# 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 since version 0.19.0: ‘sqlite’ is the only supported option if SQLAlchemy is not used.

  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.

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