pandas.Series.to_sql

Series.to_sql(name, con, flavor=None, schema=None, if_exists='fail', index=True, index_label=None, chunksize=None, dtype=None)

Write records stored in a DataFrame to a SQL database.

Parameters:

name : string Name of SQL table con : SQLAlchemy engine or DBAPI2 connection (legacy mode) Using SQLAlchemy makes it possible to use any DB supported by that library. If a DBAPI2 object, only sqlite3 is supported. flavor : ‘sqlite’, default None DEPRECATED: this parameter will be removed in a future version, as ‘sqlite’ is the only supported option if SQLAlchemy is not installed. schema : string, default None Specify the schema (if database flavor supports this). If None, use default schema. if_exists : {‘fail’, ‘replace’, ‘append’}, default ‘fail’ fail: If table exists, do nothing. replace: If table exists, drop it, recreate it, and insert data. append: If table exists, insert data. Create if does not exist. index : boolean, default True Write DataFrame index as a column. index_label : string or sequence, default None Column label for index column(s). If None is given (default) and index is True, then the index names are used. A sequence should be given if the DataFrame uses MultiIndex. chunksize : int, default None If not None, then rows will be written in batches of this size at a time. If None, all rows will be written at once. dtype : dict of column name to SQL type, default None Optional specifying the datatype for columns. The SQL type should be a SQLAlchemy type, or a string for sqlite3 fallback connection.