Pandas to_sql doesn't support decimal types - stored as text in database

I am using postgresql database

Code Sample, a copy-pastable example if possible

a=pd.DataFrame({'a':[decimal.Decimal('0.1'), decimal.Decimal('0.1'), decimal.Decimal('0.1'), decimal.Decimal('0.3')]})

Expected Output

conn is sql alchemy connection a.to_sql('testdec',conn) what is produced: CREATE TABLE testdec ( index bigint, a text ) I would have expected the use of decimal type?

output of pd.show_versions()

INSTALLED VERSIONS

commit: None python: 2.7.11.final.0 python-bits: 64 OS: Windows OS-release: 10 machine: AMD64 processor: Intel64 Family 6 Model 60 Stepping 3, GenuineIntel byteorder: little LC_ALL: None LANG: de_DE

pandas: 0.18.0 nose: 1.3.7 pip: 8.1.1 setuptools: 20.3 Cython: 0.23.4 numpy: 1.10.4 scipy: 0.17.0 statsmodels: 0.6.1 xarray: None IPython: 4.1.2 sphinx: 1.3.5 patsy: 0.4.0 dateutil: 2.5.1 pytz: 2016.2 blosc: None bottleneck: 1.0.0 tables: 3.2.2 numexpr: 2.5 matplotlib: 1.5.1 openpyxl: 2.3.2 xlrd: 0.9.4 xlwt: 1.0.0 xlsxwriter: 0.8.4 lxml: 3.6.0 bs4: 4.4.1 html5lib: None httplib2: None apiclient: None sqlalchemy: 1.0.12 pymysql: None psycopg2: 2.5.1 (dt dec pq3 ext) jinja2: 2.8 boto: 2.39.0

Comment From: jreback

we don't support decimal types in pandas generally, so I woudn't expect this to be supported. you can however, specify the dtype keyword.