编辑代码

# coding:utf-8
#JSRUN引擎2.0，支持多达30种语言在线运行，全仿真在线交互输入输出。 
import matplotlib.pyplot as plt
import pandas as pd

# 合同签订柱状图
contract_data = {
    "Year": ["2021", "2022", "2023", "2024", "2025"],
    "Q1": [175, 240, 212, 88, 300],
    "Q2": [111, 114, 126, 140, 0],
    "Q3": [149, 316, 275, 116, 0],
    "Q4": [117, 470, 809, 272, 0]
}
df_contract = pd.DataFrame(contract_data)
ax1 = df_contract.plot(x="Year", kind="bar", color=["#66C2A5","#FC8D62","#8DA0CB","#E78AC3"])
ax1.set_title("近五年合同签订季度分布（单位：万元）")
ax1.set_ylabel("金额（万元）")
plt.savefig("contract_chart.png", dpi=300)  # 保存为高清图片
plt.show()

# 回款堆叠柱状图
payment_data = {
    "Year": ["2021", "2022", "2023", "2024", "2025"],
    "Q1": [323, 319, 124, 123, 200],
    "Q2": [130, 434, 425, 73, 0],
    "Q3": [70, 331, 291, 316, 0],
    "Q4": [384, 228, 285, 303, 0]
}
df_payment = pd.DataFrame(payment_data)
ax2 = df_payment.plot(x="Year", kind="bar", stacked=True, color=["#08519C","#3182BD","#6BAED6","#BDD7E7"])
ax2.set_title("近五年回款季度结构分析（单位：万元）")
ax2.set_ylabel("金额（万元）")
plt.savefig("payment_chart.png", dpi=300)  # 保存为高清图片
plt.show()