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wuaho 2021-09-22 13:37:30 +08:00
parent 5a6bd4ea02
commit 01600069d6
1 changed files with 20 additions and 5 deletions
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25
api/api_v1/endpoints/query.py
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@ -606,7 +606,7 @@ async def scatter_model(
analysis = res['analysis']
groupby = res['groupby']
quota_interval_arr = res['quota_interval_arr']
if analysis != 'number_of_days':
if analysis != 'number_of_days' and interval_type != 'discrete':
max_v = int(df['values'].max())
min_v = int(df['values'].min())
interval = (max_v - min_v) // 10 or 1
@ -655,10 +655,25 @@ async def scatter_model(
# elif analysis == 'number_of_days':
else:
resp = {'list': {}}
for key, tmp_df in df.groupby('date'):
total = int(tmp_df['values'].sum())
resp['list'][key.strftime('%Y-%m-%d')] = {'n': total, 'total': total, 'p': 100}
resp = {'list': {}, 'label': [],
'start_date': res['start_date'],
'end_date': res['end_date'],
'time_particle': res['time_particle']
}
total_dict = {}
labels = [str(i) for i in sorted(df['values'].unique())]
resp['label'] = labels
for key, tmp_df in df.groupby(['date']):
total = len(tmp_df)
dt = key.strftime('%Y-%m-%d')
labels_dict = {}
for key2, tmp_df2 in tmp_df.groupby('values'):
label = str(key2)
n = len(tmp_df2)
labels_dict[label] = n
resp['list'][dt] = {'总体': {'n': [labels_dict.get(i, 0) for i in labels], 'total': total,
'p': [round(labels_dict.get(i, 0)*100 / total, 2) for i in labels]}}
return schemas.Msg(code=0, msg='ok', data=resp)
# bins_s = pd.cut(tmp_df['values'], bins=bins,