dt.total_seconds() stores float with appending 0.00000000000001
Simple test to show that if I have two datetime columns and use dt.total_seconds() to calc the difference, values are stored with an offset of 0.00000000000001.

```
print(pd.__version__)
print(pd.show_versions())
1.0.3

INSTALLED VERSIONS
------------------
commit           : None
python           : 3.8.0.final.0
python-bits      : 64
OS               : Linux
OS-release       : 3.10.0-1062.18.1.el7.x86_64
machine          : x86_64
processor        : x86_64
byteorder        : little
LC_ALL           : None
LANG             : en_US.UTF-8
LOCALE           : en_US.UTF-8

pandas           : 1.0.3
numpy            : 1.18.3
pytz             : 2019.3
dateutil         : 2.8.1
pip              : 20.0.2
setuptools       : 41.4.0
Cython           : 0.29.16
pytest           : 5.4.1
hypothesis       : None
sphinx           : None
blosc            : None
feather          : None
xlsxwriter       : None
lxml.etree       : None
html5lib         : None
pymysql          : None
psycopg2         : None
jinja2           : 2.11.2
IPython          : 7.13.0
pandas_datareader: None
bs4              : None
bottleneck       : None
fastparquet      : None
gcsfs            : None
lxml.etree       : None
matplotlib       : 3.2.1
numexpr          : 2.7.1
odfpy            : None
openpyxl         : 3.0.3
pandas_gbq       : None
pyarrow          : None
pytables         : None
pytest           : 5.4.1
pyxlsb           : None
s3fs             : None
scipy            : 1.4.1
sqlalchemy       : 1.3.16
tables           : 3.6.1
tabulate         : None
xarray           : None
xlrd             : None
xlwt             : None
xlsxwriter       : None
numba            : None
```

iPython code:

```
import pandas as pd
import datetime

data = {'start':datetime.datetime(2020,1,1,12),
       'end':datetime.datetime(2020,1,1,12,2) 
       }

df = pd.DataFrame(data,index=[0])

#try to parse to pd.to_datetime
df['end'] = pd.to_datetime(df['end'])
df['start'] = pd.to_datetime(df['start'])

print('print calc differences')
print((df['end'] - df['start']).dt.total_seconds())
print((df['end'] - df['start']).dt.total_seconds().values[0])
print('')

print('testing on normal float')
print(float(120))
print('')

```

Output:

```
print calc differences
0    120.0
dtype: float64
120.00000000000001

testing on normal float
120.0
```





