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Fonction read_sql_table - module pandas

Signature de la fonction read_sql_table

def read_sql_table(table_name, con, schema=None, index_col=None, coerce_float=True, parse_dates=None, columns=None, chunksize: Optional[int] = None) -> Union[pandas.core.frame.DataFrame, Iterator[pandas.core.frame.DataFrame]] 

Description

read_sql_table.__doc__

    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.

    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