新建如下测试excel表：

一：目标匹配股票公司.xlsx，一个sheet，一张表

二：招商.xlsx sheet0，有额外的无效列

sheet1 两张表， 表的位置从头开始，中间有间隔

sheet2 

sheet3 三张表，两表中间间隔不同，表从头开始

sheet4 三张表， 表的位置不是从头开始

三： 中金.xlsx

 四：汇总表.xlsx，合并效果如下

五：匹配结果.xlsx，匹配结果如下：

六：代码如下

# enconding = 'utf-8'
from pathlib import Path
import pandas as pd
import numpy as np
import os,re,time,sys

class ExeclProc(object):
    def __init__(self, target_excel, merge_excel, match_result_excel):
        self.cur_path = Path(os.path.dirname(__file__)) #获取当前执行文件的路径
        self.merge_excel = os.path.join(self.cur_path, merge_excel) #合并总表的文件相对路径
        self.workbook = pd.ExcelWriter(self.merge_excel) #新建总表
        self.excels = self.cur_path.glob('*.xlsx*') # 获取文件夹下所有工作簿的文件路径
        self.target_excel = os.path.join(self.cur_path, target_excel)
        self.match_result = os.path.join(self.cur_path, match_result_excel)
        self.save_wb = pd.ExcelWriter(self.match_result)

    def exclude_new_create_execl(self, file_name):
        exclude_new_create_file = []
        exclude_new_create_file.append(os.path.basename(self.merge_excel)) 
        exclude_new_create_file.append(os.path.basename(self.target_excel))
        exclude_new_create_file.append(os.path.basename(self.match_result))
        if file_name in exclude_new_create_file:
            return True
        return False

    def is_single_sheet_multi_table(self,cloums):
        for column in cloums:
            if re.findall(r'Unnamed: d', column):#通过识别表头中有Unnamed判断有多个表
                return True
        return False

    def save_single_sheet_multi_table_column_start_end_index(self,file, sheet_name, index, start, end):
        table_name = re.sub('.xls[x]?', "-",file) + sheet_name + '-{}'
        if start != end:
            self.table_column_start_end[table_name.format(index)] = (start, end)
            return True
        return False

    def calc_single_sheet_multi_table_start_end_idx(self,file,sheet_name,colums):
        self.table_column_start_end = {}
        column_start_idx = 0
        column_end_idx = 0
        table_head_serial_num = 0
        for column_idx,column in enumerate(colums):
            if re.findall(r'Unnamed: d+', column):
                if column_idx + 1 < len(colums) and re.findall(r'Unnamed: d+', colums[column_idx + 1]):
                    self.save_single_sheet_multi_table_column_start_end_index(file, sheet_name, table_head_serial_num, column_start_idx, column_end_idx)
                else:
                    if self.save_single_sheet_multi_table_column_start_end_index(file, sheet_name, table_head_serial_num, column_start_idx, column_end_idx):
                        table_head_serial_num = table_head_serial_num + 1
                    column_start_idx = column_idx + 1
            else:
                column_end_idx = column_idx + 1

            if column_idx + 1 == len(colums):
                column_end_idx = column_idx + 1
                self.save_single_sheet_multi_table_column_start_end_index(file, sheet_name, table_head_serial_num, column_start_idx, column_end_idx)
            # print(self.table_column_start_end)

    def merge_multi_table_to_multi_sheet(self,file_path,sheet_name):
        df = pd.read_excel(file_path, sheet_name=sheet_name)
        for key in self.table_column_start_end.keys():
            data = {}
            start,end = self.table_column_start_end[key]
            for s in range(start,end):
                colunmn_name = re.sub('.d+', '' ,df.columns.values[s]) #将数量.1中".数字"去掉
                data[colunmn_name] = list(df.values[:,s])
            sheet = pd.DataFrame(data)
            sheet.to_excel(self.workbook,sheet_name = key,index=False)


    def merge_excel_proc(self):
        for file in self.excels:
            if self.exclude_new_create_execl(file.name):
                #print("跳过{}".format(file.name))
                continue
            file_path = os.path.join(self.cur_path, file.name)
            sheets = pd.ExcelFile(file_path).sheet_names
            for sheet_name in sheets:
                df = pd.read_excel(file_path, sheet_name=sheet_name)
                if self.is_single_sheet_multi_table(df.columns.values):
                    try:
                        self.calc_single_sheet_multi_table_start_end_idx(file.name, sheet_name, df.columns.values)
                        self.merge_multi_table_to_multi_sheet(file_path, sheet_name)
                    except TypeError as e:
                        print("=*"*40)
                        print("n===>【 {}-{} 】解析失败,请人工检查<===".format(file.name, sheet_name))
                        print(e)
                        print("=*"*40)
                        print("n")
                    except:
                        print("未知异常")
                else:
                    to_excel_sheet_name = re.sub('.xls[x]?', '-' ,file.name) + sheet_name
                    df.to_excel(self.workbook,sheet_name=to_excel_sheet_name, index=False)
        self.workbook.save()
        self.workbook.close()

    def read_flag_excel_info(self):
        sheets = pd.ExcelFile(self.target_excel).sheet_names
        self.company = []
        for index,sheet_name in enumerate(sheets):
            df = pd.read_excel(self.target_excel, sheet_name=sheet_name)
            for columns in df.columns.values:
                if not self.is_match_security_name(columns): continue
                self.company.extend(df[columns])  #保存目标公司名称
                break

    def is_match_security_name(self, security_name):
        security_name_list = ['证券名称','证券简称', '股票','股票公司']
        if security_name in security_name_list:return True
        return False

    def get_table_head_deadline(self, columns):
        deadline_time_keys = ["期限（天）", "期限(天）", "期限", "最长可使用天数", "出借期限", "合约期限（天）"]
        for column_idx, columns in enumerate(columns):
            if columns in deadline_time_keys:
                return (column_idx, columns)
        return None

    def get_table_special_head_deadline(self, df, rowIdx):
        speci_time_rule = r'(d+)s*[(（]?天[)）]?'
        deadline_time = ''
        publish_quantity = ''
        for column_idx, columns in enumerate(df.columns.values):
            mm = re.findall(speci_time_rule, columns)
            if len(mm) > 0:
                deadline_time = deadline_time + mm[0] + '/'
                publish_quantity = publish_quantity + str(df.values[rowIdx, [column_idx]][0]) + '/'
        #print('===={}-{}'.format(deadline_time, publish_quantity))
        return (deadline_time, publish_quantity)
    
    def get_publish_quantity_index(self, columns):
        publish_quantity_keys = ["数量上限", "数量上限", "潜在可出借（股）", "数量", "预计市值（千万元）","委托数量","预计规模"]
        for column_idx, columns in enumerate(columns):
            if columns in publish_quantity_keys:
                return (column_idx, columns)
        return None
        
    def rebuild_match_row(self, company_name, df, rowIdx, publish_quantity_column, deadline_time_column):
        rebuild_row = []
        rebuild_row.append('')
        rebuild_row.append(company_name)
        if publish_quantity_column != None:
            rebuild_row.extend(df.values[rowIdx, [publish_quantity_column[0]]])
        else:
            rebuild_row.extend(df.values[rowIdx])
        if deadline_time_column != None:
            rebuild_row.extend(df.values[rowIdx, [deadline_time_column[0]]])
        else:
            rebuild_row.extend(df.values[rowIdx])
        return rebuild_row

    def rebuild_match_head(self, sheet_name, security_name, publish_quantity_column, deadline_time_column):
        rebuild_head = []
        rebuild_head.append(sheet_name)
        rebuild_head.append(security_name)
        if publish_quantity_column != None:
            rebuild_head.append(publish_quantity_column[1])
        else:
            rebuild_head.append('数量')
        if deadline_time_column != None:
            rebuild_head.append(deadline_time_column[1])
        else:
            rebuild_head.append('期限')
        return rebuild_head
        
    def save_match_company_info(self):
        merge_sheets = pd.ExcelFile(self.merge_excel).sheet_names
        self.match_company = []
        for sheet_name in merge_sheets:
            df = pd.read_excel(self.merge_excel, sheet_name=sheet_name)
            is_find_match_company = False
            match_company_info = []
            security_name = "证券名称"
            publish_quantity_column = self.get_publish_quantity_index(df.columns.values)
            deadline_time_column = self.get_table_head_deadline(df.columns.values)
            for column_idx, columns in enumerate(df.columns.values):
                if not self.is_match_security_name(columns): continue
                for company in self.company:
                    for rowIdx, company_name in enumerate(df[columns]):
                        if company == company_name:
                            is_find_match_company = True
                            rebuild_row = []
                            deadline_time, publish_quantity = self.get_table_special_head_deadline(df, rowIdx)
                            if len(deadline_time) > 0 and len(publish_quantity) > 0:
                                rebuild_row.append('')
                                rebuild_row.append(company_name)
                                rebuild_row.append(publish_quantity)
                                rebuild_row.append(deadline_time)
                            elif publish_quantity == None or deadline_time_column == None:
                                rebuild_row.append('')
                                rebuild_row.append(company_name)
                                rebuild_row.append('')
                                rebuild_row.append('')
                            else:
                                rebuild_row = self.rebuild_match_row(company_name, df, rowIdx, publish_quantity_column, deadline_time_column)
                            match_company_info.extend([rebuild_row])
            if is_find_match_company:
                rebuild_head = self.rebuild_match_head(sheet_name, security_name, publish_quantity_column, deadline_time_column)
                self.match_company.extend([rebuild_head])
                merge_repeat = self.merge_repeat_info(match_company_info)
                for company in merge_repeat.keys():
                    one_company = []
                    one_company.append('')
                    one_company.append(company)
                    merge_repeat[company]["数量"]= re.sub(r'//', "", merge_repeat[company]["数量"])
                    merge_repeat[company]["期限"]= re.sub(r'//', "", merge_repeat[company]["期限"])
                    #print({"company": company,"数量":merge_repeat[company]["数量"], "期限":merge_repeat[company]["期限"]})
                    if merge_repeat[company]["数量"].endswith('/'):
                        merge_repeat[company]["数量"] = merge_repeat[company]["数量"].rpartition('/')[0]
                    if merge_repeat[company]["期限"].endswith('/'):
                        merge_repeat[company]["期限"] = merge_repeat[company]["期限"].rpartition('/')[0]
                    one_company.append(merge_repeat[company]["数量"])
                    one_company.append(merge_repeat[company]["期限"])
                    self.match_company.extend([one_company])
                self.match_company.extend([''])
        if  len(self.match_company) > 0:
            data=pd.DataFrame(self.match_company)
            data.to_excel(self.save_wb, sheet_name="匹配结果",index=False, header=None)
            self.save_wb.save()
            self.save_wb.close()
    
    def merge_repeat_info(self, match_company_info):
        merge_repeat = {}
        for info in match_company_info[0:]:
            _, company_name, _, _ = tuple(info)
            merge_repeat[company_name] = company_name
            merge_repeat[company_name] ={"数量":'', "期限":''}
            
        for info in match_company_info[0:]:
            _, company_name, quantity, deadline = tuple(info)
            quantity = merge_repeat[company_name]["数量"] + str(quantity) + "/"
            deadline = str(deadline)
            if '/' not in deadline: 
                if deadline not in merge_repeat[company_name]["期限"]:
                    deadline = merge_repeat[company_name]["期限"] + str(deadline) + "/"
                else:
                    continue
            else:
                for dl in deadline.split('/'):
                    dl = str(dl)
                    if dl != '' and dl not in merge_repeat[company_name]["期限"]:
                        merge_repeat[company_name]["期限"] = merge_repeat[company_name]["期限"] + str(dl) + "/"
                deadline = merge_repeat[company_name]["期限"]
            merge_repeat[company_name] ={"数量":quantity, "期限":deadline}
        return merge_repeat
                
if __name__ == '__main__':
    # ExeclProc 第一参数：表示目标
    # 第二个参数：新建总表名字，用于保存所有表格中sheet合并结果
    # 第三个参数：新建匹配结果表，用于保存匹配目标股票公司信息
    print('n=========================匹配开始============================n')
    match_result = '匹配结果.xlsx'
    excel = ExeclProc('目标匹配股票公司.xlsx', '汇总表.xlsx', match_result)
    excel.read_flag_excel_info()
    excel.merge_excel_proc()
    excel.save_match_company_info()
    print('=========================匹配完成============================n')
    print('======================请到 [{}] 查看匹配结果====================='.format(match_result))
    time.sleep(3)
    sys.exit(0)

最后

以上就是大方红牛为你收集整理的【Python】pandas合并Excel和匹配查找并输出匹配结果一：目标匹配股票公司.xlsx，一个sheet，一张表二：招商.xlsx sheet0，有额外的无效列sheet3 三张表，两表中间间隔不同，表从头开始sheet4 三张表， 表的位置不是从头开始三： 中金.xlsx 四：汇总表.xlsx，合并效果如下五：匹配结果.xlsx，匹配结果如下：六：代码如下的全部内容，希望文章能够帮你解决【Python】pandas合并Excel和匹配查找并输出匹配结果一：目标匹配股票公司.xlsx，一个sheet，一张表二：招商.xlsx sheet0，有额外的无效列sheet3 三张表，两表中间间隔不同，表从头开始sheet4 三张表， 表的位置不是从头开始三： 中金.xlsx 四：汇总表.xlsx，合并效果如下五：匹配结果.xlsx，匹配结果如下：六：代码如下所遇到的程序开发问题。

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