Create stunning visual animations, ipyvizzu, a Python visualization library, is indispensable

Today, I will introduce a visualization module to you. You can use it to draw amazing animation effects. Of course, the first step is to install this module. Like to remember to collect, follow, like.

Install from the pipcommand line

pip install ipyvizzu

A small test

Note: The full version of the code, data, and technical exchange can be obtained at the end of the article.

Let's first simply use this module to draw a moving image and Pandasimport the data set. The code is as follows

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

data_frame = pd.read_csv("titanic.csv")

After importing the dataset, let me introduce the general steps of using this module. We instantiate the Data()object, and then place the imported dataset in it. The code is as follows

data = Data()
data.add_data_frame(data_frame)

Then we instantiate the chart object Chart()and place the data set in datait

chart = Chart()
chart.animate(data)

Next, we start to draw the chart. We need to specify some properties of the chart. For example, for a histogram, it is what data should be placed on the X-axis and Y-axis, whether the color selection is the default or needs to be specified, and the title, etc.

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

output

Then we add the following code on this basis,

chart.animate(Config({
    
    "x": ["Count","Survived"], "label": ["Count","Survived"], "color": "Survived"}))

output

Therefore, the so-called animation drawn by this module is actually the superposition of several static charts. Let's take a look at the complete case.

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

data_frame = pd.read_csv("titanic.csv")
data = Data()
data.add_data_frame(data_frame)

chart = Chart()
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"]}))

output

Animated transition between scatter plot and histogram

Due to the limited space, it is unlikely that the editor will finish this knowledge point at one time. Readers can check it out on the official website. githubThe address is: https://github.com/vizzuhq/ipyvizzu/tree/main

Here, the editor tries to draw the transition between the scatter chart and the histogram. The first is to draw the scatter chart. The code is as follows

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

data_frame = pd.read_csv("chart_types_eu.csv", dtype={
    
    "Year": str})
data = Data()
data.add_data_frame(data_frame)

chart = Chart()
chart.animate(data)

chart.animate(
    Config(
        {
    
    
            "channels": {
    
    
                "x": ["Joy factors", "Value 6 (+/-)"],
                "y": "Value 5 (+/-)",
                "color": "Joy factors",
                "size": "Value 2 (+)",
                "label": "Country_code",
            },
            "title": "Bubble Plot",
            "geometry": "circle",
        }
    )
)

output

We titleset the title through the parameters, sizethe size of colorthe scatter points and the color of the scatter points are set by the parameters, then we will draw the histogram, the code is as follows

chart.animate(
    Config(
        {
    
    
            "channels": {
    
    
                "y": "Joy factors",
                "x": ["Value 2 (+)", "Country_code"],
                "label": None
            },
            "title": "Bar Chart",
            "geometry": "rectangle",
            "orientation": "vertical",
        }
    ),
    geometry={
    
    "delay": 0.7, "duration": 1},
)

output

Then we mark the histogram with the following code

chart.animate(
    Config(
        {
    
    "channels": {
    
    "x": {
    
    "set": ["Value 2 (+)"]}, "label": {
    
    "set": ["Value 2 (+)"]}}}
    )
)

Let's take a look at the overall effect of the animation, as shown in the following figure

Whether it is static chart or dynamic, there are many other cases, you can refer to the following link for details: https://vizzuhq.github.io/ipyvizzu/examples/examples.html

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