xorbits.pandas.read_sql_table(table_name, con, schema=None, index_col=None, coerce_float=True, parse_dates=None, columns=None, chunksize=None, test_rows=5, chunk_size=None, engine_kwargs=None, incremental_index=True, use_arrow_dtype=None, partition_col=None, num_partitions=None, low_limit=None, high_limit=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.

  • table_name (str) – Name of SQL table in database.

  • con (SQLAlchemy connectable or str) – A database URI could be provided 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.

  • dtype_backend ({'numpy_nullable', 'pyarrow'}, default 'numpy_nullable' (Not supported yet)) –

    Back-end data type applied to the resultant DataFrame (still experimental). Behaviour is as follows:

    • "numpy_nullable": returns nullable-dtype-backed DataFrame (default).

    • "pyarrow": returns pyarrow-backed nullable ArrowDtype DataFrame.

    New in version 2.0(pandas).


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

Return type

DataFrame or Iterator[DataFrame]

See also


Read SQL query into a DataFrame.


Read SQL query or database table into a DataFrame.


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


>>> pd.read_sql_table('table_name', 'postgres:///db_name')  

This docstring was copied from pandas.