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ApJdataFrames Muzic2015

Title: SUBSTELLAR OBJECTS IN NEARBY YOUNG CLUSTERS (SONYC) IX: THE PLANETARY-MASS DOMAIN OF CHAMAELEON-I AND UPDATED MASS FUNCTION IN LUPUS-3
Authors: Muzic et al.

Data is from this paper:
http://iopscience.iop.org/article/10.1088/0004-637X/810/2/159/meta





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 2 - Photometric Candidates Included in the Spectroscopic Follow-up with Sofi

Awful mutliple line formatting. Whyyyy?

Data Cleaning:
You have to do a regex search and replace using \n{8}\t as the search match, and replace with nothing. Once that is complete, trim the footer and then save the file.





In [3]:



    


#tbl2 = pd.read_csv("http://iopscience.iop.org/0004-637X/810/2/159/suppdata/apj517985t2_ascii.txt",
#                   sep='\t|\n{8}', skiprows=11, skipfooter=3, engine='python', na_values="cdots")
#tbl2



    











In [4]:



    


names = ['id','alpha(J2000)','delta(J2000)','Date','Slit','I','J','K','Comments']
tbl2 = pd.read_csv('../data/Muzic2015/muzic2015_tbl2.txt', 
                   sep='\t', na_values='cdots', names=names, header=1, index_col=False)
tbl2



    


















    
Out[4]:










  
    

      
      id
      alpha(J2000)
      delta(J2000)
      Date
      Slit
      I
      J
      K
      Comments
    

  
  
    

      0 
        1
       11 05 21.36
       -77 46 33.0
       2014 Apr 19
       1
       21.92
       17.37
       14.65
                    NaN
    

    

      1 
        2
       11 06 18.62
       -77 35 17.4
       2014 Apr 18
       1
       22.43
       16.70
       13.22
                    NaN
    

    

      2 
        3
       11 06 28.04
       -77 35 54.7
       2014 Apr 13
       1
       21.68
       16.50
       13.31
                    NaN
    

    

      3 
        4
       11 08 20.20
       -77 45 48.6
       2014 Apr 13
       1
       21.50
       18.09
       15.86
                    NaN
    

    

      4 
        5
       11 08 23.59
       -77 31 29.5
       2014 Apr 14
       2
       22.26
       18.65
       16.49
                    NaN
    

    

      5 
        6
       11 08 30.31
       -77 31 38.6
       2014 Apr 14
       2
       22.50
       17.92
       16.05
       confirmed member
    

    

      6 
        7
       11 08 30.77
       -77 45 50.5
       2014 Apr 13
       1
       21.34
       17.77
       15.59
                    NaN
    

    

      7 
        8
       11 08 33.92
       -77 46 33.4
       2014 Apr 13
       1
       21.49
       18.54
       16.68
                    NaN
    

    

      8 
        9
       11 08 50.38
       -77 45 53.0
       2014 Apr 13
       1
       21.26
       17.90
       16.01
                    NaN
    

    

      9 
       10
       11 09 11.62
       -77 19 26.1
       2014 Apr 18
       1
       21.74
       16.56
       13.20
                    NaN
    

    

      10
       11
       11 09 28.57
       -76 33 28.1
       2014 Apr 14
       1
       21.95
       16.74
       11.93
       confirmed member
    

    

      11
       12
       11 09 32.26
       -76 34 39.3
       2014 Apr 19
       2
       22.76
       18.52
       15.74
                    NaN
    

    

      12
       13
       11 09 35.44
       -77 17 27.1
       2014 Apr 18
       1
       21.68
       16.73
       13.60
                    NaN
    

    

      13
       14
       11 09 37.38
       -76 41 05.7
       2014 Apr 17
       1
       22.71
       17.92
       15.18
                    NaN
    

    

      14
       15
       11 09 51.82
       -76 42 18.2
       2014 Apr 19
       1
       22.97
       17.93
       14.57
                    NaN
    

    

      15
       16
       16 08 03.96
       -39 10 28.9
       2014 Apr 18
       1
       19.39
       16.28
       14.21
                    NaN
    

    

      16
       17
       16 08 25.87
       -39 10 08.0
       2014 Apr 17
       1
       18.13
       15.26
       13.03
                    NaN
    

    

      17
       18
       16 08 30.04
       -39 10 01.4
       2014 Apr 17
       1
       15.51
       12.69
       10.82
                    NaN
    

    

      18
       19
       16 08 33.04
       -38 52 22.7
       2014 Apr 18
       1
       15.34
       12.98
       11.74
       confirmed member
    

    

      19
       20
       16 09 42.66
       -39 03 20.7
       2014 Apr 18
       1
       18.68
       15.54
       13.29
                    NaN
    

    

      20
       21
       16 09 43.74
       -39 07 11.9
       2014 Apr 17
       1
       18.96
       15.74
       13.23
                    NaN
    

    

      21
       22
       16 09 47.20
       -39 08 42.4
       2014 Apr 19
       1
       18.92
       15.91
       13.82
                    NaN
    

    

      22
       23
       16 09 52.68
       -39 06 40.4
       2014 Apr 17
       1
       17.13
       14.45
       12.52
                    NaN
    

    

      23
       24
       16 10 01.33
       -39 06 45.1
       2014 Apr 17
       1
       15.38
       12.32
       10.52
       confirmed member
    

    

      24
       25
       16 10 05.97
       -39 08 06.2
       2014 Apr 18
       1
       18.40
       15.54
       13.29
                    NaN
    

    

      25
       26
       16 10 06.01
       -39 04 23.7
       2014 Apr 17
       1
       16.90
       12.30
        9.59
                 giant?
    

    

      26
       27
       16 10 11.71
       -39 09 19.8
       2014 Apr 17
       1
       17.81
       14.84
       12.96
                    NaN
    

    

      27
       28
       16 10 13.74
       -39 02 34.8
       2014 Apr 17
       1
       17.21
       13.49
       10.86
                 giant?
    

    

      28
       29
       16 10 14.59
       -39 02 31.4
       2014 Apr 17
       1
       19.41
       15.89
       13.58
                    NaN
    

    

      29
       30
       16 10 17.86
       -39 03 47.1
       2014 Apr 17
       1
       16.26
       13.73
       11.93
                    NaN
    

    

      30
       31
       16 10 30.82
       -39 04 04.4
       2014 Apr 18
       1
       17.29
       14.66
       12.81
                    NaN
    

    

      31
       32
       16 10 33.59
       -39 08 21.4
       2014 Apr 17
       1
       17.56
       14.84
       12.54
                    NaN
    

    

      32
       33
       16 11 46.57
       -39 06 04.7
       2014 Apr 17
       1
       15.39
       13.19
       11.23
                member?
    

    

      33
       34
       16 12 04.95
       -39 06 25.6
       2014 Apr 17
       1
       15.40
       13.12
       11.51
        giant or member

The $I-$band data is Cousins $I$ for Cha, and DENIS $i$ for Lupus.





In [5]:



    


tbl2.to_csv("../data/Muzic2015/tbl2.csv", index=False)

Plots





In [7]:



    


I_J = tbl2.I - tbl2.J



    











In [9]:



    


sns.distplot(I_J, axlabel='$I-J$')



    


















    
Out[9]:








<matplotlib.axes._subplots.AxesSubplot at 0x111fb07d0>

Content source: BrownDwarf/ApJdataFrames

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