A Python package that parses SQL and interprets it as methods that act upon existing pandas (or other types of) DataFrames that have been declared and registered
dataframe_sql =============
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`dataframesql 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 dataframesql import registertemp_table, query
mytable = readcsv("some_file.csv")
registertemptable(mytable, "mytable")
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 sqltoibis, its underlying package.
You can find the full SQL syntax
here __
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
