我是python新手,正在尝试删除任何带有空EOB
代码的行,其中该Account Number
已经存在多个EOB
代码。例如,我们有这个“407”Account Number
贡献了三行。我希望删除缺少EOB
代码的行,但保留剩下的两行(EOB代码7730和3033)
然而,这里的复杂性(至少对我来说)是其他Account Number
从未有过EOB
代码。就像下面以“2300”和“6200”结尾的账户一样。在这些特定情况下,这些类型的帐户应保留在数据帧中
以下是此数据集的一小部分:
data = {'Account Number': ['407','407','407','4901','4901','4901','4901','4901','6902','6902','6902','6902','8700','6900','2300','6200','2400','2400','3200','3200','3200','3200','3200','3200','3400','2200','3300','7701','7701','7701','7701','7701','7701','3100','401','401','401','6600','6600','6600','6600'],
'Payer':['BCBS','BCBS','BCBS','BCBS','BCBS','BCBS','BCBS','BCBS','BCBS','BCBS','BCBS','BCBS','BCBS','BCBS','BCBS','BCBS','BCBS','BCBS','BCBS','BCBS','BCBS','BCBS','BCBS','BCBS','BCBS','BCBS','BCBS','BCBS','BCBS','BCBS','BCBS','BCBS','BCBS','BCBS','BCBS','BCBS','BCBS','BCBS','BCBS','BCBS','BCBS'],
'Remit Type':['IP Denied','IP Denied','IP Denied','IP Paid','IP Paid','IP Paid','IP Paid','IP Paid','IP Denied','IP Denied','IP Denied','IP Denied','IP Paid','IP Paid','IP Paid','IP Paid','IP Paid','IP Paid','IP Paid','IP Paid','IP Paid','IP Paid','IP Paid','IP Paid','IP Paid','IP Paid','IP Paid','IP Denied','IP Denied','IP Denied','IP Denied','IP Denied','IP Denied','IP Paid','IP Denied','IP Denied','IP Denied','IP Paid','IP Paid','IP Paid','IP Paid'],
'EOB':['','7730','3033','5001','','9932','3035','3038','9015','5000','','9932','','','','','','','','3035','829','9932','2635','5002','','','','851','','852','9932','818','9015','','','2628','3035','5003','','3035','9932'],
'Date':['Mar 10','Mar 10','Mar 10','Mar 10','Mar 10','Mar 10','Mar 10','Mar 10','Mar 10','Mar 10','Mar 10','Mar 10','Mar 10','Mar 10','Mar 10','Mar 10','Mar 10','Mar 10','Mar 10','Mar 10','Mar 10','Mar 10','Mar 10','Mar 10','Mar 10','Mar 10','Mar 10','Mar 10','Mar 10','Mar 10','Mar 10','Mar 10','Mar 10','Mar 10','Mar 10','Mar 10','Mar 10','Mar 10','Mar 10','Mar 10','Mar 10'],
'Status':['INPATIENT CLAIMS DENIED','INPATIENT CLAIMS DENIED','INPATIENT CLAIMS DENIED','INPATIENT CLAIMS SUSPENDED','INPATIENT CLAIMS SUSPENDED','INPATIENT CLAIMS SUSPENDED','INPATIENT CLAIMS SUSPENDED','INPATIENT CLAIMS SUSPENDED','INPATIENT CLAIMS DENIED','INPATIENT CLAIMS DENIED','INPATIENT CLAIMS DENIED','INPATIENT CLAIMS DENIED','INPATIENT CLAIMS PAID','INPATIENT CLAIMS PAID','INPATIENT CLAIMS PAID','INPATIENT CLAIMS PAID','INPATIENT CLAIMS PAID','INPATIENT CLAIMS PAID','INPATIENT CLAIMS PAID','INPATIENT CLAIMS PAID','INPATIENT CLAIMS PAID','INPATIENT CLAIMS PAID','INPATIENT CLAIMS PAID','INPATIENT CLAIMS PAID','INPATIENT CLAIMS SUSPENDED', 'INPATIENT CLAIMS PAID','INPATIENT CLAIMS SUSPENDED','INPATIENT CLAIMS DENIED','INPATIENT CLAIMS DENIED','INPATIENT CLAIMS DENIED','INPATIENT CLAIMS DENIED','INPATIENT CLAIMS DENIED','INPATIENT CLAIMS DENIED','INPATIENT CLAIMS SUSPENDED','INPATIENT CLAIMS DENIED','INPATIENT CLAIMS DENIED','INPATIENT CLAIMS DENIED','INPATIENT CLAIMS PAID','INPATIENT CLAIMS PAID','INPATIENT CLAIMS PAID','INPATIENT CLAIMS PAID']}
df = pd.DataFrame(data,columns=['Account Number','Payer','Remit Type','EOB','Date','Status'])
首先,您要检查与帐户关联的所有
EOB
是否为空。然后您可以将这些与非空EOB
组合:我将尝试在以下条件下确定要删除的索引:
它可以是:
查找相关的帐号:
删除行:
从样本开始,它给出:
首先,就个人而言,我建议不要在
pandas
中使用''
空字符串。改用np.nan
:然后定义一个helper函数,当有超过1行时,仅将其应用于
dropna
,并基于Account Number
将其应用于groupby
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