Skip to content

DOC: Clarify to_numeric behavior for numeric dtypes #61904

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Merged
Merged
Changes from 1 commit
Commits
File filter

Filter by extension

Filter by extension

Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
6 changes: 4 additions & 2 deletions pandas/core/tools/numeric.py
Original file line number Diff line number Diff line change
Expand Up @@ -55,9 +55,11 @@ def to_numeric(
"""
Convert argument to a numeric type.

The default return dtype is `float64` or `int64`
If the input is already of a numeric dtype, the dtype will be preserved.
For non-numeric inputs, the default return dtype is `float64` or `int64`
depending on the data supplied. Use the `downcast` parameter
to obtain other dtypes.
to obtain other dtypes. Numeric dtypes include all dtypes that have
the `_is_numeric` attribute set to `True`.
Copy link
Member

Choose a reason for hiding this comment

The reason will be displayed to describe this comment to others. Learn more.

_is_numeric is an internal attribute, I do not think we should be mentioning it in the docs. It seems to me this sentence can be removed without loss of clarity.

Copy link
Contributor Author

Choose a reason for hiding this comment

The reason will be displayed to describe this comment to others. Learn more.

Thanks @rhshadrach , resolved in 494aaad


Please note that precision loss may occur if really large numbers
are passed in. Due to the internal limitations of `ndarray`, if
Expand Down
Loading