ILT#4 Exploring ATNF pulsar data

First I created a parser for the pulsar data (just the main db not the glitch table but pull requests are always welcome) which can be found here

Then I wrote the following notebook to try to get a feel what differences the period (P0) distribution can have betwene the different surveys.



In [164]:

    
import json
import pandas as pd
from pandas.io.json import json_normalize

pulsarcat_str = ''

with open('atnf_pulsarcat.json', 'r') as f:
    pulsarcat_str = f.read()

pulsarcat = json.loads(pulsarcat_str)



In [165]:

    
pulsarcat_norm= json_normalize(pulsarcat)



In [166]:

    
pulsarcat_norm_num = pulsarcat_norm.convert_objects(convert_numeric=True)









    



/Users/kns/anaconda2/lib/python2.7/site-packages/ipykernel/__main__.py:1: FutureWarning: convert_objects is deprecated.  Use the data-type specific converters pd.to_datetime, pd.to_timedelta and pd.to_numeric.
  if __name__ == '__main__':



In [167]:

    
surveys = pulsarcat_norm_num['SURVEY']
surveys2 = surveys.str.split(',').tolist()
surveys3 = set([surv for srvs in surveys2 for surv in srvs])



In [168]:

    
%matplotlib inline



In [170]:

    
import seaborn as sns
import matplotlib as mpl
import matplotlib.pyplot as plt



In [172]:

    
li = 0
for i, srv in enumerate(surveys3):
    vals = pulsarcat_norm_num[pulsarcat_norm_num['SURVEY'].isin([srv])]['P0.value'].dropna()
    if(vals.size <=0):
        continue
    sns.plt.figure(i)
    sns.plt.title(srv.replace('_', '-'))
    sns.distplot(vals,kde=False)
    li = i



In [173]:

    
sns.plt.figure(li+1)
sns.plt.title('ALL')
sns.distplot(pulsarcat_norm_num['P0.value'].dropna(),kde=False)









    Out[173]:





<matplotlib.axes._subplots.AxesSubplot at 0x15b30ccd0>

It would seem that many suvey datasets have a bump at the tail which can be interesting to see if it has any physical explanation.



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