Skip to content

CLN: minor cleaning of Categorical.__init__ #24402

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.

Sign up for GitHub

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 2 commits into from
Dec 24, 2018
Merged

CLN: minor cleaning of Categorical.__init__ #24402

Changes from all commits
Commits
Show all changes
2 commits
Select commit Hold shift + click to select a range
be3832d
clean Categorical.__init__
topper-123 Dec 23, 2018
f8034cf
change according to comments
topper-123 Dec 23, 2018
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
12 changes: 3 additions & 9 deletions pandas/core/arrays/categorical.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -341,9 +341,6 @@ def __init__(self, values, categories=None, ordered=None, dtype=None,
elif categories is not None or ordered is not None:
raise ValueError("Cannot specify both `dtype` and `categories`"
" or `ordered`.")

categories = dtype.categories

elif is_categorical(values):
# If no "dtype" was passed, use the one from "values", but honor
# the "ordered" and "categories" arguments
Expand All @@ -355,19 +352,17 @@ def __init__(self, values, categories=None, ordered=None, dtype=None,
if (isinstance(values, (ABCSeries, ABCIndexClass)) and
isinstance(values._values, type(self))):
values = values._values.codes.copy()
if categories is None:
categories = dtype.categories
fastpath = True

else:
# If dtype=None and values is not categorical, create a new dtype
dtype = CategoricalDtype(categories, ordered)

# At this point, dtype is always a CategoricalDtype
# At this point, dtype is always a CategoricalDtype and you should not
# use categories and ordered seperately.
# if dtype.categories is None, we are inferring

if fastpath:
self._codes = coerce_indexer_dtype(values, categories)
self._codes = coerce_indexer_dtype(values, dtype.categories)
self._dtype = self._dtype.update_dtype(dtype)
return

Expand All @@ -379,7 +374,6 @@ def __init__(self, values, categories=None, ordered=None, dtype=None,
if is_categorical_dtype(values):
if dtype.categories is None:
dtype = CategoricalDtype(values.categories, dtype.ordered)

elif not isinstance(values, (ABCIndexClass, ABCSeries)):
# sanitize_array coerces np.nan to a string under certain versions
# of numpy
Expand Down