如何用Python畫出好看的地圖

• folium
• Plotly
• GeoPandas+Matplotlib

1import?folium
2import?pandas?as?pd
3#輸入上海經(jīng)緯度，尺度
4latitude?=?31.2
5longitude?=?121.5
6sh_map?=?folium.Map(location=[latitude,?longitude],?zoom_start=10)
7sh_map

1sh_map?=?folium.Map(location=[latitude,?longitude],?zoom_start=10,tiles='Stamen?Toner')
2sh_map

 1#?創(chuàng)建特征組
 2hotpots?=?folium.map.FeatureGroup()
 3#?Loop?through?the?200?crimes?and?add?each?to?the?incidents?feature?group
 4for?lat,?lng,?in?zip(data.lat,?data.lon):
 5????hotpots.add_child(
 6????????folium.CircleMarker(
 7????????????[lat,?lng],
 8????????????radius=7,?#?define?how?big?you?want?the?circle?markers?to?be
 9????????????color='yellow',
10????????????fill=True,
11????????????fill_color='red',
12????????????fill_opacity=0.4
13????????)
14????)
15
16#?把火鍋特征組放到上海地圖上
17sh_map?=folium.Map(location=[latitude,?longitude],?zoom_start=10)
18sh_map.add_child(hotpots)

1latitudes?=?list(datas.lat)
2longitudes?=?list(datas.lon)
3labels?=?list(datas.name)
4for?lat,?lng,?label?in?zip(latitudes,?longitudes,?labels):
5????folium.Marker([lat,?lng],?popup=label).add_to(sh_map)??????
6sh_map

1hots=data.groupby('adname',as_index=False).agg({'name':"count"})
2hots.columns=['district','num']
3hots

 1#輸入上海經(jīng)緯度，尺度
 2latitude?=?31.2
 3longitude?=?121.5
 4map?=?folium.Map(location=[latitude,?longitude],?zoom_start=12)
 5folium.Choropleth(
 6????geo_data=geo_data,
 7????data=hots,
 8????columns=['district','num'],
 9????key_on='feature.properties.name',
10????#fill_color='red',
11????fill_color='YlOrRd',
12????fill_opacity=0.7,
13????line_opacity=0.2,
14????highlight=True,
15????legend_name='Hotpot?Counts?in?Shanghai'
16).add_to(map)
17map

 1import?plotly.express?as?px
 2import?plotly.graph_objs?as?go
 3latitude?=?31.2
 4longitude?=?121.5
 5fig?=?px.choropleth_mapbox(
 6????data_frame=hots,
 7????geojson=geo_data,
 8????color='num',
 9????locations="district",
10????featureidkey="properties.name",
11????mapbox_style="carto-positron",
12????color_continuous_scale='viridis',
13????center={"lat":?latitude,?"lon":?longitude},
14????zoom=7.5,
15)
16fig.update_layout(margin={"r":0,"t":0,"l":0,"b":0})
17fig.show()

 1import?matplotlib.pyplot?as?plt
 2import?matplotlib?as?mpl
 3#?中文和負(fù)號(hào)的正常顯示
 4mpl.rcParams['font.sans-serif']?=?['Times?New?Roman']
 5mpl.rcParams['font.sans-serif']?=?[u'SimHei']
 6mpl.rcParams['axes.unicode_minus']?=?False
 7#?裁剪上海shape
 8fig,?ax?=?plt.subplots(figsize=(20,?10))
 9ax=geo_data.plot(ax=ax,facecolor='grey',edgecolor='white',linestyle='--',alpha=0.8)
10ax.axis('off')?#?移除坐標(biāo)軸

1need_data=pd.merge(geo_data,hots[['district','num']],left_on='name',
2?????????????????right_on='district')
3need_data

1need_data?=?gpd.GeoDataFrame(need_data)
2need_data.geom_type

1fig,?ax?=?plt.subplots(figsize=(20,?10))
2need_data.plot('num',?cmap='OrRd',ax=ax)
3ax.axis('off')?#?移除坐標(biāo)軸
4cmap?=?mpl.cm.get_cmap('OrRd')
5norm?=?mpl.colors.Normalize(min(need_data['num']),?max(need_data['num']))
6fcb?=?fig.colorbar(mpl.cm.ScalarMappable(norm=norm,?cmap=cmap),ax=ax)
7ax=geo_data.plot(ax=ax,facecolor='grey',edgecolor='white',linestyle='--',alpha=0.2)
8ax.set_title('Hotpot?Count?in?Shanghai',?fontsize=20)

 1fig,?ax?=?plt.subplots(figsize=(20,?10))
 2need_data.plot('num',?cmap='OrRd',ax=ax)
 3for?idx,?_?in?enumerate(need_data.geometry.representative_point()):
 4????#?提取行政區(qū)名稱
 5????region?=?need_data.loc[idx,?'name']
 6????ax.text(_.x,?_.y,?region,?ha="center",?va="center",?size=8)
 7ax.axis('off')?#?移除坐標(biāo)軸
 8cmap?=?mpl.cm.get_cmap('OrRd')
 9norm?=?mpl.colors.Normalize(min(need_data['num']),?max(need_data['num']))
10fcb?=?fig.colorbar(mpl.cm.ScalarMappable(norm=norm,?cmap=cmap),ax=ax)
11ax=geo_data.plot(ax=ax,facecolor='grey',edgecolor='white',linestyle='--',alpha=0.2)
12ax.set_title('Hotpot?Count?in?Shanghai',?fontsize=20)

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