Nullable integer data type bug in read_csv

[AlexanderSpirin]

When reading csv file column with NA fields loose precision. I think the reason of the problem is the cast to float somewhere under hood.

/tmp/1.csv:

field1,field2
,1577134800018164904
1577134800018226901,1577134800018267738

A = pd.read_csv('/tmp/1.csv', dtype='Int64')
A

	field1	field2
0		1577134800018164904
1	1577134800018226944	1577134800018267738

int(float(1577134800018226901))
1577134800018226944

Output of pd.show_versions()

INSTALLED VERSIONS

commit : None
python : 3.6.1.final.0
python-bits : 64
OS : Linux
OS-release : 3.16.0-77-generic
machine : x86_64
processor : x86_64
byteorder : little
LC_ALL : None
LANG : en_US.UTF-8
LOCALE : en_US.UTF-8

pandas : 1.0.1
numpy : 1.18.1
pytz : 2019.3
dateutil : 2.8.1
pip : 20.0.2
setuptools : 28.8.0
Cython : 0.29.14
pytest : None
hypothesis : None
sphinx : None
blosc : None
feather : None
xlsxwriter : None
lxml.etree : None
html5lib : None
pymysql : None
psycopg2 : None
jinja2 : 2.10.3
IPython : 7.12.0
pandas_datareader: None
bs4 : None
bottleneck : None
fastparquet : None
gcsfs : None
lxml.etree : None
matplotlib : 3.1.3
numexpr : None
odfpy : None
openpyxl : None
pandas_gbq : None
pyarrow : None
pytables : None
pytest : None
pyxlsb : None
s3fs : None
scipy : 1.4.1
sqlalchemy : None
tables : None
tabulate : None
xarray : None
xlrd : None
xlwt : None
xlsxwriter : None
numba : 0.48.0

[jorisvandenbossche]

@AlexanderSpirin Thanks for the report!
I think this is caused by #30268, and the actual CSV issue is also reported at #32134

So closing as a duplicate of #32134