mean_101 = data_101.groupby('sales_region_code')['ord_qty'].sum() mean_102 = data_102.groupby('sales_region_code')['ord_qty'].sum()报错怎么改

这是一个非常典型的 Pandas 报错，它表明你的 DataFrame 中没有 'sales_region_code' 这个列，或者拼写错误。请检查一下你的 DataFrame 列名是否正确，是否缺少该列，或者该列的数据类型是否正确。您可以使用 data_101.columns 和 data_102.columns 来检查一下列名是否正确。

相关问题

如何解压 _, compressed_frame = cv2.imencode('.jpeg', frame)

要解压缩使用 `cv2.imencode()` 函数压缩的帧图像，可以使用 `cv2.imdecode()` 函数进行解码。下面是修改后的代码示例：

import cv2
import socket
import pickle

# 创建socket对象
client_socket = socket.socket(socket.AF_INET, socket.SOCK_DGRAM)
host_ip = '192.168.1.10'  # 服务端 IP 地址
port = 9999

vid = cv2.VideoCapture(0)

while True:
    # 读取视频帧
    success, frame = vid.read()

    # 压缩帧图像
    _, compressed_frame = cv2.imencode('.jpeg', frame)

    # 将压缩后的帧数据转换为字节数据
    data = pickle.dumps(compressed_frame)

    # 发送帧数据到服务端
    client_socket.sendto(data, (host_ip, port))

    # 按 'q' 键退出视频传输
    if cv2.waitKey(1) & 0xFF == ord('q'):
        break

vid.release()

在服务端接收到数据后，可以使用以下代码进行解压缩：

import cv2
import socket
import struct
import pickle

# 创建 socket 对象
server_socket = socket.socket(socket.AF_INET, socket.SOCK_DGRAM)
host_name = socket.gethostname()
host_ip = socket.gethostbyname(host_name)
print('Host IP:', host_ip)
port = 9999
socket_address = (host_ip, port)

# 绑定 socket 对象到地址和端口
server_socket.bind(socket_address)

print("等待客户端连接...")

# 解码函数，将字节数据转换为图像帧
def decode_frame(frame_data):
    frame = cv2.imdecode(frame_data, cv2.IMREAD_COLOR)
    return frame

while True:
    # 接收来自客户端的数据和地址
    frame_data, addr = server_socket.recvfrom(65535)
    print('连接地址:', addr)

    if frame_data:
        # 解码接收到的帧数据
        frame = decode_frame(frame_data)

        # 显示帧图像
        cv2.imshow('Received Frame', frame)

        # 按 'q' 键退出视频传输
        if cv2.waitKey(1) & 0xFF == ord('q'):
            break

cv2.destroyAllWindows()

在上述示例中，解压缩函数 `decode_frame()` 使用 `cv2.imdecode()` 函数将压缩后的帧数据解码为原始的帧图像。

希望这可以帮助到你！如果还有其他问题，请随时提问。

UPDATE a SET a.refund_status = b.dealstat , a.refund_time = b.dealtime FROM dwi_store_setmt_ord_dtl_p a INNER JOIN sdi_dgmps_dgmpsdb_mstore.chainstorefeemangdtl_p b ON a.comp_code = trim(upper(b.companycode)) AND a.src_pid = trim(b.pid) WHERE a.refund_status = 0 AND ISNULL(a.refund_time,'') = '' AND b.dealstat = 1 AND ISNULL(a.dealtime,'') <> '' ;改为用merge into 更新

Sure, here's the equivalent MERGE statement:

MERGE INTO dwi_store_setmt_ord_dtl_p AS a
USING (
    SELECT trim(upper(b.companycode)) AS comp_code,
           trim(b.pid) AS src_pid,
           b.dealstat,
           b.dealtime
    FROM sdi_dgmps_dgmpsdb_mstore.chainstorefeemangdtl_p AS b
    WHERE b.dealstat = 1
) AS b
ON a.comp_code = b.comp_code
   AND a.src_pid = b.src_pid
   AND a.refund_status = 0
   AND ISNULL(a.refund_time, '') = ''
   AND ISNULL(a.dealtime, '') <> ''
WHEN MATCHED THEN
    UPDATE SET a.refund_status = b.dealstat,
               a.refund_time = b.dealtime;

This MERGE statement combines the source table `sdi_dgmps_dgmpsdb_mstore.chainstorefeemangdtl_p` with the target table `dwi_store_setmt_ord_dtl_p` based on the matching conditions specified in the ON clause. When a match is found, the specified columns in the target table are updated with the corresponding values from the source table.