In [2]:

    

import pandas as pd


    

In [4]:

    

df = pd.read_csv("data/url_logger.csv")


    

In [10]:

    

df['unit'] = 1


    

In [33]:

    

success = df[df.url_status_code ==200].unit.count()
success_grouped = df[df.url_status_code ==200].groupby('name').unit.count()

fail = df[df.url_status_code !=200].unit.count()
fail_grouped = df[df.url_status_code !=200].groupby('name').unit.count()


    

In [14]:

    

total_requests = df.url_status_code.sum()


    

In [61]:

    

print "Summary of URL Requests"
print "-" * 50
print "Percentage successful: %r" % (round(float(success)/ (success + fail), 2))
print "Total Succesful:", success
print "Total Unsuccesful:", fail
print "\n"


print 'Quantity of Articles Available'
print "-" * 50

for index, elem in enumerate(success_grouped):
    print success_grouped.index[index].capitalize(),": ", success_grouped[index]


    

    




Summary of URL Requests
--------------------------------------------------
Percentage successful: 0.49
Total Succesful: 261
Total Unsuccesful: 267


Quantity of Articles Available
--------------------------------------------------
Dailyobserver :  53
Frontpageafricaonline :  63
Gnnliberia :  49
Golministryofinformation :  68
Post1847 :  7
Theanalyst :  4
Thenewdawn :  17

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