我想在列表中格式化一堆数字。最简单的方法是先将其转换为一堆字符串。这是我如何执行此操作的示例:
df[col_name].astype('str').tolist()
但是，这个问题是我得到了如下值:
['12.19', '13.99', '1.00', 'nan', '9.00']
有没有办法可以将
'nan' 值作为 None 或空字符串返回，例如:['12.19', '13.99', '1.00', None, '9.00']
或者:
['12.19', '13.99', '1.00', '', '9.00']
我该怎么做这两个？
最佳答案
你可以这样试试。
>>> df[col_name].apply(lambda v: str(v) if str(v) != 'nan' else None).tolist()
['12.19', '13.99', '1.00', None, '9.00']
>>>
>>> df[col_name].apply(lambda v: str(v) if str(v) != 'nan' else '').tolist()
['12.19', '13.99', '1.00', '', '9.00']
>>>
>>> df[col_name].apply(lambda v: str(v) if not pd.isnull(v) else None).tolist()
['12.19', '13.99', '1.00', None, '9.00']
>>>
>>> df[col_name].apply(lambda v: str(v) if not pd.isnull(v) else '').tolist()
['12.19', '13.99', '1.00', '', '9.00']
>>>
这是详细的解释。
>>> import pandas as pd
>>> import numpy as np
>>>
>>> df = pd.DataFrame({
... "fullname": ['P Y', 'P T', 'T Y', 'N A', 'P Z'],
... "age": [36, 80, 25, 8, 34],
... "salary": ['12.19', '13.99', '1.00', np.nan, '9.00']
... })
>>>
>>> df
fullname age salary
0 P Y 36 12.19
1 P T 80 13.99
2 T Y 25 1.00
3 N A 8 NaN
4 P Z 34 9.00
>>>
>>> # PROBLEM
...
>>> col_name = "salary"
>>> df[col_name].astype("str").tolist()
['12.19', '13.99', '1.00', 'nan', '9.00']
>>>
>>> # SOLUTION
...
>>> df[col_name].apply(lambda v: str(v) if str(v) != 'nan' else None)
0 12.19
1 13.99
2 1.00
3 None
4 9.00
Name: salary, dtype: object
>>>
>>> df[col_name].apply(lambda v: str(v) if str(v) != 'nan' else '')
0 12.19
1 13.99
2 1.00
3
4 9.00
Name: salary, dtype: object
>>>
>>> df[col_name].apply(lambda v: str(v) if str(v) != 'nan' else None).tolist()
['12.19', '13.99', '1.00', None, '9.00']
>>>
>>> df[col_name].apply(lambda v: str(v) if str(v) != 'nan' else '').tolist()
['12.19', '13.99', '1.00', '', '9.00']
>>>
>>> df[col_name].apply(lambda v: str(v) if not pd.isnull(v) else None).tolist()
['12.19', '13.99', '1.00', None, '9.00']
>>>
>>> df[col_name].apply(lambda v: str(v) if not pd.isnull(v) else '').tolist()
['12.19', '13.99', '1.00', '', '9.00']
>>>
关于python - 将列转换为字符串，保留 NaN(作为 None 或空白)，我们在Stack Overflow上找到一个类似的问题：https://stackoverflow.com/questions/53901398/