out_string = "{0}:\t{1:.2f}\t{2:.2f}\t\t{3:.2f}\t\t{4:.2f}" print(column.title()) print('-' * len(column)) print("\tPassed\tDistinctive\tNon-Passed\tPassing") print(out_string.format('Mean', passed.mean, distinctive.mean, non_passed.mean, passing.mean)) print(out_string.format("STD", passed.std, distinctive.std, non_passed.std, passing.std)) print(out_string.format('Min', passed.min, distinctive.min, non_passed.min, passing.min)) print(out_string.format('QI\t', passed.q1, distinctive.q1, non_passed.q1, passing.q1)) print(out_string.format('Median', passed.median, distinctive.median, non_passed.median, passing.median)) print(out_string.format('QIII', passed.q3, distinctive.q3, non_passed.q3, passing.q3)) print(out_string.format("Max", passed.max, distinctive.max, non_passed.max, passing.max)) print(out_string.format('IQR', passed.iqr, distinctive.iqr, non_passed.iqr, passing.iqr)) print(out_string.format("Count", passed.count, distinctive.count, non_passed.count, passing.count)) key = b'account_key' passing = list_to_account_dict(passing_engagement, key) passed = list_to_account_dict(passed_engagement, key) distinctive = list_to_account_dict(distinctive_engagement, key) non_passing = list_to_account_dict(non_passing_engagement, key) passed_total = total_engagement_attribute(b'total_minutes_visited', sum, passed) passing_total = total_engagement_attribute(b'total_minutes_visited', sum, passing) distinctive_total = total_engagement_attribute(b'total_minutes_visited', sum, distinctive) non_passing_total = total_engagement_attribute(b'total_minutes_visited', sum, non_passing) p = to_array(passed_total) print_columns_redone(passed_total, distinctive_total, non_passing_total, passing_total, 'total_minutes_visited') passed = pandas.DataFrame({'passed':to_array(passed_total)}) distinctive = pandas.DataFrame({'distinctive':to_array(distinctive_total)}) non_passing = pandas.DataFrame({'non-passing':to_array(non_passing_total)})
# python standard library from collections import namedtuple, defaultdict # third-party import numpy # this code from paid_students import paid_engagement_in_first_week from paid_students import paid_enrollments, paid_engagements from utilities import list_to_account_dict from utilities import total_engagement_attribute PWEAVE = __name__ in ('builtins', '__builtin__') engagement_by_account = list_to_account_dict(paid_engagement_in_first_week) SummaryStatistics = namedtuple('SummaryStatistics', ['mean', 'std', 'minimum', 'maximum']) class Summary(object): def __init__(self, data): """ :param: - `data`: collection of data """ self.data = data self._summary = None return