使用pandas在folium中绘制标记时float64类型转换报错问题

开发者阿泽

2026-8-29

问题描述

首先提供使用的原始JSON文件内容如下：

{
    "entries": [
        {
            "awy_id": "",
            "distance": 0.0,
            "fl_at_wpt": 1,
            "lat": -34.821666,
            "lng": -58.536666,
            "max_fl": 410,
            "min_fl": 0,
            "ndic": "SA",
            "ndid": "SAEZ",
            "ndid_ext": "SAEZ",
            "ndtyp": "PA",
            "ndtyp_ext": "PA",
            "special_route": "",
            "through_fra_edge": false,
            "used_fl": 400
        },
        {
            "awy_id": "GBE6",
            "distance": 84661.59842290805,
            "fl_at_wpt": 322,
            "lat": -35.751666,
            "lng": -58.465,
            "max_fl": 1000,
            "min_fl": 0,
            "ndic": "SA",
            "ndid": "GBE",
            "ndid_ext": "GBE",
            "ndtyp": "D",
            "ndtyp_ext": "D",
            "special_route": "GBE6",
            "through_fra_edge": false,
            "used_fl": 400
        },
        {
            "awy_id": "DCT",
            "distance": 146604.93487805585,
            "fl_at_wpt": 400,
            "lat": -37.0,
            "lng": -59.0,
            "max_fl": 660,
            "min_fl": 95,
            "ndic": "",
            "ndid": "3700S05900W",
            "ndid_ext": "3700S05900W",
            "ndtyp": "$C",
            "ndtyp_ext": "$C",
            "special_route": "",
            "through_fra_edge": true,
            "used_fl": 400
        },
        {
            "awy_id": "DCT",
            "distance": 156860.1442784719,
            "fl_at_wpt": 400,
            "lat": -38.313333,
            "lng": -59.656666,
            "max_fl": 660,
            "min_fl": 95,
            "ndic": "SA",
            "ndid": "SIGUL",
            "ndid_ext": "SIGUL",
            "ndtyp": "EA",
            "ndtyp_ext": "EA",
            "special_route": "",
            "through_fra_edge": true,
            "used_fl": 400
        },
        {
            "awy_id": "DCT",
            "distance": 253654.31159714353,
            "fl_at_wpt": 400,
            "lat": -40.49,
            "lng": -60.551666,
            "max_fl": 660,
            "min_fl": 95,
            "ndic": "SA",
            "ndid": "PUGLI",
            "ndid_ext": "PUGLI",
            "ndtyp": "EA",
            "ndtyp_ext": "EA",
            "special_route": "",
            "through_fra_edge": true,
            "used_fl": 400
        },
        {
            "awy_id": "UT662",
            "distance": 455742.1357395189,
            "fl_at_wpt": 400,
            "lat": -44.38,
            "lng": -62.313333,
            "max_fl": 450,
            "min_fl": 250,
            "ndic": "SA",
            "ndid": "OGRAX",
            "ndid_ext": "OGRAX",
            "ndtyp": "EA",
            "ndtyp_ext": "EA",
            "special_route": "",
            "through_fra_edge": false,
            "used_fl": 400
        },
        {
            "awy_id": "DCT",
            "distance": 172690.29386362626,
            "fl_at_wpt": 400,
            "lat": -45.846666,
            "lng": -63.038333,
            "max_fl": 660,
            "min_fl": 95,
            "ndic": "SA",
            "ndid": "ESNAS",
            "ndid_ext": "ESNAS",
            "ndtyp": "EA",
            "ndtyp_ext": "EA",
            "special_route": "",
            "through_fra_edge": true,
            "used_fl": 400
        },
        {
            "awy_id": "DCT",
            "distance": 268007.5486955521,
            "fl_at_wpt": 400,
            "lat": -48.113333,
            "lng": -64.238333,
            "max_fl": 660,
            "min_fl": 95,
            "ndic": "SA",
            "ndid": "IRAVA",
            "ndid_ext": "IRAVA",
            "ndtyp": "EA",
            "ndtyp_ext": "EA",
            "special_route": "",
            "through_fra_edge": true,
            "used_fl": 400
        },
        {
            "awy_id": "DCT",
            "distance": 201521.2136195075,
            "fl_at_wpt": 400,
            "lat": -49.81,
            "lng": -65.205,
            "max_fl": 660,
            "min_fl": 95,
            "ndic": "SA",
            "ndid": "LOBOS",
            "ndid_ext": "LOBOS",
            "ndtyp": "EA",
            "ndtyp_ext": "EA",
            "special_route": "",
            "through_fra_edge": true,
            "used_fl": 400
        },
        {
            "awy_id": "UT662",
            "distance": 355978.6689666387,
            "fl_at_wpt": 400,
            "lat": -52.788333,
            "lng": -67.071666,
            "max_fl": 450,
            "min_fl": 250,
            "ndic": "SA",
            "ndid": "ERUPO",
            "ndid_ext": "ERUPO",
            "ndtyp": "EA",
            "ndtyp_ext": "EA",
            "special_route": "",
            "through_fra_edge": false,
            "used_fl": 400
        },
        {
            "awy_id": "DCT",
            "distance": 120043.42891043477,
            "fl_at_wpt": 210,
            "lat": -53.785,
            "lng": -67.76,
            "max_fl": 660,
            "min_fl": 95,
            "ndic": "SA",
            "ndid": "GRA",
            "ndid_ext": "GRA",
            "ndtyp": "DB",
            "ndtyp_ext": "DB",
            "special_route": "",
            "through_fra_edge": true,
            "used_fl": 400
        },
        {
            "awy_id": "DCT",
            "distance": 122840.72073640439,
            "fl_at_wpt": 2,
            "lat": -54.843333,
            "lng": -68.295,
            "max_fl": 660,
            "min_fl": 95,
            "ndic": "SA",
            "ndid": "SAWH",
            "ndid_ext": "SAWH",
            "ndtyp": "PA",
            "ndtyp_ext": "PA",
            "special_route": "DCT",
            "through_fra_edge": false,
            "used_fl": 400
        }
    ]
}

尝试使用pandas DataFrame中lat、lng列的经纬度数据，通过folium绘制地图标记，两列的数据类型均为float64。
实现代码如下：

import pandas as pd
import numpy as np
import folium
import json

with open('response.json') as json_data:
    data = json.load(json_data)

df = pd.DataFrame(data['entries'])
af = pd.DataFrame(data['profile'])

difference = af.diff(axis=0)
difference.drop([0],inplace=False)
difference

#df[df.select_dtypes(np.float64).columns] = df.select_dtypes(np.float64).astype(np.float32)
flight = folium.Map(
    location=[38.40, -30.40],
    zoom_start=2
)
for _, city in df.iterrows():
    folium.Marker(
        location=[df['lng'], df['lat']]
    ).add_to(flight)

flight

运行代码后出现如下报错：

Name: lng, dtype: float64 of type <class 'pandas.core.series.Series'> is not convertible to float.

已检索相关解决方案，尝试将lat、lng列强制转换为float类型，执行如下转换代码后问题仍未解决：

df[df.select_dtypes(np.float64).columns] = df.select_dtypes(np.float64).astype(np.float)

报错原因

这个报错和列的数据类型没有关系，之前做的float类型转换完全没有命中问题根源，核心问题有两个：

遍历DataFrame行的时候，没有取当前行的坐标值，反而把整个lng、lat列（pandas Series对象）传给了location参数。folium要求location接收两个单独的浮点数值组成的列表，传入整列对象自然无法转换为单个float值，触发报错。
坐标顺序写反了：folium的location参数固定要求顺序为*[纬度, 经度]*，原代码把经度lng放在了第一位，就算不报错标记位置也会完全错误。

另外代码里difference.drop([0],inplace=False)这行没有实际作用，inplace=False会返回删除后的新对象，没有赋值给变量的话原对象不会发生任何修改，不过这部分和当前报错无关。

修复方法

修改循环内的坐标取值逻辑，取当前遍历行的单个经纬度值，同时调整经纬度顺序即可，修复后的循环代码如下：

for _, city in df.iterrows():
    folium.Marker(
        # 取当前行的lat、lng值，纬度在前经度在后
        location=[city['lat'], city['lng']]
    ).add_to(flight)

不需要额外做float类型转换，原始数据里lat和lng本身就是浮点类型，直接取值即可正常运行。

内容的提问来源于stack exchange，提问作者setan0