pandas - 如何在由分区分隔的地图上绘制散点图？

Question

我想在由分区分隔的地图上绘制散点图。到目前为止，我已经尝试了以下方法。

import os
import matplotlib.pyplot as plt
import pandas as pd
import geopandas as gpd
import numpy as np

fPath = 'shape/bgd_adm_bbs_20201113_SHP/bgd_admbnda_adm2_bbs_20201113.shp'
bgd = gpd.read_file(fPath)
ax = bgd.plot(figsize=(15,15),column='ADM1_EN', legend=True)

bgd_admbnda_adm2_bbs_20201113.shp已在github中找到。它产生这个数字。

Here, there are 8 divisions 'Barishal', 'Chattogram', 'Dhaka', 'Khulna', 'Rajshahi', 'Rangpur', 'Sylhet', 'Mymensingh'.对于每个分区，都有一些数值（不是纬度、经度值）。例如达卡师[73.13 77.64 74.32 82.48 84.21 88.23 89.90]。为方便起见，我将文件附在github中。现在，我根据值范围拆分值。例如 i) 70-80：[73.13 77.64 74.32]，ii) 80-90：[82.48 84.21 88.23 89.90]。现在，我想用两种颜色在达卡分区的任何地方绘制两类值的散点图，例如这张图片。我附上了另一个预期的输出图像供您参考。

提前致谢。

标签： pandasdataframematplotlibgeopandas

Answer 1

这就像在同一轴上绘制数据一样简单

• 拥有医疗设施的数据，然后获取这些设施的 GIS 数据
• 获取地图 GEOJSON 并在轴上绘图
• 在同一轴上分散数据，使用医疗机构类型作为颜色

import requests, io
import pandas as pd
import geopandas as gpd
import matplotlib.pyplot as plt

# get some data of healthcare facilities
searchendpoint = "https://directory.spineservices.nhs.uk/ORD/2-0-0/organisations"
# get all healthcare facilities in Herefordshire
dfhc = pd.concat([pd.json_normalize(requests
                             .get(searchendpoint, params={"PostCode":f"HR{i}","Status":"Active"})
                             .json()["Organisations"]) 
           for i in range(1,10)]).reset_index(drop=True)

# get geo data for postcodes
dfgeo = (pd.json_normalize(requests.post("http://api.postcodes.io/postcodes", 
               json={"postcodes":dfhc.PostCode.unique().tolist()[0:100]}).json()["result"])
         .rename(columns={"result.postcode":"PostCode","result.longitude":"lng","result.latitude":"lat"})
         .loc[:,["PostCode","lat","lng"]]
        )

dfdata = dfhc.merge(dfgeo, on="PostCode", how="inner")
# going to use as color, so make if categorical so can get codes
dfdata["PrimaryRoleId"] = pd.Categorical(dfdata["PrimaryRoleId"])

fig, ax = plt.subplots(figsize=[14,6])

# get map of regions
df = gpd.read_file(io.StringIO(requests.get("https://martinjc.github.io/UK-GeoJSON/json/eng/msoa_by_lad/topo_E06000019.json").text))
df.plot(ax=ax)
# scatter data on top of region map
ax.scatter(x=dfdata["lng"],y=dfdata["lat"], s=50, c=dfdata["PrimaryRoleId"].cat.codes)

使用相同的数据集

import numpy as np
import geopandas as gpd
import matplotlib.pyplot as plt
import matplotlib

df = gpd.read_file("bgd_admbnda_adm2_bbs_20201113.shp")
fig, ax = plt.subplots(figsize=[8,8])
df.plot(ax=ax, alpha=0.5, edgecolor='k')
# some data that can be plotted on centroid
df["val"] = np.random.randint(1,100,len(df))

# use a discrete 
cmap = plt.cm.get_cmap('jet', 5)
# scatter data based on co-ords of centroid
sc = ax.scatter(x=df.centroid.x, y=df.centroid.y, s=50, c=df["val"], cmap=cmap)
plt.colorbar(sc)