pandas read_csv并将na_values设置为csv文件中的任何字符串 [英] pandas read_csv and setting na_values to any string in the csv file

问题描述

data.csv

data.csv

1，22，3432

1, 22, 3432

1，23，\N

2，24，54335

2, 24, 54335

2，25，3928

2, 25, 3928

我有从设备收集的数据的csv文件。该设备有时不中继信息，而不会输出 outputsN。我想将它们视为NaN并通过

I have a csv file of data that is collected from a device. Every now and then the device doesn't relay information and outputs '\N'. I want to treat these as NaN and did this by doing

read_csv(data.csv, na_values=['\\N']) 

效果很好。但是，我希望不仅将此字符串转换为NaN，而且还要将csv文件中的任何字符串转换为万一，以防万一我将来获得的数据具有不同的字符串。

which worked fine. However, I would prefer to have not only this string turned to NaN but any string that is in the csv file just in case the data I get in the future has a different string.

是我可以对参数进行任何更改，使其覆盖所有字符串吗？

Is it possible to me to make any changes in the argument so it covers all strings?

推荐答案

您必须手动传递所有关键字作为 na_values

You have to manually pass all the keywords as a list or dict to na_values

na_values：类似列表或字典，默认无

na_values : list-like or dict, default None

或者，使用 pd.to_numeric 并将错误设置为 coerce 来转换所有

Alternatively, use pd.to_numeric and set errors to coerce to convert all values to numeric after reading the csv file.

样本输入 df ：

    A   B        
0   1   2         
1   0  \N      
2  \N   8       
3  11   5       
4  11  Kud   

df = df.apply(pd.to_numeric, errors='coerce')

输出：

     A     B        
0    1     2         
1    0   NaN      
2  NaN     8       
3   11     5       
4   11   NaN   

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