Closed
Description
Code Sample, a copy-pastable example if possible
import pandas as pd
from datetime import datetime
dates = [pd.Timestamp('2012-01-01'), pd.Timestamp('2017-01-02'), pd.Timestamp('2017-01-03')]
df = pd.DataFrame({'dates': dates})
today = datetime.today().date()
print(df['dates'] == today)Traceback (most recent call last):
File "date_bug.py", line 22, in <module>
main()
File "date_bug.py", line 18, in main
print(df['dates'] == today)
File "/Users/discort/python/projects/pims/env/lib/python3.5/site-packages/pandas/core/ops.py", line 879, in wrapper
res = na_op(values, other)
File "/Users/discort/python/projects/pims/env/lib/python3.5/site-packages/pandas/core/ops.py", line 808, in na_op
y = libindex.convert_scalar(x, _values_from_object(y))
File "pandas/_libs/index.pyx", line 494, in pandas._libs.index.convert_scalar
File "pandas/_libs/index.pyx", line 509, in pandas._libs.index.convert_scalar
ValueError: cannot set a Timestamp with a non-timestamp
Problem description
There is a regression. Related: #17965
On 0.18.1 it works fine
Expected Output
0 False
1 False
2 False
Name: dates, dtype: bool
Output of pd.show_versions()
INSTALLED VERSIONS
commit: None
pandas: 0.21.0
pytest: 2.9.2
pip: 9.0.1
setuptools: 36.4.0
Cython: None
numpy: 1.13.3
scipy: None
pyarrow: None
xarray: None
IPython: 6.1.0
sphinx: None
patsy: None
dateutil: 2.6.1
pytz: 2017.3
blosc: None
bottleneck: None
tables: None
numexpr: None
feather: None
matplotlib: None
openpyxl: None
xlrd: None
xlwt: None
xlsxwriter: None
lxml: None
bs4: None
html5lib: None
sqlalchemy: None
pymysql: None
psycopg2: None
jinja2: None
s3fs: None
fastparquet: None
pandas_gbq: None
pandas_datareader: None