pandas.Series.to_sql¶
Write records stored in a DataFrame to a SQL database.
Databases supported by SQLAlchemy are supported. Tables can be newly created, appended to, or overwritten.
- param name
- string
- Name of SQL table. 
 
- param con
- sqlalchemy.engine.Engine or sqlite3.Connection
- Using SQLAlchemy makes it possible to use any DB supported by that library. Legacy support is provided for sqlite3.Connection objects. 
 
- param schema
- string, optional
- Specify the schema (if database flavor supports this). If None, use default schema. 
 
- param if_exists
- {‘fail’, ‘replace’, ‘append’}, default ‘fail’
- How to behave if the table already exists. - fail: Raise a ValueError. 
- replace: Drop the table before inserting new values. 
- append: Insert new values to the existing table. 
 
 
- param index
- bool, default True
- Write DataFrame index as a column. Uses index_label as the column name in the table. 
 
- param 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. 
 
- param chunksize
- int, optional
- Rows will be written in batches of this size at a time. By default, all rows will be written at once. 
 
- param dtype
- dict, optional
- Specifying the datatype for columns. The keys should be the column names and the values should be the SQLAlchemy types or strings for the sqlite3 legacy mode. 
 
- param method
- {None, ‘multi’, callable}, default None
- Controls the SQL insertion clause used: - None : Uses standard SQL - INSERTclause (one per row).
- ‘multi’: Pass multiple values in a single - INSERTclause.
- callable with signature - (pd_table, conn, keys, data_iter).
 - Details and a sample callable implementation can be found in the section insert method. - New in version 0.24.0. 
 
- raises
- ValueError
- When the table already exists and if_exists is ‘fail’ (the default). 
 
Warning
This feature is currently unsupported by Intel Scalable Dataframe Compiler