中國88個(gè)超500萬人口的大中城市都在哪里？Python動(dòng)態(tài)圖告訴你！
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今日表情
我國的城市層次
除港澳臺(tái)外，中國一共有337個(gè)地級(jí)市(含4個(gè)直轄市)。一般綜合考慮城市人口規(guī)模和城市經(jīng)濟(jì)發(fā)展水平等因素，可以將城市分成一線、新一線、二線、三線、四線、五線等不同層次。
下面我們來看一份第一財(cái)經(jīng)新一線城市研究所發(fā)布的一份2021城市商業(yè)魅力排行榜城市層次榜單。
我國城市人口規(guī)模
如果僅僅考慮城市人口規(guī)模的話，根據(jù)最新人口普查公開數(shù)據(jù)，中國337個(gè)地級(jí)市當(dāng)中，一共有88個(gè)城市超過500萬個(gè)。它們是哪些城市呢？我們用Python動(dòng)態(tài)圖盤點(diǎn)一下吧！
先上圖片
再上視頻
最后上代碼
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]!")
#底圖數(shù)據(jù)
dfprovince = gpd.read_file("./data/dfprovince.geojson").set_crs("epsg:4326").to_crs("epsg:2343")
dfnanhai = gpd.read_file("./data/dfnanhai.geojson").set_crs("epsg:4326").to_crs("epsg:2343")
dfline9 = dfnanhai[(dfnanhai["LENGTH"]>1.0)&(dfnanhai["LENGTH"]<2.0)]
#散點(diǎn)數(shù)據(jù)
dfpoints = gpd.read_file("./data/china_big_cities.geojson").set_crs("epsg:4326").to_crs("epsg:2343")
dfpoints["point"] = dfpoints.representative_point()
dfpoints = dfpoints.query("population>=5000000")
df = pd.DataFrame({"x":[pt.x for pt in dfpoints["point"]],
"y": [pt.y for pt in dfpoints["point"]],
"z":[x for x in dfpoints["population"]]})
df.index = [x for x in dfpoints["city"]]
def bubble_map_dance(df,title = "中國超500萬人口城市",
filename = None,
figsize = (8,6),dpi = 144,
duration = 0.5,
anotate_points = ["北京市","上海市","重慶市","贛州市","沈陽市"]):
fig, ax_base =plt.subplots(figsize=figsize,dpi=dpi)
ax_child=fig.add_axes([0.800,0.125,0.10,0.20])
def plot_frame(i):
ax_base.clear()
ax_child.clear()
#============================================================
#繪制底圖
#============================================================
#繪制省邊界
polygons = [getCoords(x) for x in dfprovince["geometry"]]
for j,coords in enumerate(polygons):
for x in coords:
poly = plt.Polygon(x, fill=True, ec = "gray", fc = "white",alpha=0.5,linewidth=.8)
poly_child = plt.Polygon(x, fill=True, ec = "gray", fc = "white",alpha=0.5,linewidth=.8)
ax_base.add_patch(poly)
ax_child.add_patch(poly_child )
#繪制九段線
coords = [getCoords(x) for x in dfline9["geometry"]]
lines = [y for x in coords for y in x ]
for ln in lines:
x, y = np.transpose(ln)
line = plt.Line2D(x,y,color="gray",linestyle="-.",linewidth=1.5)
line_child = plt.Line2D(x,y,color="gray",linestyle="-.",linewidth=1.5)
ax_base.add_artist(line)
ax_child.add_artist(line_child)
#設(shè)置spine格式
for spine in['top','left',"bottom","right"]:
ax_base.spines[spine].set_color("none")
ax_child.spines[spine].set_alpha(0.5)
ax_base.axis("off")
#設(shè)置繪圖范圍
bounds = dfprovince.total_bounds
ax_base.set_xlim(bounds[0]-(bounds[2]-bounds[0])/10, bounds[2]+(bounds[2]-bounds[0])/10)
ax_base.set_ylim(bounds[1]+(bounds[3]-bounds[1])/3.5, bounds[3]+(bounds[3]-bounds[1])/100)
ax_child.set_xlim(bounds[2]-(bounds[2]-bounds[0])/2.5, bounds[2]-(bounds[2]-bounds[0])/20)
ax_child.set_ylim(bounds[1]-(bounds[3]-bounds[1])/20, bounds[1]+(bounds[3]-bounds[1])/2)
#移除坐標(biāo)軸刻度
ax_child.set_xticks([]);
ax_child.set_yticks([]);
#============================================================
#繪制散點(diǎn)
#============================================================
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()
# 繪制散點(diǎn)圖像
if len(dftmp)>0:
ax_base.scatter(dftmp["x"],dftmp["y"],s = 100*dftmp["z"]/df["z"].mean(),
c = (cmap*100)[0:len(dftmp)],alpha = 0.3,zorder = 3)
ax_child.scatter(dftmp["x"],dftmp["y"],s = 100*dftmp["z"]/df["z"].mean(),
c = (cmap*100)[0:len(dftmp)],alpha = 0.3,zorder = 3)
# 添加注釋文字
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")
# 添加標(biāo)題和排名序號(hào)
#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(0.5, 0.5, text, va="center", ha="center",
alpha=0.3, size = 50,transform = ax_base.transAxes)
# 添加注意力動(dòng)畫
if m==0:
px,py,pz = dfdata["x"][[-1]],dfdata["y"][[-1]],dfdata["z"][-1]
p = dfdata.index[-1]+":"+str(pz//10000)+"萬"
ax_base.scatter(px,py,s = 800*pz/df["z"].mean(),
c = cmap[len(dfdata)-1:len(dfdata)],alpha = 0.5,zorder = 4)
ax_base.annotate(p,xy = (px,py), xycoords = "data",
xytext = (-15,10),fontsize = 20,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]+":"+str(pz//10000)+"萬"
ax_base.scatter(px,py,s = 400*pz/df["z"].mean(),
c = cmap[len(dfdata)-1:len(dfdata)],alpha = 0.5,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==2:
px,py,pz = dfdata["x"][[-1]],dfdata["y"][[-1]],dfdata["z"][-1]
p = dfdata.index[-1]+":"+str(pz//10000)+"萬"
ax_base.scatter(px,py,s = 100*pz/df["z"].mean(),
c = cmap[len(dfdata)-1:len(dfdata)],alpha = 0.5,zorder = 4)
ax_base.annotate(p,xy = (px,py), xycoords = "data",
xytext = (-15,10),fontsize = 10,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 = "中國超500萬人口城市.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)
收工。
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