超动感，百行Python代码制作动态气泡图
先上图片：
再上视频：
最后上代码：
import numpy as np
import pandas as pd
from matplotlib import pyplot as plt
import matplotlib.animation as animation
import imageio
import os
import cv2
from PIL import Image
plt.rcParams['animation.writer'] = 'html'
plt.rcParams['font.sans-serif'] = ['SimHei']
plt.rcParams['axes.unicode_minus'] = False
def html_to_gif(html_file, gif_file, duration=0.1):
path = html_file.replace(".html","_frames")
images = [os.path.join(path,x) for x in sorted(os.listdir(path))]
frames = [imageio.imread(x) for x in images]
imageio.mimsave(gif_file, frames, 'gif', duration=duration)
return gif_file
cmap = [
'#2E91E5',
'#1CA71C',
'#DA16FF',
'#B68100',
'#EB663B',
'#00A08B',
'#FC0080',
'#6C7C32',
'#862A16',
'#620042',
'#DA60CA',
'#0D2A63']*100
dfx = pd.read_csv("./data/gdp_per_capita.csv")
dfx = dfx.set_index("year")
dfx.index = [str(x) for x in dfx.index]
dfx = dfx[sorted(dfx.columns)]
dfy = pd.read_csv("./data/life_expect.csv")
dfy = dfy.set_index("year")
dfy.index = [str(x) for x in dfy.index]
dfy = dfy[sorted(dfy.columns)]
dfz = pd.read_csv("./data/pop_amount.csv")
dfz = dfz.set_index("year")
dfz.index = [str(x) for x in dfz.index]
dfz = dfz[sorted(dfz.columns)]
def bubble_chart_race(dfx,dfy,dfz,title = "中国大陆各省市历年人均GDP和预期寿命变化",
filename = None,
figsize = (6.5,3.5),dpi = 144,
duration = 0.5,
xlabel = "人均GDP(人民币)",
ylabel = "预期寿命",
size_label = "点尺寸: 人口数量",
anotate_points = ["江西省","北京市","上海市","广东省",
"河南省","江苏省","黑龙江省","西藏自治区"]):
fig,ax = plt.subplots(figsize=figsize,dpi=dpi)
ax.set_facecolor("0.9")
ax.set_title(title,color = "black",fontsize = 12)
# 调整spines
ax.spines["top"].set_visible(False)
ax.spines["right"].set_visible(False)
ax.spines["left"].set_visible(False)
ax.spines["bottom"].set_visible(False)
def plot_frame(date):
dfdata = pd.DataFrame()
xdata = dfx.loc[date,:].sort_index()
ydata = dfy.loc[date,:].sort_index()
zdata = dfz.loc[date,:].sort_index()
dfdata["x"] = xdata
dfdata["y"] = ydata
dfdata["z"] = zdata
# 绘制散点图像
ax.clear()
ax.scatter(dfdata["x"],dfdata["y"],s = 100*dfdata["z"]/dfdata["z"].mean(),
c = (cmap*100)[0:len(dfdata)],alpha = 0.5)
# 添加图例文字
for i,p in enumerate(dfdata.index):
px,py,pz = dfdata.loc[p,["x","y","z"]].tolist()
if p in anotate_points:
ax.annotate(p,xy = (px,py), xycoords = "data",
xytext = (-15,10),fontsize = 10,fontweight = "bold",color = cmap[i], textcoords = "offset points")
ax.tick_params(bottom = False,left = False,labelsize = 8,direction = "in",length = 2)
# 调整绘图范围
xlim = (dfx.values.min(),dfx.values.max())
ax.set_xlim(left = xlim[0]-(xlim[1]-xlim[0])/10,right = xlim[1]+(xlim[1]-xlim[0])/10)
ylim = (dfy.values.min(),dfy.values.max())
ax.set_ylim(bottom = ylim[0]-(ylim[1]-ylim[0])/10,top = ylim[1]+(ylim[1]-ylim[0])/5)
# 添加辅助元素
ax.text(0.5, 0.5, date, va="center", ha="center",alpha=0.3, size = 50,transform = ax.transAxes)
ax.text(0.85, 0.92, size_label, ha="center",va="center", size = 10,transform = ax.transAxes)
ax.grid(axis = "x",color="white",lw=1,ls = "-")
ax.tick_params(bottom = False,left = False,labelsize = 8,direction = "in",length = 2)
ax.set_xlabel(xlabel,fontsize = 10)
ax.set_ylabel(ylabel,fontsize = 10)
bubble_animation = animation.FuncAnimation(fig,plot_frame,frames = dfx.index ,interval = int(duration*1000))
if filename is None:
try:
from IPython.display import HTML
return HTML(bubble_animation.to_jshtml())
except ImportError:
pass
else:
bubble_animation.save(filename)
return filename
html_file = "bubble_chart_race.html"
gif_file = html_file.replace(".html",".gif")
bubble_chart_race(dfx,dfy,dfz,filename = html_file,title = "中国大陆各省份历年人均GDP和预期寿命")
html_to_gif(html_file,gif_file,duration=1.0)
主要思路是构建plot_frame函数逐帧绘制图像，再用matplotlib的animation模块制作动画。
收工。????
打码不易，喜欢本篇的小伙伴，或者需要完整代码和绘图数据集的同学，可以对本文点赞，在看，和分享后在公众号“算法美食屋”后台回复关键字：动态图，添加作者微信获取。
万水千山总是情，点个在看行不行。。。????