blaze – Data Blending and Analysis¶
blaze allows Python users a familiar interface to query data living in diverse data storage systems. Cf. http://blaze.pydata.org/.
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import blaze as bz
Simple Example¶
The first example constructs a blaze.Data object from native Python objects.
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t = bz.Table([('Henry', 'boy', 8),
('Lilli', 'girl', 14)],
columns=['name', 'gender', 'age'])
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t
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t[t.age > 10]
Out[4]:
Data from NumPy Array¶
Let us read data from an in-memory NumPy ndarray object.
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import numpy as np
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t1 = bz.Table(np.random.standard_normal((1000, 5)),
columns=['f0', 'f1', 'f2', 'f3', 'f4'])
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t1
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t1.data
Out[8]:
Data from CSV File¶
We generate first a CSV file using random data.
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import pandas as pd
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df = pd.DataFrame(np.random.standard_normal((1000, 5)),
columns=['f0', 'f1', 'f2', 'f3', 'f4'])
df.to_csv('data.csv', index=False)
Let us read the data with blaze.
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c = bz.CSV('data.csv')
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t2 = bz.Table(c)
t2.count()
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t2
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t2.data
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Data from SQL¶
We now generate a SQLite3 table with dummy data.
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import sqlite3 as sq3
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con = sq3.connect('data.sql')
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try:
con.execute('DROP TABLE numbers')
except:
pass
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con.execute('CREATE TABLE numbers (f0 real, f1 real, f2 real, f3 real, f4 real)')
Out[18]:
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con.executemany('INSERT INTO numbers VALUES (?, ?, ?, ?, ?)',
np.random.standard_normal((1000, 5)))
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con.commit()
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con.close()
Now reading the data with blaze.
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t3 = bz.Table('sqlite:///data.sql::numbers')
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t3
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t3.data
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Cleaning Up¶
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!ls data.* -n
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# cleaning up
!rm data.*
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