[英]Pandas column dtype is object but python thinks it is float
I read in a csv like this我读到这样的 csv
df = pd.read_csv(self.file_path, dtype=str)
then I try this:然后我试试这个:
df = df[df["MY_COLUMN"].apply(lambda x: x.isnumeric())]
I get an AttributeError:我得到一个属性错误:
AttributeError: 'float' object has no attribute 'isnumeric'
AttributeError: 'float' object 没有属性 'isnumeric'
Why is this happening?为什么会这样? The column contains mostly digits.
该列主要包含数字。
I want to filter out the ones where there are no digits.我想过滤掉没有数字的那些。
This question is not how to achieve that or do it better but why do I get an AttributeError
here?这个问题不是如何实现或做得更好,而是为什么我在这里得到一个
AttributeError
?
Why is this happening?
为什么会这样?
I think because NaN is not converting to string
if use dtype=str
, still is missing value, so type=float
我认为因为如果使用
dtype=str
, NaN 不会转换为string
,仍然缺少值,所以type=float
Use Series.str.isnumeric
for working isnumeric
with missing values like all text functions in pandas:使用
Series.str.isnumeric
处理带有缺失值的isnumeric
,例如 pandas 中的所有文本函数:
df[df["MY_COLUMN"].str.isnumeric()]
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