excel-sheet-filter-export

name: excel-sheet-filter-export description: "动态统计多Sheet Excel文件行数以判断大文件处理逻辑，并根据特定条件筛选数据、重命名字段后导出为包含下载链接的新Excel文件，适用于多Sheet数据探查与条件过滤导出场景。"

Skill Steps

This sub-skill covers one capability of the Excel workflow. For reading/counting/Parquet optimization, see the parent workflow SKILL.md.

Step1 读取目标Sheet，清理字段格式并根据特定条件筛选记录，统计关键指标。

target_sheet = 'Sheet1' # 替换为实际sheet名
df_target = pd.read_excel(file_path, sheet_name=target_sheet)

# 清理目标列的字符串格式（去除首尾空格）
filter_col = 'group_col'
if filter_col in df_target.columns:
    df_target[filter_col] = df_target[filter_col].astype(str).str.strip()

# 筛选符合条件的记录
target_value = 'target_value_example'
mask = df_target[filter_col] == target_value
df_filtered = df_target[mask]

# 统计特定范围的种类数量
target_col = 'target_col'
if target_col in df_filtered.columns:
    specific_ranges = df_filtered[target_col].dropna().unique()
    print(f"{target_col} 种类数量:", len(specific_ranges))
    
    # 统计各分类数量与占比
    value_counts_df = df_filtered[target_col].value_counts().reset_index()
    value_counts_df.columns = [target_col, '数量']
    value_counts_df['占比'] = (value_counts_df['数量'] / value_counts_df['数量'].sum()).map('{:.2%}'.format)
    
    # 添加总计行
    total_row = pd.DataFrame({
        target_col: ['总计'], 
        '数量': [value_counts_df['数量'].sum()], 
        '占比': ['100.00%']
    })
    value_counts_df = pd.concat([value_counts_df, total_row], ignore_index=True)
    print(f"\n{target_col} 分布情况:\n", value_counts_df.head())