plot(x=None, y=None, kind='line', ax=None, subplots=False, sharex=None, sharey=False, layout=None, figsize=None, use_index=True, title=None, grid=None, legend=True, style=None, logx=False, logy=False, loglog=False, xticks=None, yticks=None, xlim=None, ylim=None, rot=None, ...
regions.plot(ax=ax, column='name',legend=False, cmap='Pastel1_r', edgecolor='k') # # 地图标注 # for n, i in enumerate(regions['coords']): # plt.text(i[0]-0.15, i[1], regions['name'][n], fontsize=8, horizontalalignment="left") # 标注位置X,Y,标注内容 # 地图点标注 pts....
ax=data.plot(column="childrenNum",categorical=True,# 以数值分类的方式展示legend=True,cmap="tab20",# 对于分类数据,fmt设置无用legend_kwds={"loc":"center left","bbox_to_anchor":(1,0.5),"fmt":"{:.0f}"},)# 显示各地级市包含区县数量forindexindata.index:x=data.iloc[index].geometry.ce...
trips=mpd.ObservationGapSplitter(passenger).split(gap=timedelta(minutes=5))trips.plot() <Axes: > step3 感兴趣区域分析 我们可以确定一个感兴趣区域,如海事局。然后分析离开或达到该区域的船只时间和类型。 # 对于单个轨迹,如果其两个连续观测超过间隔gap,如5分钟,则认为该轨迹需要拆分为trips=mpd.ObservationG...
默认为Falselegend:bool型,设置是否显示图例,默认为Truescheme:字符型,同plot()中的同名参数,用于设定分层设色规则,参考我的过往文章:https://www.cnblogs.com/feffery/p/12381322.htmlk:int型,用于设置分层设色分段数量,默认为5vmin:float型,用于手动设置色彩映射最小值vmax:float型,用于手动设置色彩映射最大值...
world_data.plot(column='GDP per capita', cmap='OrRd', linewidth=0.8, ax=ax, edgecolor='0.8', legend=True) ax.set_title('World GDP per Capita') plt.show() 14. 分析结果 通过上述代码,我们可以得到世界各国的人均GDP地图,从中可以看出不同国家之间的经济发展水平差异。接下来,我们可以进一步分析...
# 绘制轨迹, column指定轨迹对象,legend展示轨迹持续时间 import as cm tc.plot(column='trajectory_id', legend=True) 1. 2. 3. <Axes: > 1. # 交互式展示轨迹 # tc.hvplot() 1. 2. 此外我们还可以从TrajectoryCollection提取单个轨迹,或者筛选所需要的轨迹。
ax = data.plot( column="childrenNum", categorical=True, # 以数值分类的方式展示 legend=True, cmap="tab20", # 对于分类数据,fmt设置无用 legend_kwds={"loc": "center left", "bbox_to_anchor": (1, 0.5), "fmt": "{:.0f}"}, ) # 显示各地级市包含区县数量 for index in data.index...
ax = data.plot( column="childrenNum", scheme="QUANTILES", # 设置分层设色标准 edgecolor='lightgrey', k=7, # 分级数量 cmap="Blues", legend=True, # 通过fmt设置位数 legend_kwds={"loc": "center left", "bbox_to_anchor": (1, 0.5),"fmt": "{:.2f}"} ...
"department_id","department_name","location_id" "1","Administration","1700" "2","Marketing","1800" "3","Purchasing","1700" "4","Human Resources","2400" "5","Shipping","1500" "6","IT","1400" "7","Public Relations","2700" ...