Return a pandas.DataFrame instance

The index of the created DataFrame is controlled by the index argument. For index=True or the default None, an index will be specified for the DataFrame if there is a primary key index on the Table and if it corresponds to a single column. If index=False then no DataFrame index will be specified. If index is the name of a column in the table then that will be the DataFrame index.

In addition to vanilla columns or masked columns, this supports Table mixin columns like Quantity, Time, or SkyCoord. In many cases these objects have no analog in pandas and will be converted to a “encoded” representation using only Column or MaskedColumn. The exception is Time or TimeDelta columns, which will be converted to the corresponding representation in pandas using np.datetime64 or np.timedelta64. See the example below.

Parameters¶

indexNone, bool, str

Specify DataFrame index mode

use_nullable_intbool, default=True

Convert integer MaskedColumn to pandas nullable integer type. If use_nullable_int=False or the pandas version does not support nullable integer types (version < 0.24), then the column is converted to float with NaN for missing elements and a warning is issued.

Returns¶

dataframepandas.DataFrame

A pandas pandas.DataFrame instance

Raises¶

ImportError

If pandas is not installed

ValueError

If the Table has multi-dimensional columns

Examples¶

Here we convert a table with a few mixins to a pandas.DataFrame instance.

>>> import pandas as pd
>>> from astropy.table import QTable
>>> import astropy.units as u
>>> from astropy.time import Time, TimeDelta
>>> from astropy.coordinates import SkyCoord

>>> q = [1, 2] * u.m
>>> tm = Time([1998, 2002], format='jyear')
>>> sc = SkyCoord([5, 6], [7, 8], unit='deg')
>>> dt = TimeDelta([3, 200] * u.s)

>>> t = QTable([q, tm, sc, dt], names=['q', 'tm', 'sc', 'dt'])

>>> df = t.to_pandas(index='tm')
>>> with pd.option_context('display.max_columns', 20):
...     print(df)
              q  sc.ra  sc.dec              dt
tm
1998-01-01  1.0    5.0     7.0 0 days 00:00:03
2002-01-01  2.0    6.0     8.0 0 days 00:03:20