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Sort monthly resuls #302

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Merged
huitema merged 1 commit into from
Dec 7, 2025
Merged

Sort monthly resuls #302

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16 changes: 9 additions & 7 deletions resolver/rsv_monthly.py
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Original file line number Diff line number Diff line change
Expand Up @@ -89,9 +89,9 @@ def __init__(self, summary_columns):
self.has_sum_delays = False
self.monthly_per_isp = dict()
self.monthly_per_day = dict()
print(str(summary_columns))
#print(str(summary_columns))
self.get_columns(summary_columns)
print(str(self.summed_columns))
#print(str(self.summed_columns))


def get_columns(self, summary_columns):
Expand Down Expand Up @@ -134,9 +134,9 @@ def add_file(self, year, month, day, file_path):
df = pd.read_csv(file_path)
df.apply(lambda row: self.add_cc_as(row),axis=1)
df.apply(lambda row: self.add_daily(row, year, month, day),axis=1)
print("After loading " + file_path + ":")
print("ISP: " + str(len(self.monthly_per_isp)))
print("Days: " + str(len(self.monthly_per_day)))
#print("After loading " + file_path + ":")
#print("ISP: " + str(len(self.monthly_per_isp)))
#print("Days: " + str(len(self.monthly_per_day)))

def load_day(self, month_dir, file_name, year, month):
day_dir = ""
Expand Down Expand Up @@ -178,22 +178,24 @@ def save(self, year, month, month_dir, table_name):
if self.has_max_delay:
isp_columns.append('max_delay')
day_columns.append('max_delay')
print("ISP-columns: " + str(isp_columns))
print("Day-columns: " + str(day_columns))
#print("ISP-columns: " + str(isp_columns))
#print("Day-columns: " + str(day_columns))

isp_t = []
for key in self.monthly_per_isp:
p = key.split('-')
row = [ year, month, p[0], p[1] ] + self.monthly_per_isp[key].get_row()
isp_t.append(row)
isp_df = pd.DataFrame(isp_t,columns=isp_columns)
isp_df.sort_values(['year', 'month', 'uids'], ascending=[True, True, False])
isp_df.to_csv(isp_path)

day_t = []
for key in self.monthly_per_day:
row = [ year, month, key[-2:] ] + self.monthly_per_day[key].get_row()
day_t.append(row)
day_df = pd.DataFrame(day_t,columns=day_columns)
day_df.sort_values(['year', 'month', 'day'], ascending=[True, True, True])
day_df.to_csv(day_path)


Expand Down
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