"""财务报表格式化"""
import pandas as pd
def format_income_statement_analysis(df: pd.DataFrame) -> str:
"""
格式化利润表分析输出
参数:
df: 包含利润表数据的DataFrame
"""
if df.empty:
return "未找到符合条件的利润表数据"
# 按照报告期末排序
df = df.sort_values('end_date')
# 提取年份和季度信息
df['year'] = df['end_date'].str[:4]
df['quarter'] = df['end_date'].str[4:6].map({'03': 'Q1', '06': 'Q2', '09': 'Q3', '12': 'Q4'})
df['period'] = df['year'] + df['quarter']
# 准备表头
header = ["项目"] + df['period'].tolist()
# 准备数据行
rows = []
metrics = {
'total_revenue': '营业总收入',
'revenue': '营业收入',
'total_cogs': '营业总成本',
'oper_cost': '营业成本',
'sell_exp': '销售费用',
'admin_exp': '管理费用',
'fin_exp': '财务费用',
'operate_profit': '营业利润',
'total_profit': '利润总额',
'n_income': '净利润',
'basic_eps': '每股收益'
}
for key, name in metrics.items():
row = [name]
for _, period_data in df.iterrows():
value = period_data[key]
# 格式化数值（单位：亿元）
if key != 'basic_eps':
value = f"{float(value)/100000000:.2f}亿" if pd.notna(value) else '-'
else:
value = f"{float(value):.2f}" if pd.notna(value) else '-'
row.append(value)
rows.append(row)
# 生成表格
table = []
table.append(" | ".join([f"{col:^12}" for col in header]))
table.append("-" * (14 * len(header)))
for row in rows:
table.append(" | ".join([f"{col:^12}" for col in row]))
# 计算同比增长率
def calc_yoy(series):
if len(series) >= 2:
return (series.iloc[-1] - series.iloc[-2]) / abs(series.iloc[-2]) * 100
return None
# 计算环比增长率
def calc_qoq(series):
if len(series) >= 2:
return (series.iloc[-1] - series.iloc[-2]) / abs(series.iloc[-2]) * 100
return None
# 生成分析报告
analysis = []
analysis.append("\n📊 财务分析报告")
analysis.append("=" * 50)
# 1. 收入分析
analysis.append("\n一、收入分析")
analysis.append("-" * 20)
# 1.1 营收规模与增长
revenue_yoy = calc_yoy(df['total_revenue'])
revenue_qoq = calc_qoq(df['total_revenue'])
latest_revenue = float(df.iloc[-1]['total_revenue'])/100000000
analysis.append("1. 营收规模与增长：")
analysis.append(f" • 当期营收：{latest_revenue:.2f}亿元")
if revenue_yoy is not None:
analysis.append(f" • 同比变动：{revenue_yoy:+.2f}%")
if revenue_qoq is not None:
analysis.append(f" • 环比变动：{revenue_qoq:+.2f}%")
# 2. 盈利能力分析
analysis.append("\n二、盈利能力分析")
analysis.append("-" * 20)
# 2.1 利润规模与增长
latest = df.iloc[-1]
profit_yoy = calc_yoy(df['n_income'])
profit_qoq = calc_qoq(df['n_income'])
latest_profit = float(latest['n_income'])/100000000
analysis.append("1. 利润规模与增长：")
analysis.append(f" • 当期净利润：{latest_profit:.2f}亿元")
if profit_yoy is not None:
analysis.append(f" • 同比变动：{profit_yoy:+.2f}%")
if profit_qoq is not None:
analysis.append(f" • 环比变动：{profit_qoq:+.2f}%")
# 2.2 盈利能力指标
gross_margin = ((latest['total_revenue'] - latest['oper_cost']) / latest['total_revenue']) * 100
operating_margin = (latest['operate_profit'] / latest['total_revenue']) * 100
net_margin = (latest['n_income'] / latest['total_revenue']) * 100
analysis.append("\n2. 盈利能力指标：")
analysis.append(f" • 毛利率：{gross_margin:.2f}%")
analysis.append(f" • 营业利润率：{operating_margin:.2f}%")
analysis.append(f" • 净利润率：{net_margin:.2f}%")
# 3. 成本费用分析
analysis.append("\n三、成本费用分析")
analysis.append("-" * 20)
# 3.1 成本费用结构
total_revenue = float(latest['total_revenue'])
cost_structure = {
'营业成本': (latest['oper_cost'] / total_revenue) * 100,
'销售费用': (latest['sell_exp'] / total_revenue) * 100,
'管理费用': (latest['admin_exp'] / total_revenue) * 100,
'财务费用': (latest['fin_exp'] / total_revenue) * 100
}
analysis.append("1. 成本费用结构（占营收比）：")
for item, ratio in cost_structure.items():
analysis.append(f" • {item}率：{ratio:.2f}%")
# 3.2 费用变动分析
analysis.append("\n2. 主要费用同比变动：")
expense_items = {
'销售费用': ('sell_exp', calc_yoy(df['sell_exp'])),
'管理费用': ('admin_exp', calc_yoy(df['admin_exp'])),
'财务费用': ('fin_exp', calc_yoy(df['fin_exp']))
}
for name, (_, yoy) in expense_items.items():
if yoy is not None:
analysis.append(f" • {name}：{yoy:+.2f}%")
# 4. 每股指标
analysis.append("\n四、每股指标")
analysis.append("-" * 20)
latest_eps = float(latest['basic_eps'])
eps_yoy = calc_yoy(df['basic_eps'])
analysis.append(f"• 基本每股收益：{latest_eps:.4f}元")
if eps_yoy is not None:
analysis.append(f"• 同比变动：{eps_yoy:+.2f}%")
# 5. 风险提示
analysis.append("\n⚠️ 风险提示")
analysis.append("-" * 20)
analysis.append("以上分析基于历史财务数据，仅供参考。投资决策需考虑更多因素，包括但不限于：")
analysis.append("• 行业周期与竞争态势")
analysis.append("• 公司经营与治理状况")
analysis.append("• 宏观经济环境")
analysis.append("• 政策法规变化")
return "\n".join(table) + "\n\n" + "\n".join(analysis)
