Use python to compare the data of two Excel tables, get the difference and the same data row.

Problem Description

At work, I encountered the need to compare the data of two Excel spreadsheet files to find out the different rows. For example, to compare whether the information of the same user is consistent, the information here may be in different versions, but the attribute columns are consistent, and the data content may be different. As shown in the table below:

Excel 1

Name	gender	age	address
Zhang San	male	26	Beijing

Excel 2

Name	gender	age	address
Zhang San	male	27	Shanghai

Solution

import pandas as pd

def compare_data(data1, sheetname1, data2, sheetname2):
    # 读取两个表
    dt1 = pd.read_excel(data1, sheet_name=sheetname1)
    dt2 = pd.read_excel(data2, sheet_name=sheetname2)
    # 确定基准列
    dt1_name = dt1['姓名'].values.tolist()
    dt2_name = dt2['姓名'].values.tolist()
    count = 0
    for i in dt1_name:
        if i in dt2_name:
            dt1_row = dt1.loc[dt1['name'] == i]
            dt2_row = dt2.loc[dt2['name'] == i]
            # 可以选择不做比较的列
            dt1_row_ = dt1_row.loc[:, dt1_row.columns.difference(['性别', '住址'])]
            dt2_row_ = dt2_row.loc[:, dt2_row.columns.difference(['性别', '住址'])]
            # 判断两行是否内容一致
            if dt1_row_.equals(dt2_row_):
                pass
            else:
                # count计数
                count += 1
                # 导入要保存的文件名，mode='a'可以控制连续写入csv文件
                dt1_row.to_csv(r'test.csv', index=False, mode='a', header=None)
                dt2_row.to_csv(r'test.csv', index=False, mode='a', header=None)

        else:
            print("匹配失败的姓名：", i)
    # 同理，可以反过来比较一下
    for j in dt2_name:
        if j not in dt1_name:
            print("匹配失败的姓名：", j)
    print("##############################")
    print('测试不同的样本数为：', count)