Skip to content

modified changes for datetime and NaT Objects Behavior closes #43280 #43289

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

Closed
wants to merge 4 commits into from
+35 −2
Closed

modified changes for datetime and NaT Objects Behavior closes #43280 #43289

Changes from 2 commits
Commits
Show all changes
4 commits
Select commit Hold shift + click to select a range
4a8fbc8
modified changes for datetime and NaT Objects Behavior
Navaneethan2503 Aug 29, 2021
2e082a1
Scalar and series argument of datatime datatype and NaT Behaviour solved
Navaneethan2503 Aug 30, 2021
0db0265
added test and release notes
Navaneethan2503 Aug 31, 2021
a4ae1cc
changed indentation error and tests
Navaneethan2503 Aug 31, 2021
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
20 changes: 19 additions & 1 deletion pandas/core/tools/numeric.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -130,6 +130,19 @@ def to_numeric(arg, errors="raise", downcast=None):
1 2.1
2 3.0
dtype: Float32

Datetime dTypes is supported

>>> s = pd.to_numeric(datetime(2021, 8, 22), errors="coerce")
0 20210822
dtype: Int64
>>> s = pd.to_numeric(pd.NaT, errors="coerce")
nan
>>> s = pd.to_numeric(pd.Series(datetime(2021, 8, 22)), errors="coerce")
0 20210822
dtype: Int64
>>> s = pd.to_numeric(pd.Series(pd.NaT), errors="coerce")
NaN
"""
if downcast not in (None, "integer", "signed", "unsigned", "float"):
raise ValueError("invalid downcasting method provided")
Expand Down Expand Up @@ -157,6 +170,11 @@ def to_numeric(arg, errors="raise", downcast=None):
return float(arg)
if is_number(arg):
return arg
if isinstance(arg , datetime):
if pd.isnull(arg):
return np.NaN
else:
return int(pd.to_datetime(arg).strftime("%Y%m%d"))
is_scalars = True
values = np.array([arg], dtype="O")
elif getattr(arg, "ndim", 1) > 1:
Expand All @@ -175,7 +193,7 @@ def to_numeric(arg, errors="raise", downcast=None):
if is_numeric_dtype(values_dtype):
pass
elif is_datetime_or_timedelta_dtype(values_dtype):
values = values.view(np.int64)

else:
values = ensure_object(values)
coerce_numeric = errors not in ("ignore", "raise")
Expand Down