# BUG: Mean of zeros turn out to be non-zero

• I have checked that this issue has not already been reported.

• I have confirmed this bug exists on the latest version of pandas.

• (optional) I have confirmed this bug exists on the master branch of pandas.

#### Code Sample, a copy-pastable example

```'''Two examples of a time-weighted rolling average, both of which should result in a final value of 0.'''
import pandas as pd

def succeeding_test():
df = pd.DataFrame(
{"A": [300239975158033.0, -0.0, -0.0]},
index=[
pd.Timestamp("19700101 09:00:00"),
pd.Timestamp("19700101 09:00:03"),
pd.Timestamp("19700101 09:00:06"),
],
)
v = df.resample("1s").ffill().rolling("3s", closed="left", min_periods=3).mean().values[-1]
assert v == 0

def failing_test():
df = pd.DataFrame(
{"A": [3002399751580331.0, -0.0, -0.0]},  # First value is a single digit longer.
index=[
pd.Timestamp("19700101 09:00:00"),
pd.Timestamp("19700101 09:00:03"),
pd.Timestamp("19700101 09:00:06"),
],
)
v = df.resample("1s").ffill().rolling("3s", closed="left", min_periods=3).mean().values[-1]
assert v == 0  # v turns out to be == -0.3333333```

#### Problem description

In both these cases, the final rolling mean value is the mean of three zeros, but in the `failing_test`, this does not result in a zero value. I am expecting the `failing_test` to have the same behaviour as the `succeeding_test`. The difference lies in the magnitude of the first value in the df, but that shouldn’t affect the last mean, as it falls outside the rolling window for that value.

## INSTALLED VERSIONS

commit : f2ca0a2
python : 3.6.9.final.0
python-bits : 64
OS : Linux
OS-release : 5.4.0-42-generic
Version : #46-Ubuntu SMP Fri Jul 10 00:24:02 UTC 2020
machine : x86_64
processor : x86_64
byteorder : little
LC_ALL : None
LANG : en_US.UTF-8
LOCALE : en_US.UTF-8

pandas : 1.1.1
numpy : 1.16.4
pytz : 2020.1
dateutil : 2.8.1
pip : 20.2.2
setuptools : 46.1.1
Cython : None
pytest : 4.6.11
hypothesis : 4.57.1
sphinx : None
blosc : None
feather : None
xlsxwriter : None
lxml.etree : None
html5lib : None
pymysql : None
psycopg2 : 2.8.4 (dt dec pq3 ext lo64)
jinja2 : 2.11.2
IPython : 7.16.1
bs4 : None
bottleneck : None
fsspec : None
fastparquet : None
gcsfs : None
matplotlib : 3.3.1
numexpr : 2.7.1
odfpy : None
openpyxl : None
pandas_gbq : None
pyarrow : 1.0.1
pytables : None
pyxlsb : None
s3fs : None
scipy : 1.4.1
sqlalchemy : 1.3.13
tables : 3.6.1
tabulate : None
xarray : 0.16.0
xlrd : 1.2.0
xlwt : None
numba : 0.47.0