python - 叶热图/绘图

Question

我正在尝试使用 Folium HeatMap 绘制坐标对向量，但我不确定如何执行此操作的语法或格式。这是下面的坐标示例。

[[40.81037274049654, -73.95031224929029],
 [50.0012314, 8.2762513],
 [42.44770298533053, -76.48085858627933],
 [38.0324946, -78.49558275000001],
 [46.9895828, 6.9292641],
 [40.0482166, -82.4256197510104],
 [46.8321794, -93.8655223],
 [40.00019767338659, -83.01630047815202],
 [39.327249, -81.997868],
 [34.395342, -111.7632755],
 [52.22336325, 6.870595664097989],
 [51.0538286, 3.7250121],
 [39.544252251998486, -119.81562594002978],
 [45.1875602, 5.7357819],
 [40.00019767338659, -83.01630047815202],
 [39.6963829, -104.98067577169373],
 [34.5442609, -91.9690285],
 [32.0961451, 34.9514955],
 [42.05617321794737, -87.67467292784035],
 [36.107321847223574, -115.1434556952617],
 [41.7808282, -87.6023695012072],
 [31.2525238, 34.7905787],
 [47.7981346, 13.0464806],
 [52.3727598, 4.8936041],
 [27.252788, 115.7838858],
 [29.9165812, -90.1287705],
 [47.7981346, 13.0464806],
 [27.252788, 115.7838858],
 [38.9542862, -95.2557007],
 [42.3764147, -71.2365688],
 [50.724165, -3.660795843955193],
 [52.0191005, 8.531007],
 [40.73160889144053, -73.98848621087781],
 [43.706734649139655, -72.27819596683293],
 [40.73160889144053, -73.98848621087781],
 [50.938361, 6.959974],
 [50.879202, 4.7011675],
 [52.1518157, 4.4811088666204295],
 [37.42624599743801, -122.15882213777446],
 [33.64595313863429, -117.84569962233687],
 [40.558794575827264, -105.06587231222527],
 [37.87240881119929, -122.25794675505735],
 [38.551583949999994, -121.72638545000001],
 [40.80082388155166, -77.85963663593435],
 [40.73160889144053, -73.98848621087781],
 [45.4077172, 11.8734455],
 [53.2190652, 6.5680077],
 [40.80082388155166, -77.85963663593435],
 [-34.70850204081632, -58.43206844897959],
 [-34.70849202040816, -58.432049224489795]]

有人能告诉我用 Folium 或其他一些有用的 HeatMapping 包对所有这些坐标对进行热图的有效方法吗？谢谢

标签： pythonplotcoordinatesheatmapfolium

Answer 1

这是一段代码：

# 'data' is the list you have in the question. 
data_a = np.array(data)
m = folium.Map()
m.add_child(plugins.HeatMap(data_a, radius=15))
m

结果（在 Jupyter 中）是：