Description
Code Sample, a copy-pastable example if possible
import pandas as pd
import io
dat = """s1;s2
1000;2000
3000;1500
500"""
df = pd.read_csv(io.StringIO(dat), sep=";")
df.index = df.index + 1
df = df.apply(lambda x: pd.to_timedelta(x, unit='ms'))
df['laptime'] = df.sum(axis=1, skipna=False)
print(df)Problem description
This code displays
s1 s2 laptime
1 00:00:01 00:00:02 0 days 00:00:03
2 00:00:03 00:00:01.500000 0 days 00:00:04.500000
3 00:00:00.500000 NaT -106752 days +00:12:43.645223
In [81]: df['laptime'][3]
Out[81]: Timedelta('-106752 days +00:12:43.645223')
Expected Output
s1 s2 laptime
1 00:00:01 00:00:02 0 days 00:00:03
2 00:00:03 00:00:01.500000 0 days 00:00:04.500000
3 00:00:00.500000 NaT NaT
In [81]: df['laptime'][3]
Out[81]: NaT
That's very strange because pd.to_timedelta(500, unit='ms') + pd.NaT returns NaT (which is expected) but it's doesn't work as expected when summing Series)
Output of pd.show_versions()
: pd.show_versions()
/Users/scls/anaconda/lib/python3.6/site-packages/xarray/core/formatting.py:16: FutureWarning: The pandas.tslib module is deprecated and will be removed in a future version.
from pandas.tslib import OutOfBoundsDatetime
INSTALLED VERSIONS
commit: None
python: 3.6.1.final.0
python-bits: 64
OS: Darwin
OS-release: 16.7.0
machine: x86_64
processor: i386
byteorder: little
LC_ALL: None
LANG: fr_FR.UTF-8
LOCALE: fr_FR.UTF-8
pandas: 0.20.1
pytest: 3.1.2
pip: 9.0.1
setuptools: 27.2.0
Cython: 0.25.2
numpy: 1.12.1
scipy: 0.19.0
xarray: 0.9.5
IPython: 5.3.0
sphinx: 1.5.6
patsy: 0.4.1
dateutil: 2.6.0
pytz: 2017.2
blosc: None
bottleneck: 1.2.1
tables: 3.3.0
numexpr: 2.6.2
feather: None
matplotlib: 2.0.2
openpyxl: 2.4.7
xlrd: 1.0.0
xlwt: 1.2.0
xlsxwriter: 0.9.6
lxml: 3.7.3
bs4: 4.6.0
html5lib: 0.999
sqlalchemy: 1.1.9
pymysql: None
psycopg2: None
jinja2: 2.9.6
s3fs: None
pandas_gbq: None
pandas_datareader: 0.5.0