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Module « pandas »

Fonction read_sql_table - module pandas

Signature de la fonction read_sql_table

def read_sql_table(table_name: 'str', con, schema: 'str | None' = None, index_col: 'str | list[str] | None' = None, coerce_float: 'bool' = True, parse_dates: 'list[str] | dict[str, str] | None' = None, columns: 'list[str] | None' = None, chunksize: 'int | None' = None, dtype_backend: 'DtypeBackend | lib.NoDefault' = <no_default>) -> 'DataFrame | Iterator[DataFrame]' 

Description

help(pandas.read_sql_table)

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

    * ``"numpy_nullable"``: returns nullable-dtype-backed :class:`DataFrame`
      (default).
    * ``"pyarrow"``: returns pyarrow-backed nullable :class:`ArrowDtype`
      DataFrame.

    .. versionadded:: 2.0

Returns
-------
DataFrame or Iterator[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

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