Closed
Description
Hello!
I'm trying to parse floating point timestamps with pd.to_datetime but the only way that it works is using the deprecated parameter coerce=True
For example, without coerce=True the result is wrong.
>>> pd.to_datetime(1.1, unit='s') # Expected result Timestamp('1970-01-01 00:00:01.100000')
Timestamp('1970-01-01 00:00:01')However, with coerce=True the result is correct.
>>> pd.to_datetime(1.1, unit='s', coerce=True) # Expected result Timestamp('1970-01-01 00:00:01.100000')
Timestamp('1970-01-01 00:00:01.100000')I'm happy to help if you need more details.
Code Sample (copy-pastable example)
import pandas as pd
expected_result = pd.Timestamp('1970-01-01 00:00:01.100000')
timestamp1 = pd.to_datetime(1.1, unit='s')
timestamp2 = pd.to_datetime(1.1, unit='s', coerce=True)
print("Result without coerce: {}".format(timestamp1 == expected_result))
print("Result with coerce: {}".format(timestamp2 == expected_result))pd.show_versions() output
INSTALLED VERSIONS
------------------
commit: None
python: 3.4.3.final.0
python-bits: 64
OS: Linux
OS-release: 3.19.0-65-generic
machine: x86_64
processor: x86_64
byteorder: little
LC_ALL: None
LANG: en_US.UTF-8
pandas: 0.18.1
nose: 1.3.7
pip: 8.1.2
setuptools: 19.2
Cython: 0.24.1
numpy: 1.11.1
scipy: 0.17.0
statsmodels: 0.6.1
xarray: None
IPython: 4.2.0
sphinx: 1.4.1
patsy: 0.4.1
dateutil: 2.5.3
pytz: 2016.6.1
blosc: None
bottleneck: 1.1.0
tables: None
numexpr: 2.5.2
matplotlib: 1.5.1
openpyxl: None
xlrd: 0.9.4
xlwt: 1.0.0
xlsxwriter: None
lxml: None
bs4: 4.4.1
html5lib: 0.999
httplib2: 0.8
apiclient: None
sqlalchemy: None
pymysql: None
psycopg2: 2.6.1 (dt dec pq3 ext lo64)
jinja2: 2.8
boto: None
pandas_datareader: None