Example Sheets using Python

Dive into the vibrant world of Neptyne's users. This gallery showcases the innovative projects developed by our community, leveraging the power of Python and AI combined with the Neptyne Google Sheets Extension. Witness the endless possibilities that Neptyne enables and get inspired for your next creation.

Stock Quote Prediction

Fetch and predict stock prices from real data. Uses Google Sheet's GOOGLEFINANCE formula to fetch recent stock prices, combined with a python function to predict the next price.

OpenAI Recipe

Call OpenAI to create a recipe based on a list of ingredients, a goal and a preparation time. Requires open-ai key that needs to be set up in the secrets management.

Iris Classification

Data exploration and classification of Iris flowers by sepal and petal sizes. Uses the sci-kit learn package to build and train a classifier.

Weather Forecast

A simple weather application that uses both Google's geocoding API, combined with the MET weather API to fetch the current and upcoming weather in a location.

News Map

Use python to fetch the latest news from around the world. Combine this data with the map chart to create a display where you can mouseover a dot and see the latest news there.

Chess

Render a chess position from a sequence of moves inside your sheet! Uses the python-chess package to track and modify the board state. A great jumping off point for experimenting with chess and chess engines.

Estimate Pi with Random Numbers

A visual example of estimating PI using random numbers. You can experiment with how changing the sample size affects the accuracy

Split the Bills

Leverage Google's OR-tools to create a bill splitting application. This technique can be applied to a variety of optimization problems such as optimal routing.

Billynomics

An interactive view of the price of Ikea's classic BILLY bookcase across the world. A great introduction for how you can scrape data from the web.

Federal Government Spending and Income

Browse the US federal government's income and spending over the last 50 years