dataframe_sql

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dataframe_sql is a Python_ package that translates SQL syntax into operations on pandas_ DataFrames, a functionality which is not available in the central pandas package.

.. _Python: https://www.python.org/

Installation

.. code-block:: bash

pip install dataframe_sql

Usage

In this simple example, a DataFrame is read in from a csv and then using the query function you can produce a new DataFrame from the sql query.

.. code-block:: python

from pandas import read_csv
from dataframe_sql import register_temp_table, query

my_table = read_csv("some_file.csv")

register_temp_table(my_table, "my_table")

query("""select * from my_table""")

The package currently only supports pandas_ but there are plans to support dask_, rapids_, and modin_ in the future.

.. _pandas: https://github.com/pandas-dev/pandas .. _dask: https://github.com/dask/dask .. _rapids: https://github.com/rapidsai/cudf .. _modin: https://github.com/modin-project/modin

SQL Syntax

The SQL syntax for dataframe_sql is exactly the same as the syntax in sql_to_ibis, its underlying package.

You can find the full SQL syntax here <https://github.com/zbrookle/sql_to_ibis#sql-syntax>__

Why use dataframe_sql?

While there are other packages that accomplish the goal of using SQL with pandas DataFrames, all other packages such as pandasql_ actually use a database on the backend which defeats the purpose of using pandas_ to begin with. In the case of pandasql_ which uses SQLite, this can result in major performance bottlenecks. dataframe_sql actually performs native pandas operations in memory on DataFrames, which avoids conflicts that may arise from using external databases.

.. _pandasql: https://github.com/yhat/pandasql