31, 2, 3, 2, 3],
‘impressions’: [25, 94, 57, 62, 70, 25, 94, 57, 62, 70, 62, 70]}
df = pd.DataFrame(raw_data)
#Group By regiment and bucket
groupbyregimentbucket = df.groupby([‘regiment’, ‘bucket’])
print “[Grouping by regiment and bucket, and aggregating #of clicks]”
print groupbyregimentbucket[‘clicks’].aggregate(np.sum)
#Without the hierarchical indexing
print “[Unstacking]”
regimentbucketclicksum = groupbyregimentbucket[‘clicks’].aggregate(np.sum).unstack()
print regimentbucketclicksum
regimentbucketclicksum.plot(kind = ‘bar’, title = ‘ by Regiment, Bucket’)
plt.ylabel(‘clicks’)
plt.show()
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