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Description

ipyvizzu is the Jupyter Notebook integration of [Vizzu](https://github.com/vizzuhq/vizzu-lib). ipyvizzu enables data scientists and analysts to utilize animation for storytelling with data using Python.

Similar to Vizzu, which is a free, open-source Javascript/C++ library, ipyvizzu also utilizes a generic dataviz engine that generates many types of charts and seamlessly animates between them. It is designed for building animated data stories as it enables showing different perspectives of the data that the viewers can easily follow.

Main features: - Designed with animation in focus; - Defaults based on data visualization guidelines; - Works with Pandas dataframe, also JSON and inline data input is available; - Auto scrolling to keep the actual chart in position while executing multiple cells.

Programming language: Jupyter Notebook
License: Apache License 2.0
Latest version: v0.13.0

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README

ipyvizzu Build animated charts in many environments with a simple Python syntax Tutorial · Examples · Repository

PyPI version Conda Version CI-CD

About The Project

ipyvizzu is an animated charting tool for Jupyter, Google Colab, Databricks, Kaggle and Deepnote notebooks among other platforms. ipyvizzu enables data scientists and analysts to utilize animation for storytelling with data using Python. It's built on the open-source Javascript/C++ charting library Vizzu

There is a new extension of ipyvizzu, ipyvizzu-story with which the animated charts can be presented right from the notebooks. Since ipyvizzu-story's syntax is a bit different to ipyvizzu's, we suggest you to start from the ipyvizzu-story repo if you're interested in using animated charts to present your findings live or to share your presentation as an HTML file.

Similarly to Vizzu, ipyvizzu utilizes a generic dataviz engine that generates many types of charts and seamlessly animates between them. It is designed for building animated data stories as it enables showing different perspectives of the data that the viewers can easily follow.

Main features:

  • Designed with animation in focus;
  • Defaults based on data visualization guidelines;
  • Works with Pandas dataframe, while also JSON and inline data input is available;
  • Auto scrolling feature to keep the actual chart in position while executing multiple cells.

Installation

ipyvizzu requires the IPython, jsonschema and pandas packages.

pip install ipyvizzu

You can also use ipyvizzu by locally installing Vizzu, you can find more info about this in the documentation

Usage

You can create the animation below with the following code snippet.

import pandas as pd
from ipyvizzu import Chart, Data, Config

data_frame = pd.read_csv(
    "https://raw.githubusercontent.com/vizzuhq/ipyvizzu/main/docs/examples/stories/titanic/titanic.csv"
)
data = Data()
data.add_data_frame(data_frame)

chart = Chart(width="640px", height="360px")

chart.animate(data)

chart.animate(
    Config(
        {
            "x": "Count",
            "y": "Sex",
            "label": "Count",
            "title": "Passengers of the Titanic",
        }
    )
)
chart.animate(
    Config(
        {
            "x": ["Count", "Survived"],
            "label": ["Count", "Survived"],
            "color": "Survived",
        }
    )
)
chart.animate(Config({"x": "Count", "y": ["Sex", "Survived"]}))

Documentation

Visit our documentation site for more details and a step-by-step tutorial into ipyvizzu or check out our example gallery.

Tools Support

ipyvizzu can be used in a wide variety of environments. We prepared examples and the list of supported/unsupported features for the following platforms:

Extensions

  • ipyvizzu-story adds presentation controls to present data stories live or to share them as an interactive HTML file.

Contributing

We welcome contributions to the project, visit our contributing guide for further info.

Contact

License

Copyright © 2022 Vizzu Kft..

Released under the Apache 2.0 License.


*Note that all licence references and agreements mentioned in the ipyvizzu README section above are relevant to that project's source code only.