append_axes("right", size="5%", pad=0.1) df = gpd.read_file(gpd.datasets.get_path('naturalearth_lowres')) df.plot(kind="geo",column = "gdp_md_est",legend=True,ax = ax,cax = cax ) 代码语言:javascript 代码运行次数:0 运行 AI代码解释 #属性图考虑缺失值 df = gpd.read_file(...
random.normal(loc=loc, scale=scale, size=[10, 2]).tolist()) for loc, scale in contents] geo_df.set_geometry('raw_points', inplace=True) # inplace=True表示对原数据进行更新 # 绘制第一图层 ax = geo_df.plot(color='red') geo_df['convex_hull'] = geo_df.convex_hull # 切换矢量...
df, geometry=gpd.points_from_xy(df.Longitude, df.Latitude), crs="EPSG:4326" ) gdf # 在南美地图上展示 world = gpd.read_file(gpd.datasets.get_path("naturalearth_lowres")) # 定位到南美 ax = world.cx[-90:-55, -25:15].plot(color="white", edgecolor="black") #在ax区域上绘制地图 ...
divider =make_axes_locatable(ax)#设置图例,right表示位置,size=5%表示图例宽度,pad表示图例离图片间距cax = divider.append_axes("right", size="5%", pad=0.2)#绘制基于人口估计值的分区统计图world.plot(column='POP_EST', legend=True, cmap='viridis',cax=cax,ax=ax)else:print("The 'POP_EST' col...
Points 对应shapely.geometry中的Point,用于表示单个点,下面我们创建一个由若干Point对象组成的GeoSeries并像Series一样定义索引: 代码语言:javascript 代码运行次数:0 运行 AI代码解释 from shapelyimportgeometryimportgeopandasasgpd # 创建存放Point对象的GeoSeries ...
points = points.to_crs(32619) # 计算点之间的距离,距离单位为坐标系的单位 distance_meters = points[0].distance(points[1]) distance_meters 1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 84698.53985065906 1. nybb = nybb.to_crs(4326) ax = nybb.plot() ...
fig, ax=plt.subplots(1,1)divider=make_axes_locatable(ax)cax=divider.append_axes("right",size="5%",pad=0.1)world.plot(column='pop_est',ax=ax,legend=True,cax=cax) 图片果然变得好看了呢,Sci风! 还可以将颜色条放在下面,并且设置颜色条的名称 ...
points_with_boundary.head(1)#boundary到属性就被赋予到points中 4.数据可视化 加plot()即可,主要参数设置和matplotlib相同 演示,将 #给边界添加一行数据,用来可视化importnumpyasnpboundary["value"]=np.random.randint(20,size=len(boundary))boundaryboundary.plot(column='value',cmap='YlGn',edgecolor='k',li...
ax.text(x, y, label, fontsize=12, ha='right') # 在每个点旁边添加标签,字体大小为12,水平对齐方式为右对齐 # 自定义图例处理器,设置图例项的颜色和标签 handles = [Patch(color='cyan', label='Original Points'), Patch(color='yellow', alpha=0.5, edgecolor='red', label='Buffer Zones')] ...
ax = china.plot(figsize=(15,12), color="whitesmoke", edgecolor="lightgrey", linewidth=0.5) texts =[] forx, y, labelinzip(china_points.geometry.x, china_points.geometry.y, china_points["name"]): texts.append(plt.text(x, y, label, fontsize=8)) ...