`ApJdataFrames` Schlieder2012

Title: THE Na 8200 Å DOUBLET AS AN AGE INDICATOR IN LOW-MASS STARS
Authors: Joshua E Schlieder, Sebastien Lepine, Emily Rice, Michal Simon, Drummond Fielding, and Rachael Tomasino

Data is from this paper:
http://iopscience.iop.org/1538-3881/143/5/114/article



In [1]:

    
%pylab inline

import seaborn as sns
sns.set_context("notebook", font_scale=1.5)

import warnings
warnings.filterwarnings("ignore")









    



Populating the interactive namespace from numpy and matplotlib



In [2]:

    
import pandas as pd



In [3]:

    
from astropy.io import ascii

Table 1 - Giant Standards



In [4]:

    
tbl1 = pd.read_csv("http://iopscience.iop.org/1538-3881/143/5/114/suppdata/aj424365t1_ascii.txt", 
                   skipfooter=2, skiprows=[0,1,2,4], sep='\t')
tbl1.drop("Unnamed: 7", axis=1, inplace=True)
tbl1

Table 2 - BPMG members



In [5]:

    
tbl2 = pd.read_csv("http://iopscience.iop.org/1538-3881/143/5/114/suppdata/aj424365t2_ascii.txt", 
                   skipfooter=5, skiprows=[0,1,2,4], sep='\t')
tbl2.drop("Unnamed: 7", axis=1, inplace=True)
tbl2









    Out[5]:






  
    
      
      Name
      alpha^a
      delta^a
      V
      K_s
      SpTy
      EW
    
  
  
    
      0 
        TYC 1208 468 1^b
        24.414167
       18.592500
       10.7
       6.7
       K7V
       1.6
    
    
      1 
             HIP 11152^b
        35.860833
       22.735278
       11.6
       7.3
       M1V
       2.1
    
    
      2 
                AG Tri^c
        36.872083
       30.973611
       10.2
       7.1
       K7V
       1.7
    
    
      3 
             BD+05 378^c
        40.357917
        5.988333
       10.2
       7.1
       K7V
       1.7
    
    
      4 
        PM I04439+3723^b
        70.987083
       37.384250
       13.4
       8.8
       M2V
       3.1
    
    
      5 
            V 1005 Ori^c
        74.895000
        1.783611
       10.3
       6.3
       M0V
       2.0
    
    
      6 
       TYC 1281 1672 1^b
        75.205375
       15.450194
       11.0
       7.6
       K7V
       1.8
    
    
      7 
       PYC J05019+0108^d
        75.485625
        1.145250
       13.2
       7.7
       M5V
       3.3
    
    
      8 
            V 1311 Ori^c
        83.018750
       -3.091389
       11.4
       7.0
       M2V
       2.7
    
    
      9 
        PM I07295+3556^b
       112.379500
       35.933389
       12.1
       7.8
       M1V
       2.5
    
    
      10
       PYC J21376+0137^d
       324.417500
        1.620556
       13.6
       7.9
       M5V
       3.6
    
    
      11
            BD-13 6424^c
       353.128750
      -12.264444
       10.9
       6.6
       M0V
       2.2

Table 4 - Model derived EWs



In [ ]:

    
tbl4 = pd.read_csv("http://iopscience.iop.org/1538-3881/143/5/114/suppdata/aj424365t4_ascii.txt",
                   skipfooter=3, skiprows=[0,1,2,3,5], sep='\t', na_values="sdotsdotsdot")
tbl4.drop("Unnamed: 5", axis=1, inplace=True)

1 Gyr model



In [21]:

    
tbl4_1Gyr = tbl4[36:]
tbl4_1Gyr

5 Myr model



In [33]:

    
mass_bins = [0.5, 0.3, 0.2, 0.1] #Solar masses
tbl4_5Myr = tbl4[(tbl4.Age == "5")] 
tbl4_5Myr["Mass"] = mass_bins
tbl4_5Myr

Script finished.

	Name	alpha^a	delta^a	V	K_s	SpTy	EW
0	HD 1879	5.768131	-15.942617	6.5	2.3	M2III	1.8
1	HD 27598	65.172214	-16.830004	7.1	1.8	M4III	1.8
2	HD 198026	311.934330	-5.027603	4.5	-0.3	M3III	1.3
3	HD 207076	326.632640	-2.212806	6.8	-1.7	M7III	0.6

	Age	T_eff	log(g)	EW	(V - K)^b
36	M0	3804	4.9	1.9	3.7
37	M2	3669	5.0	2.8	4.5
38	M4	3290	5.1	4.2	5.6
39	M6	2780	5.3	NaN	NaN

	Age	T_eff	log(g)	EW	(V - K)^b	Mass
2	5	3760	4.0	1.7	3.8	0.5
10	5	3429	4.0	1.9	4.9	0.3
18	5	3235	4.0	2.3	6.2	0.2
26	5	3023	4.0	3.0	7.5	0.1