Build animated charts in Jupyter Notebook and similar environments with a simple Python syntax.
APACHE-2.0 License
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:
Pandas
dataframe, while also JSON
and inline data input ispip install ipyvizzu
Visit Installation chapter for more options and details.
You can create the animation below with the following code snippet.
import pandas as pd
from ipyvizzu import Chart, Data, Config
df = pd.read_csv(
"https://ipyvizzu.vizzuhq.com/latest/showcases/titanic/titanic.csv"
)
data = Data()
data.add_df(df)
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"]}))
Visit our Documentation site for more
details and a step-by-step tutorial into ipyvizzu
or check out our
Example gallery.
ipyvizzu
can be used in a wide variety of environments, visit
Environments chapter for
more details.
We welcome contributions to the project, visit our contributing guide for further info.
ipyvizzu
collects aggregate usage statistics by default to follow the progress
and overall trends of our library. This feature is optional, and users can
choose to opt-out. However, we do not track, collect, or store any personal data
or personally identifiable information. Please note that even when this feature
is enabled, publishing anything made with ipyvizzu
remains GDPR compatible.
For more details, please visit
Analytics chapter.
Copyright © 2022-2023 Vizzu Inc.
Released under the Apache 2.0 License.