From the source of to_sql, I can see that it gets mapped to an Meta Data object meta = MetaData(con, schema=schema)
. However, I can't find SQLAlchemy docs that tell me how to define the Schema for MySQL
How do I specify the schema string ?
Function Parameters name – refers to the SQL table in which the data is saved. con – refers to the connection to the database engine. The SQLAlchemy engine manages the connection to the database. Hence, you can use any database supported by the library. schema – specifies the target schema under which to save the data.
DataFrame - to_sql() function. The to_sql() function is used to write records stored in a DataFrame to a SQL database. Syntax: DataFrame.to_sql(self, name, con, schema=None, if_exists='fail', index=True, index_label=None, chunksize=None, dtype=None, method=None)
Pandas in Python uses a module known as SQLAlchemy to connect to various databases and perform database operations.
The schema parameter in to_sql
is confusing as the word "schema" means something different from the general meaning of "table definitions". In some SQL flavors, notably postgresql, a schema is effectively a namespace for a set of tables.
For example, you might have two schemas, one called test
and one called prod
. Each might contain a table called user_rankings
generated in pandas and written using the to_sql
command. You would specify the test
schema when working on improvements to user rankings. When you are ready to deploy the new rankings, you would write to the prod
schema.
As others have mentioned, when you call to_sql
the table definition is generated from the type information for each column in the dataframe. If the table already exists in the database with exactly the same structure, you can use the append
option to add new data to the table.
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