Databases supported by SQLAlchemy [1] are supported. pandas.DataFrame.to_sql — pandas 1.5.0.dev0+849.g3bf2cb1b22 documentation But to_sql() completely stops executing if even one duplicate is detected. # Create the engine to connect to the inbuilt. You can use the following syntax to get from Pandas DataFrame to SQL: df.to_sql ('products', conn, if_exists='replace', index = False) Where 'products' is the table name created in step 2. Adding rows in df pandas if doesn't exists and based on conditions. pandas.DataFrame.to_sql - DataFrameに格納されているレコードをSQLデータベースに書き込みます ... Connecting Pandas to a Database with SQLAlchemy Like we did above, we can also convert a PostgreSQL table to a pandas dataframe using the read_sql_table() function as shown below. Finally, we execute commands using the execute () method to execute our SQL commands and fetchall () method to fetch the records. The database has been created. Python Code: jdata=json.loads(json_data) df=pandas.DataFrame. How to convert pandas DataFrame into SQL in Python? image.png. PostgreSQL 13 : Download link . Python DataFrame.to_sql - 30 examples found. Create if does not exist. pandas.DataFrame.to_sql — pandas 0.15.2 documentation If a table does not exist pd.to_sql is unconditionnally creating it. Python3. # import the necessary packages. Benchmarks for writing pandas DataFrames to SQL Server (ODBC) Note that if data is a pandas DataFrame, a Spark DataFrame, and a pandas-on-Spark Series, other arguments should not be used.