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In [1]:

    
# Import modules that contain functions we need
import pandas as pd
import numpy as np
%matplotlib inline
import matplotlib.pyplot as plt



In [2]:

    
data = pd.read_csv("./exoplanets-2.csv")



In [3]:

    
# list first 3 rows in table
data.head(3)









    Out[3]:






  
    
      
      DEPTH
      R
      RSTAR
      MASS
      ECC
      DATE
      DENSITY
      DIST
      GRAVITY
      STARDISCMETH
      RA
      DEC
    
  
  
    
      0
      0.010000
      0.000000
      1.613
      0.000000
      0.0
      NaN
      NaN
      NaN
      NaN
      NaN
      NaN
      NaN
    
    
      1
      66.100000
      0.008101
      0.109
      0.000001
      0.0
      NaN
      NaN
      NaN
      NaN
      NaN
      NaN
      NaN
    
    
      2
      0.000012
      0.027008
      0.770
      0.009587
      0.0
      2013.0
      645.278
      66.0
      4.55299
      Transit
      18.937307
      44.518139



In [14]:

    
# make a histogram of a column
plt.hist(data.MASS, bins=20, range=[0,100]);
plt.title("title")
plt.xlabel("label")
plt.ylabel("label")









    Out[14]:





<matplotlib.text.Text at 0x113da1c18>



In [16]:

    
# scatterplot
plt.scatter(data.R,data.RSTAR)
plt.title('title')
plt.xlabel('label')
plt.ylabel('label')
plt.show()

For more ideas, see the notebooks at the GitHub.

the "CMS mass plot" notebook has examples of selecting a subset of the data based on ranges of values.



In [ ]:

	DEPTH	R	RSTAR	MASS	DATE	DENSITY	DIST	GRAVITY	STARDISCMETH	RA	DEC
0	0.010000	0.000000	1.613	0.000000	NaN	NaN	NaN	NaN	NaN	NaN	NaN
1	66.100000	0.008101	0.109	0.000001	NaN	NaN	NaN	NaN	NaN	NaN	NaN
2	0.000012	0.027008	0.770	0.009587	2013.0	645.278	66.0	4.55299	Transit	18.937307	44.518139