pymysql写入时，遇到pandas dataframe中有混合的数据类型以及nan值

当遇到nan值无法写入mysql数据库，如果加上

df[pd.isna(df)]=None

又碰到"Cannot do inplace boolean setting on mixed-types with a non np.nan value"。可以乖乖认怂。认怂方式之一：

def importExcelToMysql(cur, objt):
    
    query = """REPLACE INTO origContactInfo (deviceRecordKey, fax, phone, email, importTime, updateTime) VALUES (%s, %s, %s, %s, %s, %s)"""
    for parent, dirnames, filenames in os.walk(objt.path_url):
        for filename in filenames:
            print(filename)
            excel_path = os.path.join(objt.path_url, filename)
            # 读取excel文件
            workbook = read_excel_with_file_name(excel_path)
            worksheet = workbook[objt.contact_sheet_name]
            row_count = len(worksheet)
            # 将表中每一行数据读到sqlstr数组中
            for i in range(1, row_count):
                current_time = datetime.datetime.now().strftime('%Y-%m-%d %H:%M:%S')
                valuestr = worksheet.loc[i].values.tolist()
#########################认怂大法在此###################################
                for find_nan in range(0,len(valuestr)): 
                    if pd.isna(valuestr[find_nan]):
                        valuestr[find_nan]=""
######################################################################
                valuestr.append(current_time)
                valuestr.append(current_time)
                valuestr = tuple(valuestr)
                # 将每行数据存到数据库中
                cur.execute(query, valuestr)
            print(filename + " finished writing to DB!")