忽略 pandas astype中的错误

问题描述

我有一个数字列，其中可能包含另一个 [0-9] 格式的字符.说:x = pandas.Series(["1","1.2", "*", "1", "**."]).然后，我想使用x.astype(dtype = float, errors = 'ignore')将该serie转换为数字列.尽管我要求他不要这样做，但我只是想不通为什么熊猫会一直给我一个错误！我的代码有问题吗?

I have a numeric column that could contain another characters different form [0-9]. Say: x = pandas.Series(["1","1.2", "*", "1", "**."]).Then I want to convert that serie into a numerical column using x.astype(dtype = float, errors = 'ignore') . I just can't figure out why Pandas keeps giving me an error despite the fact that I ask him not to! Is there something wrong with my code ?

推荐答案

我认为您想使用 pd.to_numeric(x，errors ='coerce')代替:

In [73]: x = pd.to_numeric(x, errors='coerce')

In [74]: x
Out[74]:
0    1.0
1    1.2
2    NaN
3    1.0
4    NaN
dtype: float64

PS实际上x.astype(dtype = float, errors = 'ignore')-可以正常工作，它不会产生错误，它只能保留序列，因为它不能转换某些元素:

PS actually x.astype(dtype = float, errors = 'ignore') - works as expected, it doesn't give an error, it just leaves series as it is as it can't convert some elements:

In [77]: x.astype(dtype = float, errors = 'ignore')
Out[77]:
0      1
1    1.2
2      *
3      1
4    **.
dtype: object   # <----- NOTE!!!

In [81]: x.astype(dtype = float, errors = 'ignore').tolist()
Out[81]: ['1', '1.2', '*', '1', '**.']

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