MySQL 拉取數據 、pandas轉 excel 中文亂碼

步驟

• 1、Mysql 拉取數據
• 2、封裝data Frame類型
• 3、轉csv 文件輸出 ( excel 打開中文亂碼問題)

    import logging
    from tool.db_client.mysql_client.mysql import MySqlClient
    from config.file_conf import BASE_DATA_DIR
    from tool.file_util import makedir
    import time,datetime
    import pandas as pd
    logger = logging.getLogger()

def downLoad_rt_rental_shop_cluster_snapshot():
    find_time = (datetime.datetime.today() - datetime.timedelta(days=1)).strftime('%Y-%m-%d 23:00:00')
    

    SQL_SHOP_CLUSTER_SNAPSHOT = """
     SELECT  cluster_id,
        name,
        landmark_name,
        famous_area_name,
        city_id,
        city_name,
        c_longitude,
        c_latitude,
        rental_shop_count,
        lasthour_usable_vehicle_count,

        usable_vehicle_count,
        pick_vehicle_count,
        return_vehicle_count,
        pick_forecast_count,
        dt,
        capture_time
    FROM     rt_rental_shop_cluster_snapshot
     WHERE    city_id = "1771"

    and  concat(substr(capture_time , 1,4),"-",substr(capture_time,5,2) ,"-", substr(capture_time,7,2)," ", "23:00:00") <=  "%s"
    and  concat(substr(capture_time , 1,4),"-",substr(capture_time,5,2) ,"-", substr(capture_time,7,2)," ", "23:00:00") >=  DATE_SUB("%s",INTERVAL 35 day)
    
    """
   find_time = (datetime.datetime.today() - datetime.timedelta(days=1)).strftime('%Y-%m-%d 23:00:00')
   SQL_SHOP_CLUSTER_SNAPSHOT %= (find_time, find_time)
    ms = MySqlClient()
    conn, cursor = ms.get_conn_cursor('idp')
    start_time = time.time()
    records = ms.execute_sql(conn, cursor, SQL_SHOP_CLUSTER_SNAPSHOT)
    ms.close(conn, cursor)
    makedir(BASE_DATA_DIR + "\\" + "rt_rental_shop_cluster_snapshot")
    dowload_file_name = "rt_rental_shop_cluster_snapshot_" + get_yesterday_str() + ".csv"
    file_path = BASE_DATA_DIR + "\\" + "rt_rental_shop_cluster_snapshot" + "\\" + dowload_file_name
    cols = ["cluster_id","name","landmark_name","famous_area_name","city_id",
            "city_name","c_longitude","c_latitude","rental_shop_count","lasthour_usable_vehicle_count",
            "usable_vehicle_count","pick_vehicle_count", "return_vehicle_count","pick_forecast_count","dt",
            "capture_time"
            ]
    # excel 打開中文亂碼 注意編碼       
    pd.DataFrame(np.array(records),columns=cols).to_csv(file_path, encoding="utf_8_sig", index=False)

    logger.info('rt_rental_shop_cluster_snapshot 數據, 下載耗時 %s 秒' % (round(time.time() - start_time, 0)))