def main():
#Create instances of the Analyzer objects to help conduct analyses and generate plots
general_analyzer = BitlyDataAnalyzer()
ckw_analyzer = BitlyDataAnalyzer(only_ckw=True)
#Review basic information about both data-sets.
print 'I have created a general analyzer tool which looks at some selection of the provided data, as well as a \'ckw\' analyzer tool which only looks at some selection of the provided date where a \'ckw\' value is provided.'
print 'Both datasets initially pulled 1000000 entries.'
print 'The general dataset contains ' + str(len(
general_analyzer.df)) + ' unique entries.'
print 'The \'ckw\' dataset contains ' + str(len(
ckw_analyzer.df)) + ' unique entries.'
print 'Percent entries containing \'ckw\' fields in general dataset: ' + str(
general_analyzer.compute_percent_ckw())
print 'Percent entries containing \'ckw\' fields in \'ckw\' dataset: ' + str(
ckw_analyzer.compute_percent_ckw())
print 'Now we will generate the plots. This will take some time...'
general_analyzer.generate_plots()
ckw_analyzer.generate_plots()
print 'All done! Please see Analysis.pdf for a nicely-formatted analysis of the plots and the data.'
def main(): '''When generating plots I was concerned that a lot of my graphs looked similar. It was unclear whether this was a property of the data or whether I had misunderstood some of the data fields. This function should either print Mismatched lengths or False to ensure that there is a difference in grouping by u, h or u and h. It should not print True.''' #Create instances of the Analyzer objects to help conduct analyses general_analyzer = BitlyDataAnalyzer() ckw_analyzer = BitlyDataAnalyzer(only_ckw=True) print "Checking general dataset for variation in grouping by u and h: " general_analyzer.group_by_debugging() print "Checking ckw dataset for variation in grouping by u and h: " ckw_analyzer.group_by_debugging()
def main(): #Create instances of the Analyzer objects to help conduct analyses and generate plots general_analyzer = BitlyDataAnalyzer() ckw_analyzer = BitlyDataAnalyzer(only_ckw=True) #Review basic information about both data-sets. print 'I have created a general analyzer tool which looks at some selection of the provided data, as well as a \'ckw\' analyzer tool which only looks at some selection of the provided date where a \'ckw\' value is provided.' print 'Both datasets initially pulled 1000000 entries.' print 'The general dataset contains ' + str(len(general_analyzer.df)) + ' unique entries.' print 'The \'ckw\' dataset contains ' + str(len(ckw_analyzer.df)) + ' unique entries.' print 'Percent entries containing \'ckw\' fields in general dataset: ' + str(general_analyzer.compute_percent_ckw()) print 'Percent entries containing \'ckw\' fields in \'ckw\' dataset: ' + str(ckw_analyzer.compute_percent_ckw()) print 'Now we will generate the plots. This will take some time...' general_analyzer.generate_plots() ckw_analyzer.generate_plots() print 'All done! Please see Analysis.pdf for a nicely-formatted analysis of the plots and the data.'
def main():
"""When generating plots I was concerned that a lot of my graphs looked similar.
It was unclear whether this was a property of the data or whether I had misunderstood some of the data fields.
This function should either print Mismatched lengths or False to ensure that there is a difference in grouping by u, h or u and h.
It should not print True."""
# Create instances of the Analyzer objects to help conduct analyses
general_analyzer = BitlyDataAnalyzer()
ckw_analyzer = BitlyDataAnalyzer(only_ckw=True)
print "Checking general dataset for variation in grouping by u and h: "
general_analyzer.group_by_debugging()
print "Checking ckw dataset for variation in grouping by u and h: "
ckw_analyzer.group_by_debugging()
