# -*- coding: utf-8 -*- """ @author: David R Hagen @license: MIT """ from scipy.stats import norm from general_setup import smooth_data,median_over_months,sum_over_patterns,filter_for_specific_day,plot_me from load_data import good_XXth_data,bad_XXth_data,bad_nth_data # Good medians good_XXth_medians = median_over_months(good_XXth_data) good_XXth_medians_smooth = smooth_data(good_XXth_medians, 5) # The day of interest only_11th = filter_for_specific_day(good_XXth_data, '11th') only_11th_medians_smooth = good_XXth_medians_smooth[['year','11th']] # Bad sums sum_bad_XXth = sum_over_patterns(bad_XXth_data, new_name='badth') # Sum of good and bad sum_bad_XXth_and_11th = sum_over_patterns(only_11th.merge(bad_XXth_data, on='year'), new_name='allth') sum_bad_XXth_and_11th_medians = median_over_months(sum_bad_XXth_and_11th) sum_bad_XXth_and_11th_medians_smooth = smooth_data(sum_bad_XXth_and_11th_medians, 5) # Difference between good and sum of bad and good (not necessarily equal to sum of bad alone) sum_XXth_minus_bad_medians = sum_bad_XXth_and_11th_medians.copy() sum_XXth_minus_bad_medians.columns = ['year', 'diffth'] sum_XXth_minus_bad_medians['diffth'] = sum_bad_XXth_and_11th_medians['allth'] - good_XXth_medians['11th']
# -*- coding: utf-8 -*-
"""
@author: David R Hagen
@license: MIT
"""
from scipy.stats import norm
from general_setup import smooth_data, median_over_months, sum_over_patterns, filter_for_specific_day, plot_me
from load_data import good_XXth_data, bad_XXth_data, bad_nth_data
# Good medians
good_XXth_medians = median_over_months(good_XXth_data)
good_XXth_medians_smooth = smooth_data(good_XXth_medians, 5)
# The day of interest
only_11th = filter_for_specific_day(good_XXth_data, '11th')
only_11th_medians_smooth = good_XXth_medians_smooth[['year', '11th']]
# Bad sums
sum_bad_XXth = sum_over_patterns(bad_XXth_data, new_name='badth')
# Sum of good and bad
sum_bad_XXth_and_11th = sum_over_patterns(only_11th.merge(bad_XXth_data,
on='year'),
new_name='allth')
sum_bad_XXth_and_11th_medians = median_over_months(sum_bad_XXth_and_11th)
sum_bad_XXth_and_11th_medians_smooth = smooth_data(
sum_bad_XXth_and_11th_medians, 5)
# Difference between good and sum of bad and good (not necessarily equal to sum of bad alone)
# -*- coding: utf-8 -*- """ @author: David R Hagen @license: MIT """ from general_setup import merge_data,smooth_data,median_over_months,sum_over_patterns,filter_for_specific_day,plot_me from load_data import good_XXth_data,old_style_data # Good medians good_XXth_medians = median_over_months(good_XXth_data) good_XXth_medians_smooth = smooth_data(good_XXth_medians, 5) # Old-style medians old_style_medians = median_over_months(old_style_data) old_style_medians_smooth = smooth_data(old_style_medians) # Extract new-style days only_2nd = filter_for_specific_day(good_XXth_data, '2nd') only_3rd = filter_for_specific_day(good_XXth_data, '3rd') only_22nd = filter_for_specific_day(good_XXth_data, '22nd') only_23rd = filter_for_specific_day(good_XXth_data, '23rd') # Extract old-style days only_2d = filter_for_specific_day(old_style_data, '2d') only_3d = filter_for_specific_day(old_style_data, '3d') only_22d = filter_for_specific_day(old_style_data, '22d') only_23d = filter_for_specific_day(old_style_data, '23d') # Sum old and new style sum_2nd_2d = sum_over_patterns(only_2nd.merge(only_2d, on='year'), new_name='2xx')
# -*- coding: utf-8 -*- """ @author: David R Hagen @license: MIT """ from general_setup import merge_data, smooth_data, median_over_months, sum_over_patterns, filter_for_specific_day, plot_me from load_data import good_XXth_data, old_style_data # Good medians good_XXth_medians = median_over_months(good_XXth_data) good_XXth_medians_smooth = smooth_data(good_XXth_medians, 5) # Old-style medians old_style_medians = median_over_months(old_style_data) old_style_medians_smooth = smooth_data(old_style_medians) # Extract new-style days only_2nd = filter_for_specific_day(good_XXth_data, '2nd') only_3rd = filter_for_specific_day(good_XXth_data, '3rd') only_22nd = filter_for_specific_day(good_XXth_data, '22nd') only_23rd = filter_for_specific_day(good_XXth_data, '23rd') # Extract old-style days only_2d = filter_for_specific_day(old_style_data, '2d') only_3d = filter_for_specific_day(old_style_data, '3d') only_22d = filter_for_specific_day(old_style_data, '22d') only_23d = filter_for_specific_day(old_style_data, '23d') # Sum old and new style sum_2nd_2d = sum_over_patterns(only_2nd.merge(only_2d, on='year'),