codeplot 0.1.0

codeplot is a canvas designed for code-driven data exploration where you can plot graphs, data frames, markdown and much more using plain Python

Docs · Getting Started · Discord

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codeplot is a dynamic spatial canvas for data exploration, offering an interactive environment for graphing and visualizing data with Python.

Created by @antl3x, read more about its inception.

Why Choose codeplot?

• Dynamic Visualization: Break free from static images and rigid layouts. codeplot brings your data to life on an interactive canvas.

• Easy Integration: Directly plot from your Python code or REPL into your canvas at codeplot.co.

• Varied Visualizations: From basic charts to advanced widgets, codeplot supports a wide range of data representations.

• Flexible Layouts: Arrange your visualizations to suit your workflow, with draggable and movable plots.

• Open to Everyone: Designed for data scientists and enthusiasts alike, codeplot aims to enhance your data exploration experience.

Getting Started (Python SDK)

To get started with codeplot, you can install the package using pip:

pip install codeplot

Once installed, you can start using codeplot by importing the package and connectig to a new room:

import asyncio
import codeplot

async def main():
    cP = await codeplot.connect("ws://your-ws-url/your-room-id")

    # Now you can start plotting
    await cP.plot(df.describe())
    await cP.plot(df.head(10))
    await cP.plot(df)

asyncio.run(main())

You can use the public codeplot client & server to start plotting right away:

1. Join the codeplot room at codeplot.co
2. Use the room id to connect to the room using the code above

If you want to use codeplot in a Jupyter Notebook, you can use the following code:

import codeplot
cP = await codeplot.connect("ws://your-ws-url/your-room-id")

# Now you can start plotting
await cP.plot(df.describe())
await cP.plot(df.head(10))
await cP.plot(df)

Run Codeplot on Docker

Instead of using the public codeplot server, you can self-host and run codeplot on your local machine using Docker. To do so, you can use the following command:

docker run -p 9107:9107 -p 9108:9108 codeplot/codeplot

This will start a codeplot server and a client on your local machine, and you can access it at:

• Client: http://localhost:9107
• Server: ws://localhost:9108

Join the codeplot Community

Become part of a forward-thinking community dedicated to advancing data visualization. Connect, engage, and grow with peers on Discord. With codeplot, data visualization is a shared journey. Let's explore new insights together!