Pandas Read_csv And Setting Na_values To Any String In The Csv File

data.csv 1, 22, 3432 1, 23, \N 2, 24, 54335 2, 25, 3928 I have a csv file of data that is collected from a device. Every now and then the device doesn't relay information and out

Solution 1:

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

na_values : list-like or dict, default None

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

sample input 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')

output:

     A     B        
01210NaN2NaN83115411NaN