pip install matplotlib
pip install basemap
pip install cartopy

import matplotlib.pyplot as plt
from mpl_toolkits.basemap import Basemap

# 創(chuàng)建一個(gè)新的圖形
plt.figure(figsize=(10, 7))

# 創(chuàng)建 Basemap 對(duì)象
m = Basemap(projection='lcc', resolution='h', lat_0=20, lon_0=0)

# 繪制海岸線和國(guó)家邊界
m.drawcoastlines()
m.drawcountries()

# 填充大陸
m.fillcontinents(color='lightgray', lake_color='aqua')

# 添加標(biāo)題
plt.title('World Map with Basemap')

# 顯示圖形
plt.show()

# 城市經(jīng)緯度數(shù)據(jù)
cities = {
    'New York': (-74.006, 40.7128),
    'Los Angeles': (-118.2437, 34.0522),
    'Chicago': (-87.6298, 41.8781),
    'Houston': (-95.3698, 29.7604),
    'Phoenix': (-112.074, 33.4484)
}

# 創(chuàng)建一個(gè)新的圖形
plt.figure(figsize=(10, 7))

# 創(chuàng)建 Basemap 對(duì)象
m = Basemap(projection='lcc', resolution='h', lat_0=20, lon_0=0)

# 繪制海岸線和國(guó)家邊界
m.drawcoastlines()
m.drawcountries()

# 填充大陸
m.fillcontinents(color='lightgray', lake_color='aqua')

# 標(biāo)出城市
for city, (lon, lat) in cities.items():
    x, y = m(lon, lat)
    m.plot(x, y, 'bo', markersize=10)  # 用藍(lán)色圓點(diǎn)表示城市
    plt.text(x, y, city, fontsize=12, ha='left')

# 添加標(biāo)題
plt.title('City Locations in the USA')

# 顯示圖形
plt.show()

import matplotlib.pyplot as plt
import cartopy.crs as ccrs

# 創(chuàng)建一個(gè)新的圖形
plt.figure(figsize=(10, 7))

# 使用 PlateCarree 投影創(chuàng)建地圖
ax = plt.axes(projection=ccrs.PlateCarree())

# 繪制海岸線和國(guó)家邊界
ax.coastlines()
ax.add_feature(cartopy.feature.BORDERS, linestyle=':')

# 添加標(biāo)題
plt.title('World Map with Cartopy')

# 顯示圖形
plt.show()

# 城市經(jīng)緯度數(shù)據(jù)
cities = {
    'New York': (-74.006, 40.7128),
    'Los Angeles': (-118.2437, 34.0522),
    'Chicago': (-87.6298, 41.8781),
    'Houston': (-95.3698, 29.7604),
    'Phoenix': (-112.074, 33.4484)
}

# 創(chuàng)建一個(gè)新的圖形
plt.figure(figsize=(10, 7))

# 使用 PlateCarree 投影創(chuàng)建地圖
ax = plt.axes(projection=ccrs.PlateCarree())

# 繪制海岸線和國(guó)家邊界
ax.coastlines()
ax.add_feature(cartopy.feature.BORDERS, linestyle=':')

# 標(biāo)出城市
for city, (lon, lat) in cities.items():
    ax.plot(lon, lat, 'ro', markersize=8, transform=ccrs.PlateCarree())  # 用紅色圓點(diǎn)表示城市
    plt.text(lon, lat, city, fontsize=12, ha='left', transform=ccrs.PlateCarree())

# 添加標(biāo)題
plt.title('City Locations in the USA')

# 顯示圖形
plt.show()

pip install geopandas

import geopandas as gpd
import matplotlib.pyplot as plt

# 加載世界地圖數(shù)據(jù)
world = gpd.read_file(gpd.datasets.get_path('naturalearth_lowres'))

# 創(chuàng)建圖形
fig, ax = plt.subplots(figsize=(15, 10))

# 繪制地圖
world.plot(ax=ax, color='lightgrey', edgecolor='black')

# 添加標(biāo)題
plt.title('World Map with GeoPandas')

# 顯示圖形
plt.show()

# 過濾出特定國(guó)家
countries = world[world['continent'] == 'Asia']

# 創(chuàng)建圖形
fig, ax = plt.subplots(figsize=(15, 10))

# 繪制地圖
countries.plot(ax=ax, color='lightgreen', edgecolor='black')

# 添加標(biāo)題
plt.title('Asian Countries')

# 顯示圖形
plt.show()

import numpy as np
import pandas as pd

# 生成隨機(jī)經(jīng)緯度數(shù)據(jù)
num_points = 1000
lon = np.random.uniform(-180, 180, num_points)
lat = np.random.uniform(-90, 90, num_points)

# 創(chuàng)建 DataFrame
data = pd.DataFrame({'lon': lon, 'lat': lat})

import matplotlib.pyplot as plt
import geopandas as gpd
from scipy.stats import gaussian_kde

# 加載世界地圖數(shù)據(jù)
world = gpd.read_file(gpd.datasets.get_path

('naturalearth_lowres'))

# 創(chuàng)建圖形
fig, ax = plt.subplots(figsize=(15, 10))

# 繪制世界地圖
world.plot(ax=ax, color='lightgrey', edgecolor='black')

# 計(jì)算密度
kde = gaussian_kde([lon, lat])
xgrid = np.linspace(-180, 180, 100)
ygrid = np.linspace(-90, 90, 100)
X, Y = np.meshgrid(xgrid, ygrid)
Z = kde(np.vstack([X.ravel(), Y.ravel()])).reshape(X.shape)

# 繪制熱力圖
ax.imshow(Z, extent=(-180, 180, -90, 90), origin='lower', cmap='Reds', alpha=0.5)

# 添加標(biāo)題
plt.title('Heatmap of Random Points')

# 顯示圖形
plt.show()