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# pandas.read_sql_table

`pandas.``read_sql_table`(table_name, con, index_col=None, coerce_float=True, parse_dates=None, columns=None)

  Read SQL database table into a DataFrame.

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

  Parameters : | table_name : string Name of SQL table in database con : SQLAlchemy engine Sqlite DBAPI conncection mode not supported index_col : string, optional Column to set as index coerce_float : boolean, default True Attempt to convert values to non-string, non-numeric objects (like decimal.Decimal) to floating point. Can result in loss of Precision. parse_dates : list or dict 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 List of column names to select from sql table
  Returns : | DataFrame

  See also

  `read_sql_query`
    Read SQL query into a DataFrame.

  `read_sql`

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