pandas 叶上的热图-Python问题

Heatmap on Folium with Pandas( pandas 叶上的热图)

本文介绍了 pandas 叶上的热图的处理方法，对大家解决问题具有一定的参考价值，需要的朋友们下面随着小编来一起学习吧！

问题描述

我有以下语法，无法实现我正在尝试的操作：

df_bedarf = pd.read_csv('C:/Users/xxxxxx/Desktop/xxxxx/xxxxxx.csv', sep = ";")
df_bedarf.head()

df_locations = df_bedarf[["Latitude", "Longitude"]]
location_list = df_locations.values.tolist()
location_list_size= len(location_list)

## Creating a Points Map

map_points = folium.Map(location = [47.57087, 13.43828], zoom_start = 7)

for point in range(0, location_list_size):
    folium.Circle(
        location = location_list[point],
        popup=df_bedarf["Suburb"][point] + ": " + df_bedarf["Sort"][point],
        radius = 10000, blur = 10000,
        min_opacity =0.3,
        gradient = {.3: "yellow", .6: "orange", 1: "red"},
        max_zoom =1,
    ).add_to(map_points)
    
map_points

我希望渐变的颜色变得更红，t/a越高。

CSV头部如下：

Unnamed: 0  Suburb  Sort    t/a     Latitude    Longitude
0   0   Wien    CC  2272    48.201900   16.370000
1   1   Graz    LD  426     47.079675   15.420325
2   2   Feldbach    LD  248     46.952187   15.888309
3   3   Zerlach     RE  2041    46.944865   15.650902
4   4   Gnas    SM  1488    46.874198   15.826138

相反，我的地图上只有蓝色圆圈。我必须更改什么才能获得根据数量(t/a)改变颜色的圆形

提前感谢并致以问候

它应该看起来像这样：

推荐答案

更改每个标记的颜色的最简单方法是对数值列使用bin分类功能，并为该数值设置所需的颜色名称。如果要增加颜色数，请增加存储箱和标签。

import pandas as pd
import numpy as np
import io

data = '''
Suburb Sort t/a Latitude Longitude
0 Wien CC 2272 48.201900 16.370000
1 Graz LD 426 47.079675 15.420325
2 Feldbach LD 248 46.952187 15.888309
3 Zerlach RE 2041 46.944865 15.650902
4 Gnas SM 1488 46.874198 15.826138
'''

df_locations = pd.read_csv(io.StringIO(data), delim_whitespace=True)
colors = pd.cut(df_locations['t/a'], bins=4, labels=['hotpink', 'tomato', 'red', 'crimson'])
colors = colors.to_list()

df_locations

    Suburb  Sort    t/a     Latitude    Longitude   marker_color
0   Wien    CC  2272    48.201900   16.370000   crimson
1   Graz    LD  426     47.079675   15.420325   hotpink
2   Feldbach    LD  248     46.952187   15.888309   hotpink
3   Zerlach     RE  2041    46.944865   15.650902   crimson
4   Gnas    SM  1488    46.874198   15.826138   red

map_points = folium.Map(location = [47.57087, 13.43828], zoom_start = 7)

for idx, row in df_locations.iterrows():
    folium.Circle(
        location = [row['Latitude'], row['Longitude']],
        popup=row["Suburb"] + ": " + row["Sort"],
        radius = 10000,
        # blur = 10000,
        color=colors[idx],
        fill_color=colors[idx],
        # min_opacity=0.3,
        # max_zoom=1,
    ).add_to(map_points)
    
map_points

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