地图（三）利用python绘制等值区域地图

地图（三）利用python绘制等值区域地图

等值区域地图（Choropleth Map）简介

等值区域地图通过颜色区别地图上不同区域的变量，便于在空间上进行变量的比较。

快速绘制

1. 基于geopandas和geoplot

   import geopandas as gpd
   import geoplot as gplt
   
   # 导入数据
   geoData = gpd.read_file('https://raw.githubusercontent.com/holtzy/The-Python-Graph-Gallery/master/static/data/US-counties.geojson')
   # 删除Alaska、Hawaii、Puerto Rico.
   stateToRemove = ['02', '15', '72']
   geoData = geoData[~geoData.STATE.isin(stateToRemove)]
   geoData = geoData.explode(index_parts=True)
   
   # 外部轮廓
   gplt.polyplot(geoData, figsize=(20, 4));
   

   

   import pandas as pd
   import seaborn as sns
   
   # 读取美国失业率数据，用来作为区域的数值变量
   data = pd.read_csv('https://raw.githubusercontent.com/holtzy/The-Python-Graph-Gallery/master/static/data/unemployment-x.csv')
   
   # 匹配数据
   geoData['id'] = geoData['id'].astype('int64')
   fullData = geoData.merge(data, left_on=['id'], right_on=['id'])
   fullData.head()
   

   

   import matplotlib.pyplot as plt
   fig, ax = plt.subplots(1, 1, figsize=(16, 12))
   
   # 设置颜色方案
   import mapclassify as mc
   scheme = mc.Quantiles(fullData['rate'], k=10)
   
   # 绘制choropleth
   gplt.choropleth(fullData, 
       hue="rate", 
       linewidth=.1,
       scheme=scheme, cmap='inferno_r',
       legend=True,
       edgecolor='black',
       ax=ax
   );
   
   ax.set_title('Unemployment rate in US counties', fontsize=13);
   

   

2. 基于plotly

   import pandas as pd
   import matplotlib.pyplot as plt
   from urllib.request import urlopen
   import json
   import plotly.express as px
   
   # 导入数据
   df = pd.read_csv("https://raw.githubusercontent.com/plotly/datasets/master/fips-unemp-16.csv",
                      dtype={"fips": str})
   
   
   # 加载county的边界坐标
   with urlopen('https://raw.githubusercontent.com/plotly/datasets/master/geojson-counties-fips.json') as response:
       counties = json.load(response)
   
   # 绘制choropleth
   fig = px.choropleth(df, 
       geojson=counties, 
       locations='fips', 
       color='unemp',
       color_continuous_scale="Viridis",
       range_color=(0, 12),
       scope="usa",
       labels={'unemp':'unemployment rate'}
   )
   fig.update_layout(margin={"r":0,"t":0,"l":0,"b":0})
   
   # 修改图例
   fig.update_layout(coloraxis_colorbar=dict(
       thicknessmode="pixels", thickness=10,
       lenmode="pixels", len=150,
       yanchor="top", y=0.8,
       ticks="outside", ticksuffix=" %",
       dtick=5
   ))
   
   fig.show()
   

   

总结

以上利用geoplot和plotly快速绘制等值区域地图。

共勉～