I have a question about the online version of the documentation.

If I change something in a ipynb file in doc/examples, after that I need to run make doc and commit changed htmls if I want to update the site too? (In that case I do not understand clearly what pages-build-deployment workflow do.)

All Animation has a main key (Data => "data", Config => "config") therefore it is quite straightforward to merge different animation in one Chart.animate call. Therefore Chart.animate can allow multiple animations until they do not override any data.

The *animations and **config can be merged with this strategy, too and the *args and **kwargs calls will lokk similar:

Chart().animate(config={...}, data={...})

Chart().animate(Config(...), Data(...))

ipyvizzu.Chart.animate() can not handle animoptions (like delay, duration etc.).

The JS API accepts the following arguments: animate({ data, config, style }, animoptions) animate(config, animoptions) animate({ data, config, style }) animate(config)

ipyvizzu's behavior do not need to be the same like the JS API, so it can be pythonic, but the functions have to work. (animoptions is a js object like a python dict, or in js api it can be a single string if only want to change the duration so '500ms' instead of {duration: '500ms'})

I think possible solutions in ipyvizzu are:

I. kwargs only be animoptions style, data and config only be Style, Data, Config classes in args (it is a further problem with this, Style(None) needs to work to reset previous style modifications, but now it is working only in kwargs style=None)

II. create az animOptions class, and handle it differently in _merge_animations()

III. any other idea

Usage:

cd tools/example-generator
npm intall
pip install -r requirements.txt
./run.sh

Sparse clones/checks out the vizzu-lib repo to the current folder. Generates ipynb files for each example file found in the vizzu-lib repo test/integration/test_cases/web_content/sample_static/*.mjs, test/integration/test_cases/web_content/templates/*.mjs into docs/examples/static, docs/examples/animated folders

This is a great library! Exactly the lib that I was looking for! Thank you! :1st_place_medal:

How to run the animation in the loop? Can I add controls for animation (stop, play)?

I'm working on a framework for converting Jupyter Notebooks to interactive web apps. Would love to use vizzu in demos. I will let you know, thanks!

If the notebook is running and the user scrolls, then auto scrolling should switch off for that run. It is inconvenient for the user that they couldn't scroll during running.

Something like this would be the solution:

global scope:

let inhibitScroll = false;
document.addEventListener('scroll', function(e) {
  inhibitScroll = true;
});

cell:

if (!inhibitScroll) myVizzu.scrollIntoView(...);

I don't how to set inhibitScroll back to false after running, but next run should do autoscrolling again.

…ptions

• [x] refactor Chart.animate

• [x] fix unit tests

• [x] add unit tests to anim options

• [x] fix examples

• [x] add examples to anim options

• [x] load data in the examples

The notebooks (ipynb) inculdes the markdown and code cells as list of lines. Editing the notebook is error prone therefore we should read the cells from separate assets.

A notebook

{                                                                                                                                                                                                                      
  "cells": [                                                                                 
    {                                                                                         
       "cell_type": "markdown",                                                              
       "id": "e582c95b",                                                                     
       "metadata": {},                                                                       
       "source": [                                                                           
          "## Aggregate/drill-down\n",                                                         
          "\n",                                                                                
          "These features basically mean that you add or remove an additional dimension to/from an axis or another channel. As you can see below, there are some important things to keep in mind when you use them.\n",
          "\n",                                                                                
          "Let’s stack together the elements by putting the Genres dimension from the x-axis to the y-axis. At the end of this phase, there are chart elements with the same color stacked on top of each other, which is something you would want to avoid. "
      ]                                                                                     
    }
  ]
}

would be split into a json and markdown/python files

{                                                                                                                                                                                                                      
  "cells": [                                                                                 
    {                                                                                         
      "cell_type": "markdown",                                                              
      "id": "e582c95b",                                                                     
      "metadata": {},                                                                       
      "source": {"@readlines": "aggregate.md"}
    }
  ]                                                                                     
}

## Aggregate/drill-down

These features basically mean that you add or remove an additional dimension to/from an axis or another channel. As you can see below, there are some important things to keep in mind when you use them.

Let’s stack together the elements by putting the Genres dimension from the x-axis to the y-axis. At the end of this phase, there are chart elements with the same color stacked on top of each other, which is something you would want to avoid.

The {"@readlines": "aggregate.md"} would be handle by a simple python script with the json.load object_hook. And the Makefile would genearte ipynb from the json template:

#!/usr/bin/env python3
"""
Replace `{"@readlines": "referred/file"}` object from the `json_file` with the
list of lines read from the referred file. The path of the referred file is
relative to the `json_file`.
"""

import argparse
import json
import sys
import pathlib


def main():
    args = _parse_args()
    reader = Reader(args.json_file.parent)

    with args.json_file.open() as fp:
        obj = json.load(fp, object_hook=reader.object_hook)

    json.dump(obj, fp=sys.stdout, indent=4, sort_keys=True)


def _parse_args():
    parser = argparse.ArgumentParser(
        description="Read files as list of lines into json", epilog=__doc__
    )
    parser.add_argument("json_file", type=pathlib.Path)

    return parser.parse_args()


class Reader:
    def __init__(self, source_dir):
        self._source_dir = source_dir

    def object_hook(self, obj):
        if len(obj) != 1:
            return obj

        try:
            path = obj["@readlines"]
        except KeyError:
            return obj

        file_name = self._source_dir / path

        with file_name.open() as fp:
            return fp.readlines()


if __name__ == "__main__":
    exit(main())

PyCharm is a popular Python IDE, it would be great to see if ipyvizzu and ipyvizzu-story work in it. Pic: Kaggle State of Data Science and Machine Learning Survey 2022

A conda install option could be very helpful. Adding ipyvizzu to conda-forge channel will be ideal.

Note: I have started working on this already in the following PR.

• https://github.com/conda-forge/staged-recipes/pull/19838

Once merged you will be able to install the library with:

conda install -c conda-forge ipyvizzu

Please put all content from the readme to the github pages index page (https://vizzuhq.github.io/ipyvizzu/index.html). Including a link to the github repo. See vizzu-lib for reference, where the repo readme is the same as the lib.vizzuhq.com index page. 2. Please create an ipyvizzu.vizzuhq.com subdomain and direct it to the ipyvizzu project's github pages site. 3. We have the ipyvizzu.com domain now, please redirect it to ipyvizzu.vizzuhq.com

Change the mkdocs theme to resemble the vizzu lib doc site https://lib.vizzuhq.com/0.4/

• [x] colors, font-sizes
• [x] add vizzu logo, favicon
• [x] syntax highlight
• [ ] add social logos/links

Please let me know if I'm misunderstanding some of how this works!

My current understanding is the documentation for updating Styles for charts is present in the JS Vizzu library, but not super clear for the ipyvizzu.

My PR #200 adds a small Style tweak, but I think a full tutorial on Style properties and how to change them could help a lot, especially to explain a little of how python users can leverage the js documentation to customize plots. If this seems valuable, I would be happy to take a shot of making such a notebook. If so - feel free to tag me as the Assignee, but if not or if this documentation already exists feel free to close 👍

This can be replicated by following the plots in the sorting tutorial notebook.

As you follow along, the second to last plot looks like this:

and the final plot looks like:

Here - I think ideally, the final plot would have multi-tiered x axis labels, as by default it is impossible to know what each of the Genre bars within a Kind represent.

Currently - Mac users cannot run any of the make commands for the repo - which forces repo maintainers to reformat code written by Mac users.

This applies to both ipyvizzu and ipyvizzu-story

Enable users to use Spark dataframe next to the currently available pandas dataframe. More info: https://spark.apache.org/docs/3.1.1/api/python/reference/api/pyspark.sql.DataFrame.html