小编mnm*_*mnm的帖子

我的数据框中有一列包含 nan 值和 int 值。原来的dType是float64，但我试图将其更改为int6，并将nan值更改为np.nan。现在我收到此错误： TypeError: float() argument must be a string or a number, not 'NAType' 当尝试对其进行插补时。在下表中，列类似于“年龄”

data = {'name':  ['Alex', 'Ben', 'Marry','Alex', 'Ben', 'Marry'],
        'job': ['teacher', 'doctor', 'engineer','teacher', 'doctor', 'engineer'],
        'age': [27, 32, 78,27, 32, 78],
        'weight': [160, 209, 130,164, 206, 132],
        'date': ['6-12-2022', '6-12-2022', '6-12-2022','6-13-2022', '6-13-2022', '6-13-2022']
        }

df = pd.DataFrame(data) df

    |name   |job        |age|weight |date
|---|-------|-----------|---|-------|--------
|0  |Alex   |teacher    |27 |160    |6-12-2022
|1  |Ben    |doctor     |32 |209    |6-12-2022
|2  |Marry  |engineer   |78 |130    |6-12-2022
|3  |Alex …

当我查询时，我得到一行，其中包含多个空值。有没有办法在结果中不获取空值，或者删除具有空值的列？

示例代码是：

let table_name = datatable(name:string, date_part:datetime, job_1:string, job_2:string, job_3:string, job_4:string)
[
     "David", datetime(2022-05-9), "Architect", "", "", "Engineer"
  
];
table_name 
|where name == "David" and (date_part  between (now() .. -10d))
|project  (job_1),(job_2),(job_3),(job_4)

谢谢你！