leguadmin/xbackend
1
0
Fork 0
Code Issues Pull Requests Releases Wiki Activity

update

Browse Source
This commit is contained in:
wuaho 2021-06-18 19:24:19 +08:00
parent 9aeb897e4a
commit c1c2f64390
2 changed files with 48 additions and 6 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

51
api/api_v1/endpoints/query.py
View File

@ -212,6 +212,15 @@ async def funnel_model(
groupby = res['groupby']
df = await ckdb.query_dataframe(sql)
# 补齐level数据
concat_data = []
for key, tmp_df in df.groupby(['date'] + groupby):
not_exists_level = {i for i in range(1, len(cond_level) + 1)} - set(tmp_df['level'])
for item in not_exists_level:
key = key if isinstance(key, tuple) else (key,)
concat_data.append((*key, item, 0))
df = pd.concat([df, pd.DataFrame(concat_data, columns=df.columns)])
# df.set_index('date',inplace=True)
data_list = []
date_data = {}
@ -231,6 +240,34 @@ async def funnel_model(
tmp['p1'].append(round(v * 100 / tmp_df.loc[1, 'values'], 2))
# tmp['p2'].append(round(v*100 / tmp_df.loc[i - 1, 'values'], 2))
data_list.append(tmp)
# 补齐日期
all_idx = {(dt, lv) for dt in date_range for lv in range(1, len(cond_level) + 1)}
concat_data = []
for i in all_idx - set(df.set_index(['date', 'level']).index):
concat_data.append((*i, 0))
summary_df = pd.concat(
[df[['date', 'level', 'values']], pd.DataFrame(concat_data, columns=['date', 'level', 'values'])])
for key, tmp_df in summary_df.groupby('date'):
tmp_df = tmp_df.groupby('level').sum()
tmp_df.sort_index(inplace=True)
for i in tmp_df.index:
tmp_df.loc[i, 'values'] = tmp_df.loc[i:]['values'].sum()
tmp = dict()
tmp['n'] = tmp_df['values'].to_list()
tmp['p1'] = [100]
# tmp['p2'] = []
for i, v in tmp_df.loc[2:, 'values'].items():
var = round(v * 100 / tmp_df.loc[1, 'values'], 2)
var = 0 if np.isnan(var) else var
tmp['p1'].append(var)
# tmp['p2'].append(round(v*100 / tmp_df.loc[i - 1, 'values'], 2))
_ = date_data.setdefault(key.strftime('%Y-%m-%d'), {})
_['总体'] = tmp
if groupby:
# 补齐数据
concat_data = []
@ -253,7 +290,9 @@ async def funnel_model(
tmp['p1'] = [100]
# tmp['p2'] = []
for i, v in tmp_df.loc[2:, 'values'].items():
tmp['p1'].append(round(v * 100 / tmp_df.loc[1, 'values'], 2))
var = round(v * 100 / tmp_df.loc[1, 'values'], 2)
var = 0 if np.isnan(var) else var
tmp['p1'].append(var)
# tmp['p2'].append(round(v*100 / tmp_df.loc[i - 1, 'values'], 2))
data_list.append(tmp)
@ -270,13 +309,15 @@ async def funnel_model(
tmp['p1'] = [100]
# tmp['p2'] = []
for i, v in tmp_df.loc[2:, 'values'].items():
tmp['p1'].append(round(v * 100 / tmp_df.loc[1, 'values'], 2))
var = round(v * 100 / tmp_df.loc[1, 'values'], 2)
var = 0 if np.isnan(var) else var
tmp['p1'].append(var)
# tmp['p2'].append(round(v*100 / tmp_df.loc[i - 1, 'values'], 2))
_ = date_data.setdefault(key[0].strftime('%Y-%m-%d'), {})
_[key[1]] = tmp
resp = {'list': data_list, 'date_data': date_data, 'title': groupby + cond_level, 'level': cond_level
title = (groupby or ['总体']) + cond_level
resp = {'list': data_list, 'date_data': date_data, 'title': title, 'level': cond_level
}
return schemas.Msg(code=0, msg='ok', data=resp)
@ -320,7 +361,7 @@ async def scatter_model_sql(
resp['label'] = [f'[{i},{i + interval})' for i in range(min_v, max_v, interval)]
bins = [i for i in range(min_v, max_v + interval, interval)]
else:
quota_interval_arr = [-float('inf')] + quota_interval_arr+[float('inf')]
quota_interval_arr = [-float('inf')] + quota_interval_arr + [float('inf')]
resp['label'] = []
bins = [quota_interval_arr[0]]
for i, v in enumerate(quota_interval_arr[1:]):

3
models/behavior_analysis.py
View File

@ -273,7 +273,8 @@ ORDER BY level
.group_by(sa.Column('date'), *[sa.Column(i.key) for i in self.groupby], sa.Column('level')) \
.order_by(sa.Column('date'), *[sa.Column(i.key) for i in self.groupby], sa.Column('level'))
sql = str(qry.compile(compile_kwargs={"literal_binds": True}))
sql = sql.replace('_windows_gap_', f"({windows_gap},'strict_increase')")
# sql = sql.replace('_windows_gap_', f"({windows_gap},'strict_increase')")
sql = sql.replace('_windows_gap_', f"({windows_gap})")
print(sql)
return {'sql': sql,
'groupby': [i.key for i in self.groupby],