Table Explorer#
New in version 0.7.6:
pip install jupysql --upgrade
In this guide, we demonstrate how to use JupySQL’s table explorer to visualize SQL tables in HTML format and interact with them efficiently. By running SQL queries in the background instead of loading the data into memory, we minimize the resource consumption and processing time required for handling large datasets, making the interaction with the SQL tables faster and more streamlined.
Let’s start by preparing our dataset. We’ll be using the NYC taxi dataset.
Download the data#
from pathlib import Path
from urllib.request import urlretrieve
url = "https://d37ci6vzurychx.cloudfront.net/trip-data/yellow_tripdata_2021-01.parquet"
if not Path("yellow_tripdata_2021-01.parquet").is_file():
urlretrieve(url, "yellow_tripdata_2021.parquet")
Installation#
%pip install jupysql --upgrade --quiet
Note: you may need to restart the kernel to use updated packages.
Set connection#
After our dataset is ready, we should set our connection.
For this demonstration, we’ll be using the DuckDB connection.
%load_ext sql
%sql duckdb://
Connecting to 'duckdb://'