CA_data = cwd +"/medicare_data/Medicare_Data_CA_xxx.csv" f_CA = read_csv(CA_data) f_CA.describe() f_CA.head(10) len(f_IL.columns) for c in f_IL.columns : print c
IPython notebook
%pylab inline from IPython.display import HTML %matplotlib inline import os import sys from StringIO import StringIO import scipy import seaborn as sns from pandas import read_csv import matplotlib.pyplot as pyplot cwd = os.getcwd() IL_data = cwd +"/medicare_data/Medicare_Data_IL_xxx.csv" f_IL = read_csv(IL_data) f_IL.describe() f_IL.head(5)
len(f_IL.columns) for c in f_IL.columns: print c print len(f_IL.provider_type.unique()) print len(f_IL.nppes_provider_city.unique()) print len(f_IL.hcpcs_description.unique()) f0 = f_IL.average_submitted_chrg_amt.values f1 = f_IL.average_Medicare_payment_amt.values f2 = f_IL.average_Medicare_allowed_amt.values