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This commit is contained in:
wuaho 2021-08-30 19:05:28 +08:00
parent ed5055e2e2
commit 621f351f93
1 changed files with 10 additions and 9 deletions
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19
api/api_v1/endpoints/query.py
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@ -136,11 +136,11 @@ async def event_model(
# df_group.reset_index(drop=True, inplace=True) # df_group.reset_index(drop=True, inplace=True)
q['groups'].append(groupby) q['groups'].append(groupby)
q['values'].append(df['values'].to_list()) q['values'].append(df['values'].to_list())
q['sum'].append(int(df['values'].sum())) q['sum'].append(float(df['values'].sum()))
q['avg'].append(int(df['values'].mean())) q['avg'].append(float(df['values'].mean()))
for last_value in df['values'].values[::-1]: for last_value in df['values'].values[::-1]:
if last_value > 0: if last_value > 0:
q['last_value'] = int(last_value) q['last_value'] = float(last_value)
break break
if groupby: if groupby:
q['date_range'] = [f'{i}' for i in df.set_index(groupby).index] q['date_range'] = [f'{i}' for i in df.set_index(groupby).index]
@ -165,11 +165,11 @@ async def event_model(
df_group = pd.concat([df_group, pd.DataFrame(concat_data, columns=df_group.columns)]) df_group = pd.concat([df_group, pd.DataFrame(concat_data, columns=df_group.columns)])
df_group.sort_values('date', inplace=True) df_group.sort_values('date', inplace=True)
q['values'].append(df_group['values'].to_list()) q['values'].append(df_group['values'].to_list())
q['sum'].append(int(df_group['values'].sum())) q['sum'].append(float(df_group['values'].sum()))
q['avg'].append(int(df_group['values'].mean())) q['avg'].append(float(df_group['values'].mean()))
for last_value in df['values'].values[::-1]: for last_value in df['values'].values[::-1]:
if last_value > 0: if last_value > 0:
q['last_value'] = int(last_value) q['last_value'] = float(last_value)
break break
else: else:
@ -186,10 +186,10 @@ async def event_model(
q['values'].append(df['values'].to_list()) q['values'].append(df['values'].to_list())
for last_value in df['values'].values[::-1]: for last_value in df['values'].values[::-1]:
if last_value > 0: if last_value > 0:
q['last_value'] = int(last_value) q['last_value'] = float(last_value)
break break
q['sum'].append(int(df['values'].sum())) q['sum'].append(float(df['values'].sum()))
q['avg'].append(round(df['values'].mean(), 2)) q['avg'].append(float(df['values'].mean()))
if item['time_particle'] in ('P1D', 'P1W'): if item['time_particle'] in ('P1D', 'P1W'):
q['date_range'] = [d.strftime('%Y-%m-%d') for d in q['date_range']] q['date_range'] = [d.strftime('%Y-%m-%d') for d in q['date_range']]
elif item['time_particle'] in ('P1M',): elif item['time_particle'] in ('P1M',):
@ -239,6 +239,7 @@ async def retention_model(request: Request,
days = [i for i in range(unit_num + 1)] days = [i for i in range(unit_num + 1)]
summary_values = {} summary_values = {}
today = datetime.datetime.today().date() today = datetime.datetime.today().date()
for date, value in df.T.items(): for date, value in df.T.items():
tmp = summary_values.setdefault(date.strftime('%Y-%m-%d'), dict()) tmp = summary_values.setdefault(date.strftime('%Y-%m-%d'), dict())
tmp['d0'] = int(value.cnt0) tmp['d0'] = int(value.cnt0)