QS世界排名前200的大学都在哪里？Python动态图告诉你！

import numpy as np 
import pandas as pd 
import geopandas as gpd 
import shapely 
from shapely import geometry as geo 
from shapely import wkt 
import geopandas as gpd 
import matplotlib.pyplot as plt 
import matplotlib.animation as  animation 
import contextily as ctx 

import imageio
import os 
from PIL import Image

plt.rcParams['font.family'] = 'sans-serif'
plt.rcParams['font.sans-serif'] = ['SimHei']
plt.rcParams['axes.unicode_minus'] = False
plt.rcParams['animation.writer'] = 'html'
plt.rcParams['animation.embed_limit'] = 100

def rgba_to_rgb(img_rgba):
    img_rgb = Image.new("RGB", img_rgba.size, (255, 255, 255))
    img_rgb.paste(img_rgba, mask=img_rgba.split()[3]) 
    return img_rgb 

def html_to_gif(html_file, gif_file, duration=0.5):
    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]
    if frames[0].shape[-1]==4:
        frames = [np.array(rgba_to_rgb(Image.fromarray(x))) for x in frames]
    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

def getCoords(geom):
    if isinstance(geom,geo.MultiPolygon):
        return [np.array(g.exterior) for g in geom.geoms]
    elif isinstance(geom,geo.Polygon):
        return [np.array(geom.exterior)]
    elif isinstance(geom,geo.LineString):
        return [np.array(geom)]
    elif isinstance(geom,geo.MultiLineString):
        return [np.array(x) for x in list(geom.geoms)]
    else:
        raise Exception("geom must be one of [polygon,MultiPolygon,LineString,MultiLineString]!")

#底图数据
dfcoutries = gpd.read_file(gpd.datasets.get_path('naturalearth_lowres')).set_crs("epsg:4326")

#散点数据
dfpoints = gpd.read_file("./data/QS世界大学排名前200.geojson")
df = pd.DataFrame({"x":[pt.x for pt in dfpoints["geometry"]],
                  "y": [pt.y for pt in dfpoints["geometry"]]})

df["z"] = 1.0
df.index = dfpoints["name"].values

def bubble_map_dance(df,title = "QS世界排名前200大学分布",
                     filename = None,
                     figsize = (8,6),dpi = 144,
                     duration = 0.5,
                     anotate_points = []):

    fig, ax_base =plt.subplots(figsize=figsize,dpi=dpi)

    def plot_frame(i):
        ax_base.clear()

        #============================================================
        #绘制底图
        #============================================================

        dfcoutries.plot(ax=ax_base,color='white',edgecolor='gray',alpha = 0.5) 

        #设置绘图范围
        ax_base.set_xlim(-198.0, 198.00000000000009)
        ax_base.set_ylim(-98.68225649999998, 92.3273865)
        ax_base.axis("off")


        #============================================================
        #绘制散点
        #============================================================

        k = i//3+1
        m = i%3
        text = "NO."+str(len(df)+1-k) 

        dfdata = df.iloc[:k,:].copy()
        dftmp = df.iloc[:k-1,:].copy()

        # 绘制散点图像
        if len(dftmp)>0:
            ax_base.scatter(dftmp["x"],dftmp["y"],s = 40*dftmp["z"]/df["z"].mean(),
                   c = (cmap*100)[0:len(dftmp)],alpha = 0.4,zorder = 3)

            # 添加注释文字
            for i,p in enumerate(dftmp.index):
                px,py,pz = dftmp.loc[p,["x","y","z"]].tolist() 
                if p in anotate_points:
                    ax_base.annotate(p,xy = (px,py),  xycoords = "data",xytext = (-15,10),
                    fontsize = 10,fontweight = "bold",color = cmap[i], textcoords = "offset points")

        # 添加标题和排名序号
        ax_base.set_title(title,color = "black",fontsize = 12)
        #ax_base.text(0.5, 0.95, title, va="center", ha="center", 
        #            size = 12,transform = ax_base.transAxes)
        ax_base.text(0.17, 0.3, text, va="center", ha="center", 
                     alpha=0.4, size = 40,transform = ax_base.transAxes)

        # 添加注意力动画
        if m==0:
            px,py,pz = dfdata["x"][[-1]],dfdata["y"][[-1]],dfdata["z"][-1]
            p = dfdata.index[-1]
            ax_base.scatter(px,py,s = 200*pz/df["z"].mean(),
               c = cmap[len(dfdata)-1:len(dfdata)],alpha = 0.4,zorder = 4)
            ax_base.annotate(p,xy = (px,py),  xycoords = "data",
                    xytext = (-15,10),fontsize = 15,fontweight = "bold",
                    color = cmap[k-1], textcoords = "offset points",zorder = 5)

        if m==1:
            px,py,pz = dfdata["x"][[-1]],dfdata["y"][[-1]],dfdata["z"][-1]
            p = dfdata.index[-1]
            ax_base.scatter(px,py,s = 100*pz/df["z"].mean(),
               c = cmap[len(dfdata)-1:len(dfdata)],alpha = 0.4,zorder = 4)
            ax_base.annotate(p,xy = (px,py),  xycoords = "data",
                    xytext = (-15,10),fontsize = 12,fontweight = "bold",
                    color = cmap[k-1], textcoords = "offset points",zorder = 5)

        if m==2:
            px,py,pz = dfdata["x"][[-1]],dfdata["y"][[-1]],dfdata["z"][-1]
            p = dfdata.index[-1]
            ax_base.scatter(px,py,s = 40*pz/df["z"].mean(),
               c = cmap[len(dfdata)-1:len(dfdata)],alpha = 0.4,zorder = 4)
            ax_base.annotate(p,xy = (px,py),  xycoords = "data",
                    xytext = (-15,10),fontsize = 9,fontweight = "bold",
                    color = cmap[k-1], textcoords = "offset points",zorder = 5)
                
    my_animation = animation.FuncAnimation(fig,plot_frame,frames = range(0,3*len(df)),interval = int(duration*1000))
    
    if filename is None:
        try:
            from IPython.display import HTML
            HTML(my_animation.to_jshtml())
            return HTML(my_animation.to_jshtml())
        except ImportError:
            pass
    else:
        my_animation.save(filename)
        return filename
    

html_file = "QS世界排名前200大学分布.html"
bubble_map_dance(df,filename = html_file)

gif_file = html_file.replace(".html",".gif")
html_to_gif(html_file,gif_file,duration=0.5)