ApJdataFrames Luhman2010Title: The Disk Population of the Taurus Star-Forming Region
Authors: Kevin L Luhman, et al.
Data is from this erratum to this paper: http://iopscience.iop.org/0067-0049/189/2/353/article#apjs363478t1
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%pylab inline
import seaborn as sns
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import warnings
warnings.filterwarnings("ignore")
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import pandas as pd
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names = ['Name_2MASS','Name_alt','[3.6]','[4.5]','[5.8]','[8.0]','Date']
tbl4_pm = pd.read_csv('http://iopscience.iop.org/0067-0049/186/1/111/suppdata/apjs328021t4_ascii.txt',
sep='\t', names=names, skiprows=4, skipfooter=2, index_col=False,na_values=[' ... ', 'out', 'sat'])
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tbl4_pm['NAME'] = tbl4_pm.Name_2MASS
no_name = tbl4_pm.NAME !=tbl4_pm.NAME
tbl4_pm.NAME[no_name] = tbl4_pm.Name_alt[no_name]
tbl4_pm.dropna(axis=0, subset=['NAME'], inplace=True)
tbl4_pm = tbl4_pm.drop(['Name_2MASS', 'Name_alt', 'Date'],axis=1)
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fv = lambda a: a.split(' +or- ')[0] if a == a else np.NaN
fe = lambda a: a.split(' +or- ')[-1] if a == a else np.NaN #awesome little hack here!
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bands = ['[3.6]','[4.5]','[5.8]','[8.0]']
tbl4 = tbl4_pm.drop(bands, axis=1)
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for band in bands:
tbl4[band]=tbl4_pm[band].apply(fv)
tbl4[band+'_e']=tbl4_pm[band].apply(fe)
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names = ['Name_2MASS','Name_alt','Spectral_type','alpha(2-8 mum)',
'alpha(2-24 mum)','alpha(3.6-8 mum)','alpha(3.6-24 mum)','SED']
tbl7_unabridged = pd.read_csv('http://iopscience.iop.org/0067-0049/186/1/111/suppdata/apjs328021t7_ascii.txt',
sep='\t', names = names, skiprows=5, na_values = ' ... ', skipfooter=5,
index_col=False)
tbl7_short = tbl7_unabridged[['Name_2MASS','Name_alt','Spectral_type', 'SED']]
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tbl7_short['NAME'] = tbl7_short.Name_2MASS
no_name = tbl7_short.NAME !=tbl7_short.NAME
tbl7_short.NAME[no_name] = tbl7_short.Name_alt[no_name]
tbl7_short.dropna(axis=0, subset=['NAME'], inplace=True)
tbl7 = tbl7_short.drop(['Name_2MASS', 'Name_alt'],axis=1)
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out = pd.merge(tbl4, tbl7, on='NAME', how='outer')
Do some more data munging.
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has_c = out['Spectral_type'].str.contains('c').values
throw_out = has_c == True
out.drop(out.index[throw_out], inplace=True)
Convert the spectral type to a value.
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from gully_custom import specTypePlus
SpT, _, _, _ = specTypePlus(out['Spectral_type'])
out['SpT'] = SpT
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I1_I4 = out['[3.6]'].astype(float) -out['[8.0]'].astype(float)
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sns.set_context('notebook', font_scale=1.5)
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plt.plot(out.SpT, I1_I4, '.')
plt.xlim(0, 10)
plt.xlabel('Spectral Type (M0 = 0)')
plt.ylabel('$[3.6]-[8.0]$')
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names = ['Spectral Type','J - H','H - K_s','K_s - [3.6]','[3.6] - [4.5]',
'[4.5] - [5.8]','[5.8] - [8.0]','[8.0] - [24]']
tbl13 = pd.read_csv("http://iopscience.iop.org/0067-0049/189/2/353/suppdata/apjs363478t1_ascii.txt",
sep='\t', skiprows=range(4), names = names)
tbl13.drop(0, axis=0, inplace=True)
tbl13.head()
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from gully_custom import specType
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tbl13['SpT'] = specType(tbl13['Spectral Type'])
!!mkdir ../data/Luhman2010
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tbl13.to_csv('../data/Luhman2010/tbl13_fixed_erratrum.csv', index=False)
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out.to_csv('../data/Luhman2010/tbl4_7_merge.csv', index=False)
The end.