diff --git a/contributors/han_ying_feng/office/excel.py b/contributors/han_ying_feng/office/excel.py
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index 0000000000000000000000000000000000000000..3dc95c888f03dac63231546ab889a2e38eb3a7b1
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+++ b/contributors/han_ying_feng/office/excel.py
@@ -0,0 +1,118 @@
+#!/usr/bin/env python
+# -*- coding:utf-8 -*-
+
+#############################################
+# File Name: excel.py
+# Mail: 1957875073@qq.com
+# Created Time:  2022-4-25 10:17:34
+# Description: 有关 excel 的自动化操作
+#############################################
+import math
+
+import numpy
+from faker import Faker
+import pandas as pd
+from alive_progress import alive_bar
+
+from utils import pandas_mem
+
+
+def fake2excel(columns=['name'], rows=1, language='zh_CN', path='./fake2excel.xlsx', ):
+    """
+    @Author & Date  : CoderWanFeng 2022/5/13 0:12
+    @Desc  : columns:list，每列的数据名称，默认是名称
+            rows：多少行，默认是1
+            language：什么语言，可以填english，默认是中文
+            path：输出excel的位置，有默认值
+    """
+    # 可以选择英语
+    if language.lower() == 'english':
+        language = 'en_US'
+    # 开始造数
+    fake = Faker(language)
+    excel_dict = {}
+    with alive_bar(len(columns) * rows) as bar:
+        for column in columns:
+            excel_dict[column] = list()
+            # excel_dict[column] = map(lambda x: eval('fake.{func}()'.format(func=x)), [column] * rows) # 使用map，会报错
+            while len(excel_dict[column]) < rows:
+                excel_dict[column].append(eval('fake.{func}()'.format(func=column)))
+                bar()
+        # 用pandas，将模拟数据，写进excel里面
+        data = pd.DataFrame(excel_dict)
+        data = pandas_mem.reduce_pandas_mem_usage(data)
+        __excelWriter__(path=path, data=data)
+
+
+#############################################
+# Author: han_ying_feng
+# Mail: gyuanhao@163.com
+# Created Time:  2022-05-26 12:13:09
+# Description: 将想要添加的DataFrame 写入到相应Path的Excel文件中
+#############################################
+def __excelWriter(path, data: pd.DataFrame):
+    # 使用文件路径创建ExcelWriter对象
+    writer = pd.ExcelWriter(path)
+    # 将数据写入到writer对象中
+    data.to_excel(writer, index=False)
+    # 保存文件
+    writer.save()
+    # 关闭资源
+    writer.close()
+
+
+#############################################
+# Author: han_ying_feng
+# Mail: gyuanhao@163.com
+# Created Time:  2022-05-26 12:13:09
+# Description: 根据表名读取Excel数据
+#############################################
+def read_all_excel(excel_file_path, sheet_name='Sheet1', header=0) -> pd.DataFrame:
+    return read_cols_to_name(excel_file_path, sheet_name=sheet_name, header=header)
+
+
+#############################################
+# Author: han_ying_feng
+# Mail: gyuanhao@163.com
+# Created Time:  2022-05-26 12:13:09
+# Description: 读取Excel某列数据
+#############################################
+def read_cols_to_name(excel_file_path, cols_name=None, header=0, sheet_name='Sheet1') -> pd.DataFrame:
+    return pd.read_excel(excel_file_path, usecols=cols_name, header=header, sheet_name=sheet_name)
+
+
+#############################################
+# Author: han_ying_feng
+# Mail: gyuanhao@163.com
+# Created Time:  2022-05-26 12:13:03
+# Description: 计算某列数据的和，并返回
+#############################################
+def sum_by_cols(excel_file_path, cols_name=[], header=0, sheet_name='Sheet1'):
+    # 读取数据表
+    cols_data_list = read_cols_to_name(excel_file_path, cols_name=cols_name, header=header, sheet_name=sheet_name)
+    # 获取数据表中的数据
+    values = cols_data_list.values
+    # 将获取到的数据更改为list
+    num_list = []
+    for item in values:
+        # 判断整列中的数据是否是数字类型
+        if type(item[0]) == int or type(item[0]) == numpy.int64:
+            num_list.append(item[0])
+    return math.fsum(num_list)
+
+
+#############################################
+# Author: han_ying_feng
+# Mail: gyuanhao@163.com
+# Created Time:  2022-05-26 12:13:03
+# Description: 将一段数据添加到指定列中的单元格内
+#############################################
+def append_by_cols(data, excel_file_path, cols_name=[], sheet_name='Sheet1', header=0, axis=0):
+    # 读取整个表的内容
+    read_data = read_all_excel(excel_file_path, sheet_name, header=header)
+    # 创建新数据的Frame
+    df = pd.DataFrame(data=[data], columns=cols_name)
+    # 新数据与读取到的整个表的数据合并
+    data = pd.concat([read_data, df], ignore_index=True, axis=axis)
+    # 写入原文件中
+    __excelWriter__(excel_file_path, data)