xorbits.pandas.read_sql_table#
- 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.
- Parameters
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 ofpandas.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-backedDataFrame
(default)."pyarrow"
: returns pyarrow-backed nullableArrowDtype
DataFrame.
New in version 2.0(pandas).
- Returns
A SQL table is returned as two-dimensional data structure with labeled axes.
- Return type
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')
This docstring was copied from pandas.