pandas.read_sql_query(sql, con, index_col=None, coerce_float=True, params=None, parse_dates=None, chunksize=None)
[source]
Read SQL query into a DataFrame.
Returns a DataFrame corresponding to the result set of the query string. Optionally provide an index_col
parameter to use one of the columns as the index, otherwise default integer index will be used.
Parameters: |
sql : string SQL query or SQLAlchemy Selectable (select or text object) SQL query to be executed. con : SQLAlchemy connectable(engine/connection), database string URI, or sqlite3 DBAPI2 connection Using SQLAlchemy makes it possible to use any DB supported by that library. If a DBAPI2 object, only sqlite3 is supported. index_col : string or list of strings, optional, default: None Column(s) to set as index(MultiIndex). coerce_float : boolean, default True Attempts to convert values of non-string, non-numeric objects (like decimal.Decimal) to floating point. Useful for SQL result sets. params : list, tuple or dict, optional, default: None List of parameters to pass to execute method. The syntax used to pass parameters is database driver dependent. Check your database driver documentation for which of the five syntax styles, described in PEP 249’s paramstyle, is supported. Eg. for psycopg2, uses %(name)s so use params={‘name’ : ‘value’} parse_dates : list or dict, default: None
chunksize : int, default None If specified, return an iterator where |
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Returns: |
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Any datetime values with time zone information parsed via the parse_dates
parameter will be converted to UTC.
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Licensed under the 3-clause BSD License.
http://pandas.pydata.org/pandas-docs/version/0.23.4/generated/pandas.read_sql_query.html