pandas.read_sql_table

pandas.read_sql_table(table_name, con, schema=None, index_col=None, coerce_float=True, parse_dates=None, columns=None, chunksize=None) [source]

Read SQL database table into a DataFrame.

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

Parameters:

table_name : string Name of SQL table in database con : SQLAlchemy connectable (or database string URI) Sqlite DBAPI connection mode not supported schema : string, default None Name of SQL schema in database to query (if database flavor supports this). If None, use default schema (default). index_col : string or list of strings, optional, default: None Column(s) to set as index(MultiIndex) 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, 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, return an iterator where chunksize is the number of rows to include in each chunk.

Returns:

DataFrame

See also

read_sql_query

Read SQL query into a DataFrame.

read_sql

Notes

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