58 lines
1.5 KiB
Python
58 lines
1.5 KiB
Python
import pandas as pd
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import matplotlib.pyplot as plt
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import numpy as np
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# 读取数据
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df = pd.read_excel('MFP Regular Sites 2019.xlsx')
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# 计算中心纬度，用于校正经纬度比例
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lat_center = df['latitude'].mean()
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# 经度在该纬度下的校正系数
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aspect_ratio = 1 / np.cos(np.radians(lat_center))
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# 创建图形
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fig, ax = plt.subplots(figsize=(14, 10))
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# 绘制散点图
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scatter = ax.scatter(df['longitude'], df['latitude'],
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c=df['Number of Visits in 2019'],
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cmap='viridis',
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s=100,
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alpha=0.7,
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edgecolors='black',
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linewidth=0.5)
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# 设置等比例坐标轴（考虑纬度校正）
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ax.set_aspect(aspect_ratio)
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# 添加颜色条
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cbar = plt.colorbar(scatter, ax=ax)
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cbar.set_label('Number of Visits in 2019', fontsize=10)
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# 添加站点标签
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for idx, row in df.iterrows():
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ax.annotate(row['Site Name'].replace('MFP ', ''),
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(row['longitude'], row['latitude']),
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fontsize=6,
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alpha=0.7,
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xytext=(3, 3),
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textcoords='offset points')
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# 设置标签和标题
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ax.set_xlabel('Longitude', fontsize=12)
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ax.set_ylabel('Latitude', fontsize=12)
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ax.set_title('MFP Regular Sites 2019 - Geographic Distribution', fontsize=14)
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# 添加网格
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ax.grid(True, alpha=0.3)
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# 调整布局
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plt.tight_layout()
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# 保存图片
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plt.savefig('sites_map.png', dpi=150, bbox_inches='tight')
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print('图片已保存为 sites_map.png')
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# 显示图形
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plt.show()
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