:tomato: Plost

A deceptively simple plotting library for Streamlit.

Because you've been writing plots wrong all this time.

👇 THE REAL README IS ACTUALLY HERE:

👆 You can find interactive examples, documentation, and much more in the app above.

Our goal

• What you need 99% of the time is insanely easy
• The other 1% is impossible. Use Vega-Lite instead!

Getting started

pip install plost

Basics

Plost makes it easy to build common plots using the Vega-Lite library but without having to delve into Vega-Lite specs (unless you're doing something tricky), and without having to melt your DataFrame from long format to wide format (the bane of most Vega-Lite plots!)

For example, let's say you have a "long-format" table like this:

Then you can draw a line chart by simply calling line_chart() with some column names:

import plost

plost.line_chart(
  my_dataframe,
  x='time',  # The name of the column to use for the x axis.
  y='stock_value',  # The name of the column to use for the data itself.
  color='stock_name', # The name of the column to use for the line colors.
)

Simple enough! But what if you instead have a "wide-format" table like this, which is super common in reality:

Normally you'd have to melt() the table with Pandas first or create a complex Vega-Lite layered plot. But with Plost, you can just specify what you're trying to accomplish and it will melt the data internally for you:

import plost

plost.line_chart(
  my_dataframe,
  x='time',
  y=('stock1', 'stock2'),  # 👈 This is magic!
)

Ok, now let's add a mini-map to make panning/zooming even easier:

import plost

plost.line_chart(
  my_dataframe,
  x='time',
  y=('stock1', 'stock2'),
  pan_zoom='minimap',  # 👈 This is magic!
)

But we're just scratching the surface. Basically the idea is that Plost allows you to make beautiful Vega-Lite-driven charts for your most common needs, without having to learn about the powerful yet complex language behind Vega-Lite.

Check out the the sample app / docs for a taste of other amazing things you can do!

Juicy examples

Check out the documentation app!

Documentation

This is in the documentation app too!