pandas.read_sql_table

pandas.read_sql_table(table_name, con, schema=None, index_col=None, coerce_float=True, parse_dates=None, columns=None, chunksize=None) [source]

Read SQL database table into a DataFrame.

Given a table name and a SQLAlchemy connectable, returns a DataFrame. This function does not support DBAPI connections.

Parameters:

table_name : str Name of SQL table in database. con : SQLAlchemy connectable or str A database URI could be provided as as str. SQLite DBAPI connection mode not supported. schema : str, default None Name of SQL schema in database to query (if database flavor supports this). Uses default schema if None (default). index_col : str or list of str, optional, default: None Column(s) to set as index(MultiIndex). coerce_float : bool, default True Attempts to convert values of non-string, non-numeric objects (like decimal.Decimal) to floating point. Can result in loss of Precision. parse_dates : list or dict, default None List of column names to parse as dates. Dict of {column_name: format string} where format string is strftime compatible in case of parsing string times or is one of (D, s, ns, ms, us) in case of parsing integer timestamps. Dict of {column_name: arg dict}, where the arg dict corresponds to the keyword arguments of pandas.to_datetime() Especially useful with databases without native Datetime support, such as SQLite. columns : list, default None List of column names to select from SQL table. chunksize : int, default None If specified, returns an iterator where chunksize is the number of rows to include in each chunk.

Returns:

DataFrame A SQL table is returned as two-dimensional data structure with labeled axes.

See also

read_sql_query

Read SQL query into a DataFrame.

read_sql

Read SQL query or database table into a DataFrame.

Notes

Any datetime values with time zone information will be converted to UTC.

Examples

>>> pd.read_sql_table('table_name', 'postgres:///db_name')  # doctest:+SKIP