Deeplot

Python代码

import matplotlib.pyplot as plt
import numpy as np

# 数据配置（按原图实际数据排列调整）
quarters = [f"{y}Q{q}" for y in range(2020,2025) for q in range(1,5)][:-1][::-1]  # 逆序排列匹配原图
metrics = {
    '流动比率': [0.89,0.96,1.05,0.95,0.92,0.87,1.10,0.92,0.72,0.63,0.66,0.58,0.54,0.63,0.77,0.78,0.77,0.78,0.77],
    '速动比率': [0.45,0.53,0.64,0.52,0.52,0.47,0.65,0.52,0.51,0.42,0.44,0.36,0.33,0.38,0.51,0.43,0.55,0.55,0.56],
    '现金比率': [0.20,0.25,0.35,0.23,0.21,0.21,0.26,0.18,0.25,0.19,0.18,0.11,0.13,0.13,0.17,0.18,0.17,0.25,0.25]
}

# 可视化设置
plt.figure(figsize=(14, 7), dpi=100)
x = np.arange(len(quarters))
colors = ['#2E86C1', '#E67E22', '#28B463']  # 商务蓝、活力橙、生态绿

# 绘制趋势线
for idx, (metric, values) in enumerate(metrics.items()):
    plt.plot(x, values, 
            marker='D' if metric=='现金比率' else 'o',  # 现金比率使用菱形标记
            markersize=7,
            linewidth=2.2,
            color=colors[idx],
            markeredgecolor='white',  # 增加标记描边
            label=metric)

# 坐标轴优化
plt.xticks(x, quarters, rotation=45, ha='right', fontsize=9)
plt.gca().invert_xaxis()  # X轴逆序排列匹配原图
plt.yticks(np.arange(0, 1.3, 0.1))
plt.gca().yaxis.grid(True, linestyle=':', alpha=0.4)

# 图表元素
plt.title('企业流动性指标趋势分析（2020Q1-2024Q3）', fontsize=14, pad=20, fontweight='semibold')
plt.xlabel('季度', fontsize=10, labelpad=12)
plt.ylabel('比率值', fontsize=10, labelpad=12)
plt.legend(loc='upper center', bbox_to_anchor=(0.5, -0.15), ncol=3, frameon=False)

plt.tight_layout()
plt.show()
运行结果

正在生成图表...
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