python matplotlib animation制作世界人口变动动画

主要利用animation 做了个世界人口动画，数据从网上下载的。做成json格式的。读入pandas。没有放数据，只是弄了4个国家的。图片的很多细节也没有设置。
代码如下：

# -*- coding: UTF-8 -*-
import pandas as pd
import numpy as np
from matplotlib import pyplot as plt
from matplotlib.animation import FuncAnimationplt.style.use("ggplot")
plt.rcParams['font.sans-serif'] = ['SimHei']
plt.rcParams['axes.unicode_minus'] = Falsedf = pd.read_json('{"year":{"59":1959,"58":1960,"57":1961,"56":1962,"55":1963,"54":1964,"53":1965,"52":1966,"51":1967,"50":1968,"49":1969,"48":1970,"47":1971,"46":1972,"45":1973,"44":1974,"43":1975,"42":1976,"41":1977,"40":1978,"39":1979,"38":1980,"37":1981,"36":1982,"35":1983,"34":1984,"33":1985,"32":1986,"31":1987,"30":1988,"29":1989,"28":1990,"27":1991,"26":1992,"25":1993,"24":1994,"23":1995,"22":1996,"21":1997,"20":1998,"19":1999,"18":2000,"17":2001,"16":2002,"15":2003,"14":2004,"13":2005,"12":2006,"11":2007,"10":2008,"9":2009,"8":2010,"7":2011,"6":2012,"5":2013,"4":2014,"3":2015,"2":2016,"1":2017,"0":2018},
"india":{"59":4.41,"58":4.51,"57":4.6,"56":4.69,"55":4.79,"54":4.89,"53":4.99,"52":5.1,"51":5.2,"50":5.32,"49":5.43,"48":5.55,"47":5.68,"46":5.81,"45":5.95,"44":6.09,"43":6.23,"42":6.38,"41":6.52,"40":6.67,"39":6.83,"38":6.99,"37":7.15,"36":7.32,"35":7.49,"34":7.67,"33":7.84,"32":8.02,"31":8.2,"30":8.37,"29":8.55,"28":8.73,"27":8.91,"26":9.09,"25":9.27,"24":9.46,"23":9.64,"22":9.82,"21":10.01,"20":10.19,"19":10.38,"18":10.57,"17":10.75,"16":10.93,"15":11.12,"14":11.3,"13":11.48,"12":11.65,"11":11.83,"10":12.01,"9":12.18,"8":12.34,"7":12.5,"6":12.66,"5":12.81,"4":12.96,"3":13.1,"2":13.25,"1":13.39,"0":13.53},
"china":{"59":6.55,"58":6.67,"57":6.6,"56":6.66,"55":6.82,"54":6.98,"53":7.15,"52":7.35,"51":7.55,"50":7.75,"49":7.96,"48":8.18,"47":8.41,"46":8.62,"45":8.82,"44":9.0,"43":9.16,"42":9.31,"41":9.43,"40":9.56,"39":9.69,"38":9.81,"37":9.94,"36":10.09,"35":10.23,"34":10.37,"33":10.51,"32":10.67,"31":10.84,"30":11.02,"29":11.19,"28":11.35,"27":11.51,"26":11.65,"25":11.78,"24":11.92,"23":12.05,"22":12.18,"21":12.3,"20":12.42,"19":12.53,"18":12.63,"17":12.72,"16":12.8,"15":12.88,"14":12.96,"13":13.04,"12":13.11,"11":13.18,"10":13.25,"9":13.31,"8":13.38,"7":13.44,"6":13.51,"5":13.57,"4":13.64,"3":13.71,"2":13.79,"1":13.86,"0":13.93},
"japan":{"59":0.92,"58":0.93,"57":0.95,"56":0.96,"55":0.97,"54":0.98,"53":0.99,"52":1.0,"51":1.01,"50":1.01,"49":1.03,"48":1.04,"47":1.06,"46":1.07,"45":1.08,"44":1.1,"43":1.12,"42":1.13,"41":1.14,"40":1.15,"39":1.16,"38":1.17,"37":1.18,"36":1.18,"35":1.19,"34":1.2,"33":1.21,"32":1.21,"31":1.22,"30":1.23,"29":1.23,"28":1.24,"27":1.24,"26":1.24,"25":1.25,"24":1.25,"23":1.25,"22":1.26,"21":1.26,"20":1.26,"19":1.27,"18":1.27,"17":1.27,"16":1.27,"15":1.28,"14":1.28,"13":1.28,"12":1.28,"11":1.28,"10":1.28,"9":1.28,"8":1.28,"7":1.28,"6":1.28,"5":1.27,"4":1.27,"3":1.27,"2":1.27,"1":1.27,"0":1.27},
"usa":{"59":1.78,"58":1.81,"57":1.84,"56":1.87,"55":1.89,"54":1.92,"53":1.94,"52":1.97,"51":1.99,"50":2.01,"49":2.03,"48":2.05,"47":2.08,"46":2.1,"45":2.12,"44":2.14,"43":2.16,"42":2.18,"41":2.2,"40":2.23,"39":2.25,"38":2.27,"37":2.29,"36":2.32,"35":2.34,"34":2.36,"33":2.38,"32":2.4,"31":2.42,"30":2.44,"29":2.47,"28":2.5,"27":2.53,"26":2.57,"25":2.6,"24":2.63,"23":2.66,"22":2.69,"21":2.73,"20":2.76,"19":2.79,"18":2.82,"17":2.85,"16":2.88,"15":2.9,"14":2.93,"13":2.96,"12":2.98,"11":3.01,"10":3.04,"9":3.07,"8":3.09,"7":3.12,"6":3.14,"5":3.16,"4":3.18,"3":3.21,"2":3.23,"1":3.25,"0":3.27}}')population = df.iloc[:, 1:5]
country = population.keys()
country = list(country)year = 3977 - df.iloc[:,0]
year.sort_values(ascending=False)fig, ax = plt.subplots()
y_pos = np.arange(len(country))
titleList = year.sort_values(ascending=False)ax.set_xlim(0, 16)
ax.set_yticks(y_pos)
ax.set_yticklabels(country)
ax.invert_yaxis()
ax.set_xlabel('population')def animate(i):if i < 60:ax.clear()ax.set_yticks(y_pos)ax.set_yticklabels(country)ax.set_xlim(0, 16)title = ax.text(7, 3, str(titleList[i]), fontsize = 18)###关键是这一步pop = df.iloc[i, 1:5]rects = ax.barh(y_pos, pop, color = ['maroon', 'olive', 'teal', 'purple'])return rectsani = FuncAnimation(fig, animate)ani.save('population.gif',writer='pillow')

最后做成gif如图：

主要代码参考了stackoverflow里的。

https://stackoverflow.com/questions/56063390/how-do-i-update-the-title-and-data-of-a-matplotlib-bar-chart-animation/56065311?r=SearchResults#56065311

python matplotlib animation制作世界人口变动动画相关推荐

Python + matplotlib.animation 模拟斜抛运动动画（含完整代码）
提示:文章写完后,目录可以自动生成,如何生成可参考右边的帮助文档文章目录 Abstract Introduction Matplotlib.animation Physics model and C ...
Python入门：制作世界人口地图
来源:<Python编程:从入门到实践> 目录第 16 章下载数据 16.1 CSV文件格式 16.1.1 分析CSV文件头 16.1.2 打印文件头及其位置 16.1.3 提取并读取 ...
用Animation制作简单的物体动画
** 用Animation制作简单的物体动画 ** 大家好,今天来记录一下制作简单物体动画的教程. 1.首先打开窗口(Window)-动画(Animation)-动画(Animation) 2.选中需 ...
Python对JSON文件世界人口数据进行可视化
制作世界人口地图,用json模块来处理,将人口数据进行可视化!!! 下载JSON格式的人口数据,下面附上完整的,在网站中https://datahub.io/下载的数据集的详细过程!!! 1.下载世界 ...
【收藏】如何优雅的在 Python matplotlib 中制作平滑线/趋势线
有时候需要在绘制曲线的时候,绘制一条趋势线,如下图,这种如何实现呢,请看下文. 数据如下趋势计算代码有两个输入第一个输入是一个待平滑的数值数组, 第二个输入是权重,越大越平滑 # weight ...
Python 动图、动画制作 —— moviepy、matplotlib.animation
进入命令行界面(windows ⇒ cmd),下载安装,pip install moviepy 0. figure 的成员函数 # 创建 figure fig, ax = plt.subplots() ...
如何用python制作动画_如何基于Python Matplotlib实现网格动画
-1- 如果你对本文的代码感兴趣,可以去 Github (文末提供)里查看.第一次运行的时候会报一个错误(还没找到解决办法),不过只要再运行一次就正常了. 这篇文章虽然不是篇典型的数据科学类文章,不过 ...
编程python如何制作动画_用Python Matplotlib 制作动画
前言本文的文字及图片来源于网络,仅供学习.交流使用,不具有任何商业用途,版权归原作者所有,如有问题请及时联系我们以作处理. 作者:Hanz - 1 - 如果你对本文的代码感兴趣,可以去 Github ...
Python+Matplotlib制作动画
转载自:https://www.cnblogs.com/endlesscoding/p/10308111.html 看到一篇觉得非常不错的Python+Matplotlib制作动画的方法

python matplotlib animation制作世界人口变动动画

python matplotlib animation制作世界人口变动动画

python matplotlib animation制作世界人口变动动画相关推荐

最新文章

热门文章