pandas.Series.to_sql

Series.to_sql(name, con, flavor='sqlite', 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’, ‘mysql’}, default ‘sqlite’

The flavor of SQL to use. Ignored when using SQLAlchemy engine. ‘mysql’ is deprecated and will be removed in future versions, but it will be further supported through SQLAlchemy engines.

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.