Group_by not available for tables with mixin columns [Astropy, Table]
I am trying to run this code:
from astropy.table import Table
from astroquery.nasa_exoplanet_archive import NasaExoplanetArchive
exoplanets = NasaExoplanetArchive.get_confirmed_planets_table()
df=exoplanets.group_by('pl_orbsmax')
print(df)
And get the error:
NotImplementedError: group_by not available for tables with mixin
columns
I want to simply extract data according to entries in specific columns. How can I convert this table to a format where I can use "group_by"?
I tried to restrict the columns to just a few which I am pretty sure are not mixin, eg:
subset=exoplanets['pl_discmethod','pl_orbsmax', 'pl_bmassj', 'st_mass']
but got the same error. I tried to converting to pandas, but that did not work either.
python mixins astropy
asked Jan 2 at 2:50
TheDemonicPenguinTheDemonicPenguin
61
add a comment |
I am trying to run this code:
from astropy.table import Table
from astroquery.nasa_exoplanet_archive import NasaExoplanetArchive
exoplanets = NasaExoplanetArchive.get_confirmed_planets_table()
df=exoplanets.group_by('pl_orbsmax')
print(df)
And get the error:
NotImplementedError: group_by not available for tables with mixin
columns
I want to simply extract data according to entries in specific columns. How can I convert this table to a format where I can use "group_by"?
I tried to restrict the columns to just a few which I am pretty sure are not mixin, eg:
subset=exoplanets['pl_discmethod','pl_orbsmax', 'pl_bmassj', 'st_mass']
but got the same error. I tried to converting to pandas, but that did not work either.
python mixins astropy
asked Jan 2 at 2:50
TheDemonicPenguinTheDemonicPenguin
61
Related to my answer below, I was able to successfully run your example with no errors using astropy 3.1.
– Tom Aldcroft
Jan 2 at 15:52
add a comment |
I am trying to run this code:
from astropy.table import Table
from astroquery.nasa_exoplanet_archive import NasaExoplanetArchive
exoplanets = NasaExoplanetArchive.get_confirmed_planets_table()
df=exoplanets.group_by('pl_orbsmax')
print(df)
And get the error:
NotImplementedError: group_by not available for tables with mixin
columns
I want to simply extract data according to entries in specific columns. How can I convert this table to a format where I can use "group_by"?
I tried to restrict the columns to just a few which I am pretty sure are not mixin, eg:
subset=exoplanets['pl_discmethod','pl_orbsmax', 'pl_bmassj', 'st_mass']
but got the same error. I tried to converting to pandas, but that did not work either.
python mixins astropy
asked Jan 2 at 2:50
TheDemonicPenguinTheDemonicPenguin
61
I am trying to run this code:
from astropy.table import Table
from astroquery.nasa_exoplanet_archive import NasaExoplanetArchive
exoplanets = NasaExoplanetArchive.get_confirmed_planets_table()
df=exoplanets.group_by('pl_orbsmax')
print(df)
And get the error:
NotImplementedError: group_by not available for tables with mixin
columns
I want to simply extract data according to entries in specific columns. How can I convert this table to a format where I can use "group_by"?
I tried to restrict the columns to just a few which I am pretty sure are not mixin, eg:
subset=exoplanets['pl_discmethod','pl_orbsmax', 'pl_bmassj', 'st_mass']
but got the same error. I tried to converting to pandas, but that did not work either.
python mixins astropy
python mixins astropy
asked Jan 2 at 2:50
TheDemonicPenguinTheDemonicPenguin
61
asked Jan 2 at 2:50
TheDemonicPenguinTheDemonicPenguin
61
asked Jan 2 at 2:50
TheDemonicPenguinTheDemonicPenguin
61
asked Jan 2 at 2:50
TheDemonicPenguinTheDemonicPenguin
61
asked Jan 2 at 2:50
TheDemonicPenguinTheDemonicPenguin
61
61
Related to my answer below, I was able to successfully run your example with no errors using astropy 3.1.
– Tom Aldcroft
Jan 2 at 15:52
add a comment |
Related to my answer below, I was able to successfully run your example with no errors using astropy 3.1.
– Tom Aldcroft
Jan 2 at 15:52
Related to my answer below, I was able to successfully run your example with no errors using astropy 3.1.
– Tom Aldcroft
Jan 2 at 15:52
Related to my answer below, I was able to successfully run your example with no errors using astropy 3.1.
– Tom Aldcroft
Jan 2 at 15:52
add a comment |
1 Answer
1
active
oldest
votes
Grouping of mixin columns is implemented as of astropy 3.1:
In [3]: t = Table([[1,2], Time([1,2], format='cxcsec')], names=['x', 'time'])
In [4]: tg = t.group_by('x')
In [5]: tg.groups[1]
Out[5]:
<Table length=1>
x time
int64 object
----- ----------------
2 2.00000000000351
By the way, you can definitively check for mixin columns with the has_mixin_columns property:
In [7]: t.has_mixin_columns
Out[7]: True
answered Jan 2 at 15:46
Tom AldcroftTom Aldcroft
1,305911
add a comment |
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1 Answer
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active
oldest
votes
1 Answer
1
active
oldest
votes
active
oldest
votes
active
oldest
votes
Grouping of mixin columns is implemented as of astropy 3.1:
In [3]: t = Table([[1,2], Time([1,2], format='cxcsec')], names=['x', 'time'])
In [4]: tg = t.group_by('x')
In [5]: tg.groups[1]
Out[5]:
<Table length=1>
x time
int64 object
----- ----------------
2 2.00000000000351
By the way, you can definitively check for mixin columns with the has_mixin_columns property:
In [7]: t.has_mixin_columns
Out[7]: True
answered Jan 2 at 15:46
Tom AldcroftTom Aldcroft
1,305911
add a comment |
Grouping of mixin columns is implemented as of astropy 3.1:
In [3]: t = Table([[1,2], Time([1,2], format='cxcsec')], names=['x', 'time'])
In [4]: tg = t.group_by('x')
In [5]: tg.groups[1]
Out[5]:
<Table length=1>
x time
int64 object
----- ----------------
2 2.00000000000351
By the way, you can definitively check for mixin columns with the has_mixin_columns property:
In [7]: t.has_mixin_columns
Out[7]: True
answered Jan 2 at 15:46
Tom AldcroftTom Aldcroft
1,305911
add a comment |
Grouping of mixin columns is implemented as of astropy 3.1:
In [3]: t = Table([[1,2], Time([1,2], format='cxcsec')], names=['x', 'time'])
In [4]: tg = t.group_by('x')
In [5]: tg.groups[1]
Out[5]:
<Table length=1>
x time
int64 object
----- ----------------
2 2.00000000000351
By the way, you can definitively check for mixin columns with the has_mixin_columns property:
In [7]: t.has_mixin_columns
Out[7]: True
answered Jan 2 at 15:46
Tom AldcroftTom Aldcroft
1,305911
Grouping of mixin columns is implemented as of astropy 3.1:
In [3]: t = Table([[1,2], Time([1,2], format='cxcsec')], names=['x', 'time'])
In [4]: tg = t.group_by('x')
In [5]: tg.groups[1]
Out[5]:
<Table length=1>
x time
int64 object
----- ----------------
2 2.00000000000351
By the way, you can definitively check for mixin columns with the has_mixin_columns property:
In [7]: t.has_mixin_columns
Out[7]: True
answered Jan 2 at 15:46
Tom AldcroftTom Aldcroft
1,305911
answered Jan 2 at 15:46
Tom AldcroftTom Aldcroft
1,305911
answered Jan 2 at 15:46
Tom AldcroftTom Aldcroft
1,305911
answered Jan 2 at 15:46
Tom AldcroftTom Aldcroft
1,305911
1,305911
add a comment |
add a comment |
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Related to my answer below, I was able to successfully run your example with no errors using astropy 3.1.
– Tom Aldcroft
Jan 2 at 15:52