I use Pandas to manipulate csv files.
In one of these files, there’s a column called “name and birth date” that contains a string :
<code>id, name and birth date, score
1 , John Doe 20/10/1980, 255
</code>
<code>id, name and birth date, score
1 , John Doe 20/10/1980, 255
</code>
id, name and birth date, score
1 , John Doe 20/10/1980, 255
The dataframe returned by Pandas contains these 3 rows :
<code>id, name and birth date, score
1 , John Doe 20 , 255
1 , 10 , 255
1 , 1980. , 255
</code>
<code>id, name and birth date, score
1 , John Doe 20 , 255
1 , 10 , 255
1 , 1980. , 255
</code>
id, name and birth date, score
1 , John Doe 20 , 255
1 , 10 , 255
1 , 1980. , 255
I really can’t find out how to prevent this. I read the documentation but none of the arguments about dates listed seem to refer to this case.