import pandas as pd
import matplotlib.pyplot as plt
import numpy as np

# 读取数据
df = pd.read_excel('MFP Regular Sites 2019.xlsx')

# 计算中心纬度，用于校正经纬度比例
lat_center = df['latitude'].mean()
# 经度在该纬度下的校正系数
aspect_ratio = 1 / np.cos(np.radians(lat_center))

# 创建图形
fig, ax = plt.subplots(figsize=(14, 10))

# 绘制散点图
scatter = ax.scatter(df['longitude'], df['latitude'],
                     c=df['Number of Visits in 2019'],
                     cmap='viridis',
                     s=100,
                     alpha=0.7,
                     edgecolors='black',
                     linewidth=0.5)

# 设置等比例坐标轴（考虑纬度校正）
ax.set_aspect(aspect_ratio)

# 添加颜色条
cbar = plt.colorbar(scatter, ax=ax)
cbar.set_label('Number of Visits in 2019', fontsize=10)

# 添加站点标签
for idx, row in df.iterrows():
    ax.annotate(row['Site Name'].replace('MFP ', ''),
                (row['longitude'], row['latitude']),
                fontsize=6,
                alpha=0.7,
                xytext=(3, 3),
                textcoords='offset points')

# 设置标签和标题
ax.set_xlabel('Longitude', fontsize=12)
ax.set_ylabel('Latitude', fontsize=12)
ax.set_title('MFP Regular Sites 2019 - Geographic Distribution', fontsize=14)

# 添加网格
ax.grid(True, alpha=0.3)

# 调整布局
plt.tight_layout()

# 保存图片
plt.savefig('sites_map.png', dpi=150, bbox_inches='tight')
print('图片已保存为 sites_map.png')

# 显示图形
plt.show()