These two methods are almost database-agnostic, so you can use them for any SQL database of your choice: MySQL, Postgres, Snowflake, MariaDB, Azure, etc. In this post you will learn two easy ways to use Python and SQL from the Jupyter notebooks interface and create SQL queries with a few lines of code. What if you could use both programming languages inside of one tool? SQL is extremely good for data retrieval and calculating basic statistics, whereas Python comes into its own when you need in-depth, flexible exploratory data analysis or data science. Why you need to combine SQL and Python inside Jupyter notebooks Method 2: Using SQL cells in Datalore notebooks.Step 2: Create a database connection in Jupyter.Step 1: Install a Python package to connect to your database.Why you need to combine SQL and Python inside Jupyter notebooks.
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