![]() You just saw how to create a database in Python using the sqlite3 package. You’ll then get the following results: product_name price LEFT JOIN prices b ON a.product_id = b.product_idĭf = pd.DataFrame(c.fetchall(), columns=) You can then run the following code to display the results in Pandas DataFrame: import sqlite3 INSERT INTO products (product_id, product_name)įor the final step, let’s join the ‘ products‘ table with the ‘ prices‘ table using the product_id column which is present in both tables. Here is the complete code to insert the values into the 2 tables: import sqlite3 Let’s also insert the following data into the ‘ prices‘ table: product_id Step 2: Insert values into the tablesįor this step, let’s insert the following data into the ‘ products‘ table: product_id The brute force approach to getting the authorbookpublisher.csv data into an SQLite database would be to create a single table. Once you run the above script in Python, a new file, called test_database, would be created at the same location where you saved your Python script. Here are the columns to be added for the 2 tables: Table Nameīelow is the script that you can use in order to create the database and the 2 tables using sqlite3: import sqlite3 ![]() ![]() We will create the Create, Read, Update and Delete operation to manage the data in the database. nnect('database_name') Steps to Create a Database in Python using sqlite3 Step 1: Create the Database and Tables Load a SQLite database: Drag and drop your SQLite file directly into the SQLite editor or click on 'Database file > Open DB file' to open your SQLite database. Create a database and tables using sqlite3īut before we begin, here is a simple template that you can use to create your database using sqlite3: import sqlite3.In this guide, you’ll see a complete example with the steps to create a database in Python using sqlite3. ![]()
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