python | 基于geoplot重绘全国某要素分布图

用户11172986

发布于 2024-10-12 21:08:06

13200

代码可运行

文章被收录于专栏：气python风雨气python风雨

运行总次数：0

代码可运行

前言

之前使用pandas和cartopy绘制过

https://www.heywhale.com/mw/project/65b0e3448886afac92b3cb5a

来表现全国某个要素在各个省份的分布

现在我们使用geoplot库重新绘制一遍看看效果

!pip install geoplot -i https://pypi.mirrors.ustc.edu.cn/simple/

数据读取与处理

## 读取随机生成的数据
import pandas as pd
import geopandas as gpd
import numpy as np
# 读取shp文件
shp = gpd.read_file('/home/mw/input/china1656/china_map/china_map/China_Province_2022.shp')
random_nums = 1000*np.random.rand(len(shp))
# 将随机数列添加为新的列
shp['Random'] = random_nums
shp.head()

	省	省级码	省类型	ENG_NAME	VAR_NAME	FIRST_GID	FIRST_TYPE	year	geometry	Random
0	北京市	110000	直辖市	Beijing	Běi Jīng	110000	Municipality	2022	POLYGON ((117.38335 40.22647, 117.38557 40.224...	841.927184
1	天津市	120000	直辖市	Tianjin	Tiān Jīn	120000	Municipality	2022	POLYGON ((117.56937 40.19153, 117.56744 40.189...	807.565088
2	河北省	130000	省	Hebei	Hé Běi	130000	Province	2022	MULTIPOLYGON (((118.26945 38.98097, 118.26871 ...	987.744808
3	山西省	140000	省	Shanxi	Shān Xī	140000	Province	2022	POLYGON ((114.13714 40.73445, 114.13860 40.732...	202.062701
4	内蒙古自治区	150000	自治区	Neimenggu	Nèi Měng Gǔ	150000	Autonomous Region	2022	POLYGON ((121.49813 53.32607, 121.50116 53.321...	804.195501

Choropleth Map (分级统计图)

shp.loc[shp['省'] == '广东省', 'Random'] = 10

import geoplot as gplt
import geoplot.crs as gcrs
import matplotlib.pyplot as plt

# 设置画布大小
plt.figure(figsize=(16, 10),dpi=300)  # 这里设置宽度为10英寸，高度为8英寸，你可以根据需要调整

ax = gplt.choropleth(
    shp, hue='Random', projection=gcrs.AlbersEqualArea(),
    edgecolor='black', linewidth=1,
    cmap='Blues', legend=True,
    scheme='FisherJenks',
    legend_labels=[
        '0-10', '10-100', '100-300',
        '300-500', '>500'
    ]
)
gplt.polyplot(shp, facecolor='lightgray', edgecolor='None', ax=ax)
plt.title("全国压岁钱分布图")

# 显示图形
plt.show()

<Figure size 4800x3000 with 0 Axes>

高清版

import geopandas as gpd  
import geoplot as gplt
import geoplot.crs as gcrs
import matplotlib.pyplot as plt


# 创建一个子图
fig, ax = plt.subplots(1, 1, figsize=(16, 10), dpi=300, subplot_kw={'projection': gcrs.PlateCarree()})

# 绘制填充颜色的地图
gplt.choropleth(
    shp, hue='Random',  # 'Random'是你的GeoDataFrame中的列名
    edgecolor='black', linewidth=1,
    cmap='Blues', legend=True,
    scheme='FisherJenks',
    legend_labels=['0-10', '10-100', '100-300', '300-500', '>500'],
    ax=ax  
)

# 添加灰色底色的多边形轮廓
gplt.polyplot(shp, facecolor='lightgray', edgecolor='None', ax=ax)

# 设置标题
plt.title("全国压岁钱分布图")

# 显示图形
plt.show()

cartogram（变形统计图）

import pandas as pd
import geopandas as gpd
import geoplot as gplt
import geoplot.crs as gcrs
import matplotlib.pyplot as plt
import mapclassify as mc

scheme = mc.Quantiles(shp['Random'], k=5)
ax = gplt.cartogram(
    shp,
    scale='Random', limits=(0.75, 1),
    projection=gcrs.PlateCarree(),
    hue='Random', cmap='Reds', scheme=scheme,
    linewidth=0.5,
    legend=True, legend_kwargs={'loc': 'lower right'}, legend_var='hue',
    figsize=(12, 7)
)
gplt.polyplot(shp, facecolor='lightgray', edgecolor='None', ax=ax)

plt.title("全国压岁钱分布图")

Text(0.5, 1.0, '全国压岁钱分布图')

高清版

import pandas as pd
import geopandas as gpd
import geoplot as gplt
import geoplot.crs as gcrs
import matplotlib.pyplot as plt
import mapclassify as mc

scheme = mc.Quantiles(shp['Random'], k=5)

# 设置画布大小和DPI
fig, ax = plt.subplots(1, 1, figsize=(12, 7), dpi=300, subplot_kw={'projection': gcrs.PlateCarree()})

# 绘制变形统计图
gplt.cartogram(
    shp,
    scale='Random', limits=(0.75, 1),
    projection=gcrs.PlateCarree(),
    hue='Random', cmap='Reds', scheme=scheme,
    linewidth=0.5,
    legend=True, legend_kwargs={'loc': 'lower right'}, legend_var='hue',
    ax=ax  # 使用之前创建的ax
)

# 添加灰色底色的多边形轮廓
gplt.polyplot(shp, facecolor='lightgray', edgecolor='None', ax=ax)

# 设置标题
plt.title("全国压岁钱分布图")

# 显示图形
plt.show()