Series.to_sql(name, con, flavor=None, schema=None, if_exists='fail', index=True, index_label=None, chunksize=None, dtype=None)
[source]
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’
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 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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http://pandas.pydata.org/pandas-docs/version/0.22.0/generated/pandas.Series.to_sql.html