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使用Folium绘图

什么是Folium?

Folium 建立在 Python 生态系统的数据处理优势和 leaflet.js 库的映射优势之上。这使您能够在 Geopandas 中处理数据，并通过 Folium 以 Leaflet 地图的形式进行可视化。

在这个例子中，我们将首先使用 Geopandas 加载几何图形（火山点数据），然后创建一个 Folium 地图，标记表示不同类型的火山。

加载几何

这个例子使用了一个可自由获取的 火山数据集。我们将使用pandas读取csv文件，然后将pandas DataFrame 转换为Geopandas GeoDataFrame。

# Import Libraries
import pandas as pd
import geopandas
import folium
import geodatasets
import matplotlib.pyplot as plt

df1 = pd.read_csv("volcano_data_2010.csv")

# Keep only relevant columns
df = df1.loc[:, ("Year", "Name", "Country", "Latitude", "Longitude", "Type")]
df.info()

<class 'pandas.core.frame.DataFrame'>
RangeIndex: 63 entries, 0 to 62
Data columns (total 6 columns):
 #   Column     Non-Null Count  Dtype
---  ------     --------------  -----
 0   Year       63 non-null     int64
 1   Name       63 non-null     object
 2   Country    63 non-null     object
 3   Latitude   63 non-null     float64
 4   Longitude  63 non-null     float64
 5   Type       63 non-null     object
dtypes: float64(2), int64(1), object(3)
memory usage: 3.1+ KB

# Create point geometries
geometry = geopandas.points_from_xy(df.Longitude, df.Latitude)
geo_df = geopandas.GeoDataFrame(
    df[["Year", "Name", "Country", "Latitude", "Longitude", "Type"]], geometry=geometry
)

geo_df.head()

	年份	名称	国家	纬度	经度	类型	几何
0	2010	通古鲁阿省	厄瓜多尔	-1.467	-78.442	层状火山	POINT (-78.442 -1.467)
1	2010	Eyjafjallajokull	冰岛	63.630	-19.620	层状火山	POINT (-19.62 63.63)
2	2010	帕卡亚	危地马拉	14.381	-90.601	复合火山	POINT (-90.601 14.381)
3	2010	Sarigan	美国	16.708	145.780	层状火山	POINT (145.78 16.708)
4	2010	Karangetang [Api Siau]	印度尼西亚	2.780	125.480	层状火山	POINT (125.48 2.78)

world = geopandas.read_file(geodatasets.get_path("naturalearth.land"))
df.Type.unique()

array(['Stratovolcano', 'Complex volcano', 'Shield volcano',
       'Subglacial volcano', 'Lava dome', 'Caldera'], dtype=object)

fig, ax = plt.subplots(figsize=(24, 18))
world.plot(ax=ax, alpha=0.4, color="grey")
geo_df.plot(column="Type", ax=ax, legend=True)
plt.title("Volcanoes")

Text(0.5, 1.0, 'Volcanoes')

创建 Folium 地图

Folium 有来自 OpenStreetMap、Mapbox 和 CartoDB 的多个内置图层。例如：

# CartoDB Positron
map = folium.Map(location=[13.406, 80.110], tiles="CartoDB Positron", zoom_start=9)
map

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# OpenStreetMap
map = folium.Map(location=[13.406, 80.110], tiles="OpenStreetMap", zoom_start=9)
map

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添加标记

要表示不同类型的火山，您可以创建Folium标记并将它们添加到您的地图中。

# Create a geometry list from the GeoDataFrame
geo_df_list = [[point.xy[1][0], point.xy[0][0]] for point in geo_df.geometry]

# Iterate through list and add a marker for each volcano, color-coded by its type.
i = 0
for coordinates in geo_df_list:
    # assign a color marker for the type of volcano, Strato being the most common
    if geo_df.Type[i] == "Stratovolcano":
        type_color = "green"
    elif geo_df.Type[i] == "Complex volcano":
        type_color = "blue"
    elif geo_df.Type[i] == "Shield volcano":
        type_color = "orange"
    elif geo_df.Type[i] == "Lava dome":
        type_color = "pink"
    else:
        type_color = "purple"

    # Place the markers with the popup labels and data
    map.add_child(
        folium.Marker(
            location=coordinates,
            popup="Year: "
            + str(geo_df.Year[i])
            + "<br>"
            + "Name: "
            + str(geo_df.Name[i])
            + "<br>"
            + "Country: "
            + str(geo_df.Country[i])
            + "<br>"
            + "Type: "
            + str(geo_df.Type[i])
            + "<br>"
            + "Coordinates: "
            + str(geo_df_list[i]),
            icon=folium.Icon(color="%s" % type_color),
        )
    )
    i = i + 1

map

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Folium 热力图

Folium 以其热图而闻名，热图创建一个热图层。要在 Folium 中绘制热图，您需要一个纬度和经度的列表。

# This example uses heatmaps to visualize the density of volcanoes
# which is more in some parts of the world compared to others.

from folium import plugins

map = folium.Map(location=[15, 30], tiles="Cartodb dark_matter", zoom_start=2)

heat_data = [[point.xy[1][0], point.xy[0][0]] for point in geo_df.geometry]

heat_data
plugins.HeatMap(heat_data).add_to(map)

map

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