pandas 忽略熊猫 astype 中的错误
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Ignore errors in pandas astype
提问by Neroksi
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 ?
我有一个数字列，它可以包含另一个不同形式的字符[0-9]。说：x = pandas.Series(["1","1.2", "*", "1", "**."])。然后，我要转换的是意甲成使用数值列x.astype(dtype = float, errors = 'ignore')。我就是不明白为什么 Pandas 总是给我一个错误，尽管我要求他不要！我的代码有问题吗？
回答by MaxU
I think you want to use pd.to_numeric(x, errors='coerce')instead:
我想你想用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 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:
PS实际上x.astype(dtype = float, errors = 'ignore')- 按预期工作，它不会出错，它只是保留系列，因为它无法转换某些元素：
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', '**.']
