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Project Description

pandasql allows you to query pandas DataFrames using SQL syntax. It works similarly to sqldf in R. pandasql seeks to provide a more familiar way of manipulating and cleaning data for people new to Python or pandas.

Installation

$ pip install -U pandasql

Basics

The main function used in pandasql is sqldf. sqldf accepts 2 parametrs - a sql query string - an set of session/environment variables (locals() or globals())

Specifying locals() or globals() can get tedious. You can defined a short helper function to fix this.

from pandasql import sqldf
pysqldf = lambda q: sqldf(q, globals())

Querying

pandasql uses SQLite syntax. Any pandas dataframes will be automatically detected by pandasql. You can query them as you would any regular SQL table.

$ python
>>> from pandasql import sqldf, load_meat, load_births
>>> pysqldf = lambda q: sqldf(q, globals())
>>> meat = load_meat()
>>> births = load_births()
>>> print pysqldf("SELECT * FROM meat LIMIT 10;").head()
                  date  beef  veal  pork  lamb_and_mutton broilers other_chicken turkey
0  1944-01-01 00:00:00   751    85  1280               89     None          None   None
1  1944-02-01 00:00:00   713    77  1169               72     None          None   None
2  1944-03-01 00:00:00   741    90  1128               75     None          None   None
3  1944-04-01 00:00:00   650    89   978               66     None          None   None
4  1944-05-01 00:00:00   681   106  1029               78     None          None   None

joins and aggregations are also supported

>>> q = """SELECT
        m.date, m.beef, b.births
     FROM
        meats m
     INNER JOIN
        births b
           ON m.date = b.date;"""
>>> joined = pyqldf(q)
>>> print joined.head()
                    date    beef  births
403  2012-07-01 00:00:00  2200.8  368450
404  2012-08-01 00:00:00  2367.5  359554
405  2012-09-01 00:00:00  2016.0  361922
406  2012-10-01 00:00:00  2343.7  347625
407  2012-11-01 00:00:00  2206.6  320195

>>> q = "select
           strftime('%Y', date) as year
           , SUM(beef) as beef_total
           FROM
              meat
           GROUP BY
              year;"
>>> print pysqldf(q).head()
   year  beef_total
0  1944        8801
1  1945        9936
2  1946        9010
3  1947       10096
4  1948        8766

More information and code samples available in the examples folder or on our blog.

Release History

Release History

0.7.3

This version

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0.7.2

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0.7.1

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0.7.0

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0.6.3

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0.6.2

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0.6.1

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0.6.0

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0.5.1

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0.5.0

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0.4.3

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0.4.2

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0.4.1

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0.4.0

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0.3.1

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0.3.0

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0.2.1

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0.2.0

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0.1.3

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0.1.2

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0.1.1

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0.1.0

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0.0.9

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0.0.8

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0.0.7

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0.0.6

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0.0.5

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0.0.4

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0.0.3

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0.0.2

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0.0.1

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Download Files

Download Files

TODO: Brief introduction on what you do with files - including link to relevant help section.

File Name & Checksum SHA256 Checksum Help Version File Type Upload Date
pandasql-0.7.3-py2.7.egg (36.3 kB) Copy SHA256 Checksum SHA256 2.7 Egg Apr 20, 2016
pandasql-0.7.3.tar.gz (26.7 kB) Copy SHA256 Checksum SHA256 Source Apr 20, 2016

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