job_matching = pd.merge(job_info.assign(key=1), job_seekers.assign(key=1), on='key').drop('key', axis=1)

这是一行Python代码，用于将两个数据表按照共同的key列进行合并。其中，job_info和job_seekers分别是两个数据表的名称。具体实现过程是先给两个数据表都新增一个key列，并将其值都设为1，然后按照key列进行合并，最后再将新增的key列删除。这样做的目的是将两个数据表合并成一个，以方便进行职位匹配等操作。

相关问题

reports_avg = np.mean(reports_list, axis=0) matrices_avg = np.mean(matrices_list, axis=0) micro_auc_avg = np.mean(micro_auc_list) macro_auc_avg = np.mean(macro_auc_list) fpr_avg = np.mean(fpr_list, axis=0) tpr_avg = np.mean(tpr_list, axis=0) roc_auc_avg = np.mean(roc_auc_list, axis=0)出现ufunc 'add' did not contain a loop with signature matching types (dtype('<U326'), dtype('<U326')) -> None的问题怎么解决

这个错误通常是由于numpy数组中包含字符串类型的数据引起的。numpy中的大多数函数是针对数值类型的，不支持字符串类型的数据。解决方法是将字符串类型的数据转换为数值类型。你可以使用numpy中的astype()函数将字符串类型的数据转换为数值类型，例如：

reports_list = reports_list.astype(float)
matrices_list = matrices_list.astype(float)

如果你还有其他包含字符串类型数据的数组，也需要进行相应的转换。

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.