四种做动态数据可视化的方法

1. 柱状图动态可视化

转载教程 https://www.bilibili.com/video/av28087807/

开源代码 https://github.com/Jannchie/Historical-ranking-data-visualization-based-on-d3.js

2. Python画图+GIF

https://www.zhihu.com/question/302105116 第一个答复

用Python生成数据动图的体验版代码
链接:https://pan.baidu.com/s/1VXh7BPT4JrEOX5csdNyRxw  密码:b2wo

3. Python animation

https://towardsdatascience.com/bar-chart-race-in-python-with-matplotlib-8e687a5c8a41

import pandas as pd
import matplotlib.pyplot as plt
import matplotlib.ticker as ticker
import matplotlib.animation as animation
from IPython.display import HTML

df = pd.read_csv('https://gist.githubusercontent.com/johnburnmurdoch/4199dbe55095c3e13de8d5b2e5e5307a/raw/fa018b25c24b7b5f47fd0568937ff6c04e384786/city_populations', 
                 usecols=['name', 'group', 'year', 'value'])

fig, ax = plt.subplots(figsize=(15, 8))
def draw_barchart(year):
    dff = df[df['year'].eq(year)].sort_values(by='value', ascending=True).tail(10)
    ax.clear()
    ax.barh(dff['name'], dff['value'], color=[colors[group_lk[x]] for x in dff['name']])
    dx = dff['value'].max() / 200
    for i, (value, name) in enumerate(zip(dff['value'], dff['name'])):
        ax.text(value-dx, i,     name,           size=14, weight=600, ha='right', va='bottom')
        ax.text(value-dx, i-.25, group_lk[name], size=10, color='#444444', ha='right', va='baseline')
        ax.text(value+dx, i,     f'{value:,.0f}',  size=14, ha='left',  va='center')
    # ... polished styles
    ax.text(1, 0.4, year, transform=ax.transAxes, color='#777777', size=46, ha='right', weight=800)
    ax.text(0, 1.06, 'Population (thousands)', transform=ax.transAxes, size=12, color='#777777')
    ax.xaxis.set_major_formatter(ticker.StrMethodFormatter('{x:,.0f}'))
    ax.xaxis.set_ticks_position('top')
    ax.tick_params(axis='x', colors='#777777', labelsize=12)
    ax.set_yticks([])
    ax.margins(0, 0.01)
    ax.grid(which='major', axis='x', linestyle='-')
    ax.set_axisbelow(True)
    ax.text(0, 1.12, 'The most populous cities in the world from 1500 to 2018',
            transform=ax.transAxes, size=24, weight=600, ha='left')
#     ax.text(1, 0, 'by @pratapvardhan; credit @jburnmurdoch', transform=ax.transAxes, ha='right',
#             color='#777777', bbox=dict(facecolor='white', alpha=0.8, edgecolor='white'))
    plt.box(False)
    
import matplotlib.animation as animation
from IPython.display import HTML
fig, ax = plt.subplots(figsize=(15, 8))
animator = animation.FuncAnimation(fig, draw_barchart, frames=range(1968, 2019))
HTML(animator.to_jshtml()) 
# or use animator.to_html5_video() or animator.save()

python 动图尝试

 

4. R语言

https://rdrr.io/cran/processanimateR/

https://github.com/bupaverse/processanimateR

 

流程图（不太相关）

https://blog.csdn.net/weixin_41916005/article/details/80482609

 https://blog.csdn.net/mouday/article/details/80903408

 

啥时候能学会啊？？？