| 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'
df_target = pd.read_excel(file_path, sheet_name=target_sheet)
filter_col = 'group_col'
if filter_col in df_target.columns:
df_target[filter_col] = df_target[filter_col].astype(str).str.strip()
target_value = 'target_value_example'
mask = df_target[filter_col] == target_value
df_filtered = df_target[mask]
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))
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)
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())
Step2 提取所需字段,对结果进行字段重命名与格式化处理,保存为新的Excel文件并生成下载链接。
selected_cols = ['col1', 'col2', filter_col, target_col]
existing_cols = [col for col in selected_cols if col in df_filtered.columns]
result_df = df_filtered[existing_cols].copy()
rename_mapping = {
'col1': '重命名列1',
'col2': '重命名列2',
filter_col: '筛选维度',
target_col: '分析维度'
}
result_df = result_df.rename(columns=rename_mapping)
output_path = "filtered_result_output.xlsx"
result_df.to_excel(output_path, index=False)
print("结果已保存至:", output_path)
print(f"[下载结果文件](sandbox:{output_path})")