In [1]:

    

%matplotlib inline
import matplotlib.pyplot as plt
import seaborn as sns
import pandas as pd
pd.options.display.max_columns = 150


    

In [2]:

    

#%config InlineBackend.figure_format = 'retina'


    

In [3]:

    

import astropy
from astropy.table import Table
from astropy.io import ascii


    

In [4]:

    

from IPython.core.display import display, HTML
display(HTML("<style>.container { width:100% !important; }</style>"))


    

In [5]:

    

#! mkdir ../data/Kraus2017


    

In [6]:

    

#! wget -q --directory-prefix=../data/Kraus2017/ http://iopscience.iop.org/0004-637X/838/2/150/suppdata/apjaa62a0t1_mrt.txt
#! wget -q --directory-prefix=../data/Kraus2017/ http://iopscience.iop.org/0004-637X/838/2/150/suppdata/apjaa62a0t2_mrt.txt
#! wget -q --directory-prefix=../data/Kraus2017/ http://iopscience.iop.org/0004-637X/838/2/150/suppdata/apjaa62a0t3_mrt.txt
#! wget -q --directory-prefix=../data/Kraus2017/ http://iopscience.iop.org/0004-637X/838/2/150/suppdata/apjaa62a0t4_mrt.txt
#! wget -q --directory-prefix=../data/Kraus2017/ http://iopscience.iop.org/0004-637X/838/2/150/suppdata/apjaa62a0t5_mrt.txt
#! wget -q --directory-prefix=../data/Kraus2017/ http://iopscience.iop.org/0004-637X/838/2/150/suppdata/apjaa62a0t6_mrt.txt
#! wget -q --directory-prefix=../data/Kraus2017/ http://iopscience.iop.org/0004-637X/838/2/150/suppdata/apjaa62a0t7_mrt.txt


    

In [7]:

    

! ls -1 ../data/Kraus2017/


    

    




apjaa62a0t1_mrt.txt
apjaa62a0t2_mrt.txt
apjaa62a0t3_mrt.txt
apjaa62a0t4_mrt.txt
apjaa62a0t5_mrt.txt
apjaa62a0t6_mrt.txt
apjaa62a0t7_mrt.txt

In [8]:

    

! head ../data/Kraus2017/apjaa62a0t7_mrt.txt


    

    




Title: The Greater Taurus-Auriga Ecosystem I: There is a Distributed Older 
       Population 
Authors: Kraus A.L., Herczeg G.J., Rizzuto A.C., Mann A.W., Slesnick C.L., 
         Carpenter J.M., Hillenbrand L.A., Mamajek E.E. 
Table: Na8189 Indices for Candidate Class III Taurus Members of Herczeg & 
    Hillenbrand (2014ApJ...786...97H) 
================================================================================
Byte-by-byte Description of file: apjaa62a0t7_mrt.txt
--------------------------------------------------------------------------------
   Bytes Format Units Label   Explanations

In [9]:

    

tab1 = ascii.read('../data/Kraus2017/apjaa62a0t1_mrt.txt')


    

In [18]:

    

#tab1.show_in_notebook(display_length=5)


    

In [11]:

    

#tab1.write('../data/Kraus2017/tab1.csv', format='ascii.csv', overwrite=True)


    

In [12]:

    

tab5 = ascii.read('../data/Kraus2017/apjaa62a0t5_mrt.txt')


    

In [13]:

    

df1, df5 = tab1.to_pandas(), tab5.to_pandas()


    

In [14]:

    

df1.head()


    

    
Out[14]:







  

    

      

      
2MASS
      
Name
      
SpT
      
r_SpT
      
Avmag
      
r_Avmag
      
rpmag
      
r_rpmag
      
Ksmag
      
pmRA
      
pmDE
      
e_pm
      
r_pm
      
BinRef
    
  
  

    

      
0
      
J03500343+2235300
      
[LH98] 106
      
G0
      
26.0
      
2.4
      
11
      
8.77
      
8
      
6.04
      
156.9
      
-60.6
      
1.0
      
1
      
NaN
    
    

      
1
      
J03502840+1631151
      
[LH98] 108
      
G5
      
26.0
      
0.5
      
11
      
10.38
      
7,8
      
8.63
      
27.3
      
-26.9
      
0.6
      
1
      
NaN
    
    

      
2
      
J03505432+2350056
      
[LH98] 110
      
G7
      
26.0
      
0.8
      
11
      
11.08
      
7,8
      
9.05
      
19.3
      
-45.4
      
0.7
      
1
      
NaN
    
    

      
3
      
J03520223+2439479
      
HBC351
      
K5
      
14.0
      
0.0
      
14
      
11.63
      
7,8
      
9.07
      
17.4
      
-47.4
      
1.7
      
1
      
37
    
    

      
4
      
J03533134+2631411
      
[LH98] 117
      
G7
      
26.0
      
1.4
      
11
      
11.62
      
7,8
      
9.24
      
21.4
      
-45.3
      
1.3
      
1
      
NaN
    
  

In [15]:

    

df5.head()


    

    
Out[15]:







  

    

      

      
2MASS
      
Name
      
Epoch
      
Tint
      
SNR
      
EWHa
      
EWLi
      
RVel
      
e_RVel
      
vsini
      
e_vsini
    
  
  

    

      
0
      
04072456+2332553
      
[SCH2006b] J0407246+2332554
      
20061212
      
1800
      
24
      
-5.5
      
0
      
11.8
      
0.5
      
14.2
      
0.6
    
    

      
1
      
04073502+2237394
      
[SCH2006b] J0407350+2237396
      
20061213
      
1800
      
21
      
-16.4
      
612
      
15.4
      
2.5
      
97.3
      
3.5
    
    

      
2
      
04162725+2053091
      
[SCH2006b] J0416272+2053093
      
20061213
      
1800
      
20
      
-4.0
      
561
      
19.3
      
0.5
      
14.3
      
0.6
    
    

      
3
      
04270739+2215037
      
[SCH2006b] J0427074+2215039
      
20061213
      
1800
      
9
      
-15.5
      
443
      
16.8
      
0.6
      
14.9
      
0.7
    
    

      
4
      
04295950+2433078
      
[SCH2006b] J0429595+2433080
      
20061213
      
1800
      
6
      
-83.2
      
307
      
19.3
      
0.8
      
18.4
      
1.0
    
  

In [16]:

    

df1.shape


    

    
Out[16]:





(396, 14)

In [17]:

    

df5.shape


    

    
Out[17]:





(35, 11)