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ApJdataFrames Muzic2012

Title: Substellar Objects in Nearby Young Clusters (SONYC). V. New Brown Dwarfs in ρ Ophiuchi
Authors: Muzic et al.

Data is from this paper:
http://iopscience.iop.org/0004-637X/744/2/134/





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

Table 1 - Parameters of ρ Oph M-type Objects Observed with FMOS/Subaru and SINFONI/VLT





In [3]:



    


addr = "http://iopscience.iop.org/0004-637X/744/2/134/suppdata/apj408590t1_ascii.txt"
names = ["ID","RA", "DEC", "ins", "A_V_phot","A_V","T_eff","SpT","Ref","Name"]
tbl1 = pd.read_csv(addr, sep='\t', skiprows=10, skipfooter=8, index_col=False,
                   engine='python', na_values=r" ... ", names = names)
tbl1.T_eff = tbl1.T_eff.str.replace(">or=", '')
tbl1



    


















    
Out[3]:










  
    

      
      ID
      RA
      DEC
      ins
      A_V_phot
      A_V
      T_eff
      SpT
      Ref
      Name
    

  
  
    

      0 
        1
       16 26 03.28
       -24 30 25.8
       F
        8.4
       10
       2650
                  NaN
         NaN
                       SONYC-RhoOph-7
    

    

      1 
        2
       16 27 05.93
       -24 18 40.2
       F
        7.8
        8
       2700
                  NaN
         NaN
                       SONYC-RhoOph-6
    

    

      2 
        3
       16 27 38.63
       -24 38 39.2
       F
        6.6
        8
       2750
         M8.5, M7, M6
       1 2 3
                                GY310
    

    

      3 
        4
       16 26 22.27
       -24 24 07.1
       F
        9.7
        8
       2750
           M6.5, M8.5
         1 3
                                 GY11
    

    

      4 
        4
       16 26 22.27
       -24 24 07.1
       S
        9.7
       12
       2800
           M6.5, M8.5
         1 3
                                 GY11
    

    

      5 
        5
       16 26 18.82
       -24 26 10.5
       F
        9.4
       10
       2850
       M7.5, M5.5, M7
       1 2 3
                  CRBR 14; ISO-Oph-23
    

    

      6 
        6
       16 26 18.98
       -24 24 14.3
       F
       17.6
       16
       2850
                   M5
         1 2
                              CRBR 15
    

    

      7 
        7
       16 26 22.96
       -24 28 46.1
       F
       13.2
       14
       2900
                  NaN
         NaN
                       SONYC-RhoOph-5
    

    

      8 
        8
       16 26 51.28
       -24 32 42.0
       F
        2.3
        2
       2900
             M8, M8.5
         5 4
                                GY141
    

    

      9 
        9
       16 26 53.35
       -24 40 02.3
       F
       12.4
       13
       3000
                  NaN
         NaN
                       SONYC-RhoOph-3
    

    

      10
       10
       16 26 22.19
       -24 23 52.4
       F
       13.8
       14
       3100
           M8.5, M6.5
         1 2
                                 GY10
    

    

      11
       11
       16 26 27.81
       -24 26 41.8
       F
        6.4
        6
       3200
               M5, M6
         6 1
                                 GY37
    

    

      12
       11
       16 26 27.81
       -24 26 41.8
       S
        6.4
        6
       3100
               M5, M6
         6 1
                                 GY37
    

    

      13
       12
       16 26 18.14
       -24 30 33.0
       F
       14.7
       13
       3200
                  NaN
         NaN
                       SONYC-RhoOph-4
    

    

      14
       13
       16 27 46.29
       -24 31 41.2
       F
        8.3
        9
       3200
                   M6
           3
                                GY350
    

    

      15
       14
       16 27 40.84
       -24 29 00.7
       S
        3.1
        3
       2550
                M8.25
           7
                        CFHTWIR-Oph96
    

    

      16
       15
       16 26 18.58
       -24 29 51.4
       S
       15.0
       18
       2600
                  NaN
         NaN
        SONYC-RhoOph-8, CFHTWIR-Oph16
    

    

      17
       16
       16 27 26.58
       -24 25 54.4
       S
        0.9
        2
       2650
                   M8
           6
                                GY264
    

    

      18
       17
       16 27 26.22
       -24 19 23.0
       S
       13.6
       15
       2800
                  NaN
         NaN
       SONYC-RhoOph-10; CFHTWIR-Oph78
    

    

      19
       18
       16 26 37.81
       -24 39 03.2
       S
        6.2
        6
       3100
                  NaN
         NaN
        SONYC-RhoOph-9; CFHTWIR-Oph31
    

    

      20
       19
       16 27 06.60
       -24 41 48.8
       S
        3.7
        6
       3150
             M5.5, M6
         6 3
                                GY204
    

    

      21
       20
       16 26 23.81
       -24 18 29.0
       S
        8.2
       10
       3200
             M6.7, M7
         5 8
                              CRBR 31

Table 2. Spectral Types Calculated from the SINFONI Spectra





In [4]:



    


addr = "http://iopscience.iop.org/0004-637X/744/2/134/suppdata/apj408590t2_ascii.txt"
names = ["ID","SpT_HPI", "SpT_Q", "SpT_H_2O"]
tbl2 = pd.read_csv(addr, sep='\t', skiprows=8, skipfooter=5, index_col=False,
                   engine='python', na_values=r" ... ", names = names)
tbl2



    


















    
Out[4]:










  
    

      
      ID
      SpT_HPI
      SpT_Q
      SpT_H_2O
    

  
  
    

      0 
        1
               M9.7
        NaN
               M9.6
    

    

      1 
        2
               M8.6
        NaN
               M6.9
    

    

      2 
        3
               M8.3
        NaN
               M6.6
    

    

      3 
        4
         M8.5, M8.0
       M6.1
         M6.6, M7.8
    

    

      4 
        5
               M8.5
        NaN
               M8.0
    

    

      5 
        6
               M8.0
        NaN
               M5.7
    

    

      6 
        7
               M7.4
        NaN
               M5.7
    

    

      7 
        8
               M8.0
        NaN
               M6.3
    

    

      8 
        9
               M7.5
        NaN
               M5.1
    

    

      9 
       10
               M7.4
        NaN
               M5.5
    

    

      10
       11
       <or=M7, M7.1
       M5.8
       <or=M5, M5.8
    

    

      11
       12
               M7.0
        NaN
               M5.0
    

    

      12
       13
               M7.1
        NaN
             <or=M5
    

    

      13
       14
               M9.3
       M7.1
                NaN
    

    

      14
       15
               M9.1
       M8.7
               M8.0
    

    

      15
       16
               M8.6
       M8.0
               M8.0
    

    

      16
       17
               M7.8
       M6.2
               M8.4
    

    

      17
       18
               M7.0
       M6.8
               M5.4
    

    

      18
       19
               M7.1
       M5.9
               M6.4
    

    

      19
       20
               M7.0
       M6.6
               M5.7
    

    

      20
       21
             <or=M7
        NaN
             <or=M5

Need to parse these strings if I'm going to use this data.

Save data.





In [5]:



    


!mkdir ../data/Muzic2012



    


















    






mkdir: ../data/Muzic2012: File exists

















In [6]:



    


tbl1.to_csv("../data/Muzic2012/tbl1.csv", sep='\t', index=False)

Script finished.

Content source: BrownDwarf/ApJdataFrames

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