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Mercury/mljar

Features

The features of ipyvizzu that are available in Mercury/mljar are marked with a green check.

  • Change the url of Vizzu (vizzu)
  • Change the width of the Chart (width)
  • Change the height of the Chart (height)
  • Use scroll into view (scroll_into_view=True)

Dislay features:

  • Display all animations after _repr_html_ method called (display=DisplayTarget.MANUAL)
  • Display all animations after show method called (display=DisplayTarget.MANUAL)
  • Automatically display all animations after the first cell (display=DisplayTarget.BEGIN)
  • Automatically display all animations after the currently running cell (display=DisplayTarget.ACTUAL)
  • Automatically display all animations after the last running cell (display=DisplayTarget.END)
  • Rerun any cell without rerun the first cell (display!=DisplayTarget.MANUAL)

Check Chart settings chapter for more details.

Live example

Open in Mercury

Installation

Add ipyvizzu to requirements.txt.

python-dotenv
pandas
mljar-mercury
ipyvizzu

Sample

Try ipyvizzu in Mercury/mljar with the following sample.

# configure application

---
title: ipyvizzu demo
description: ipyvizzu mercury demo
show-code: False
params:
params:
    gender:
        input: select
        label: select the gender
        choices: [male, female]
        multi: False
---
# configure default choice

gender = "male"
# import pandas and ipyvizzu

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


# initialize Chart

chart = Chart(
    width="640px", height="360px"
)  # or Chart(width="640px", height="360px", display=DisplayTarget.ACTUAL)
# chart = Chart(width="640px", height="360px", display=DisplayTarget.BEGIN)
# chart = Chart(width="640px", height="360px", display=DisplayTarget.END)
# chart = Chart(width="640px", height="360px", display=DisplayTarget.MANUAL)


# add data to Chart

data = Data()
data_frame = pd.read_csv(
    "https://ipyvizzu.vizzuhq.com/0.15/showcases/titanic/titanic.csv"
)
data.add_data_frame(data_frame)

chart.animate(data)


# add config to Chart

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"]}))


# add style to Chart

chart.animate(Style({"title": {"fontSize": 35}}))


# filter data by the selected gender to Chart

data_filter = Data.filter(f"record['Sex'] == '{gender}'")
chart.animate(data_filter)


# display Chart with show method (display=DisplayTarget.MANUAL)

# chart.show()

Check the Tutorial for more info.