Comments (6)
If your CSV file has the columns col1
, col2
, col3
, and you passed names=['name1', 'name2', 'name3']
, then, passing usecols=['name1', 'name3']
will work correctly.
Can you share why you think it's inconsistent? If you passed names
then it makes sense that usecols
will rely on those names rather than the names in the CSV header row, do you agree?
from pandas.
Thanks for the report! The documentation states: "If names
are given, the document header row(s) are not taken into account" which is the current behavior, so this sounds more to me like an enhancement request than a bug report, is that right?
from pandas.
I think this is a discrepancy to the other referenced sentence see my report, in the documentation.
Quote:"For example, a valid list-like usecols parameter would be [0, 1, 2] or ['foo', 'bar', 'baz']."
Therefore I assume usecols works with both, what "or" said.
Usecols is for read the csv, names is for representation of the result, if I understood it right. So in my opinion it's a bug, because it's not working with both as described into the documentation.
from pandas.
Well yes, you can pass a list of the column names just as the documentation states. But it also states that if names
are provided then the header row won't be considered.
from pandas.
Stupid behavior. Not consistent in my opinion.
from pandas.
That works I agree, but in a use case where you have 25 columns in the input csv and you need only the 1st and maybe the 23th, you have to name 25 new columns that you can usecols by column name (what's still in the csv). I think this is ineffective.
from pandas.
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from pandas.