to_numeric with errors = "coerce" is adding digits at the end
#### Code Sample, a copy-pastable example if possible

```python
# Your code here
#problem: pandas to_numeric might give some errors when using coerce 
# it is adding digits at the end.

import pandas as pd


#minimal example
data = [{'value': '.'}, {'value': '.'}, {'value': '.'}, {'value': '.'}, {'value': '243.164'}, {'value': '245.968'}, {'value': '249.585'}, {'value': '259.745'}, {'value': '265.742'}, {'value': '272.567'}]
df = pd.DataFrame(data,columns=['value'])

df.value = pd.to_numeric(df.value,errors='coerce')

#looks as if all is good:
df.value 

#but
df.value[4]


#this can be random:
data2 = [{'value': '.'}, {'value': '.'}, {'value': '.'}, {'value': '.'}, {'value': '243.164'}, {'value': '245.968'}, {'value': '249.585'}, {'value': '259.745'}, {'value': '265.742'}, {'value': '272.567'}, {'value': '279.196'}, {'value': '280.366'}, {'value': '275.034'}, {'value': '271.351'}, {'value': '272.889'}, {'value': '270.627'}, {'value': '280.828'}, {'value': '290.383'}, {'value': '308.153'}, {'value': '319.945'}, {'value': '336.0'}, {'value': '344.09'}, {'value': '351.385'}, {'value': '356.178'}, {'value': '359.82'}, {'value': '361.03'}, {'value': '367.701'}, {'value': '380.812'}, {'value': '387.98'}, {'value': '391.749'}, {'value': '391.171'}, {'value': '385.97'}, {'value': '385.345'}, {'value': '386.121'}, {'value': '390.996'}, {'value': '399.734'}, {'value': '413.073'}, {'value': '421.532'}, {'value':
'430.221'}, {'value': '437.092'}, {'value': '439.746'}, {'value': '446.01'}, {'value': '451.191'}, {'value': '460.463'}, {'value': '469.779'}, {'value': '472.025'}, {'value': '479.49'}, {'value': '474.864'}, {'value': '467.54'}, {'value': '471.978'}]


#now 4, 36, and 47 are wrong, with different endings.
df2 = pd.DataFrame(data2,columns=['value'])

df2.value = pd.to_numeric(df2.value,errors='coerce')


df2.value[[4,36,47]].to_list()
```
#### Problem description

Current behavior:  pandas to_numeric, when using errors='coerce' seem to randomly add 
decimals at the end of the number. 

#### Expected Output

no decimals should be added at the end.

#### Output of ``pd.show_versions()``

<details>

[paste the output of ``pd.show_versions()`` here below this line]


INSTALLED VERSIONS
------------------
commit           : None
python           : 3.7.3.final.0
python-bits      : 64
OS               : Windows
OS-release       : 10
machine          : AMD64
processor        : Intel64 Family 6 Model 85 Stepping 4, GenuineIntel
byteorder        : little
LC_ALL           : None
LANG             : en_US.UTF-8
LOCALE           : None.None

pandas           : 0.25.3
numpy            : 1.16.4
pytz             : 2019.1
dateutil         : 2.8.0
pip              : 19.1.1
setuptools       : 41.0.1
Cython           : 0.29.12
pytest           : 5.0.1
hypothesis       : None
sphinx           : 2.1.2
blosc            : None
feather          : None
xlsxwriter       : 1.1.8
lxml.etree       : 4.3.4
html5lib         : 1.0.1
pymysql          : None
psycopg2         : None
jinja2           : 2.10.1
IPython          : 7.6.1
pandas_datareader: 0.7.4
bs4              : 4.7.1
bottleneck       : 1.2.1
fastparquet      : None
gcsfs            : None
lxml.etree       : 4.3.4
matplotlib       : 3.1.2
numexpr          : 2.6.9
odfpy            : None
openpyxl         : 2.6.2
pandas_gbq       : None
pyarrow          : 0.15.1
pytables         : None
s3fs             : None
scipy            : 1.2.1
sqlalchemy       : 1.3.5
tables           : 3.5.2
xarray           : 0.12.3
xlrd             : 1.2.0
xlwt             : 1.3.0
xlsxwriter       : 1.1.8
</details>
