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ML
ffm-baseline
Commits
89b3ae79
Commit
89b3ae79
authored
Feb 21, 2020
by
张彦钊
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2 changed files
with
32 additions
and
6 deletions
+32
-6
ai_test.py
ai_test.py
+5
-4
make_data.py
make_data.py
+27
-2
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ai_test.py
View file @
89b3ae79
...
@@ -7,11 +7,12 @@ url="http://doris.paas.test/v1/once"
...
@@ -7,11 +7,12 @@ url="http://doris.paas.test/v1/once"
header_dict
=
{
'Content-Type'
:
'application/x-www-form-urlencoded'
}
header_dict
=
{
'Content-Type'
:
'application/x-www-form-urlencoded'
}
param_dict
=
{}
param_dict
=
{}
param_dict
[
"method"
]
=
"doris/search/doctor_officer"
# param_dict["method"]="doris/search/doctor_officer"
param_detail
=
{
"device_id"
:
'xx'
,
"size"
:
10
,
"offset"
:
0
,
"query"
:
"双眼皮"
,
"user_city_tag_id"
:
328
,
"is_officer"
:
False
}
# param_detail = {"device_id": 'xx',"size": 10,"offset":0, "query": "双眼皮","user_city_tag_id": 328,
# "is_officer":False,"filters":{}}
#
param_dict["method"]="doris/search/bangdan"
param_dict
[
"method"
]
=
"doris/search/bangdan"
# param_detail = {"device_id": '2',"size": 10,"offset":0, "user_city_tag_id": 328
,"is_officer":False,"unit_ids":[]}
param_detail
=
{
"device_id"
:
'2'
,
"size"
:
10
,
"offset"
:
0
,
"user_city_tag_id"
:
-
1
,
"is_officer"
:
False
,
"unit_ids"
:[]}
# a = [105, 2941, 780, 102, 873, 2060, 187, 2935, 2108, 912, 928, 2059, 4437, 822, 2866, 2778, 824, 821, 2938]
# a = [105, 2941, 780, 102, 873, 2060, 187, 2935, 2108, 912, 928, 2059, 4437, 822, 2866, 2778, 824, 821, 2938]
...
...
make_data.py
View file @
89b3ae79
...
@@ -62,6 +62,8 @@ def doctor():
...
@@ -62,6 +62,8 @@ def doctor():
"merchant_id"
,
"doctor_ad_money_30_days"
,
"expand_rechange_amount_30"
,
"service_pv_30"
,
"merchant_id"
,
"doctor_ad_money_30_days"
,
"expand_rechange_amount_30"
,
"service_pv_30"
,
"mexpert_pv_30"
,
"organization_pv_30"
,
"budan_payment_30_days"
]
"mexpert_pv_30"
,
"organization_pv_30"
,
"budan_payment_30_days"
]
data
=
df
.
loc
[:,
columns
]
data
=
df
.
loc
[:,
columns
]
data
=
data
.
rename
(
columns
=
renames
)
data
=
data
.
drop_duplicates
()
data
.
to_csv
(
'/tmp/doctor.csv'
,
index
=
False
)
data
.
to_csv
(
'/tmp/doctor.csv'
,
index
=
False
)
print
(
"doctor end"
)
print
(
"doctor end"
)
...
@@ -134,11 +136,34 @@ def hospital():
...
@@ -134,11 +136,34 @@ def hospital():
"doctor_ad_money_30_days"
,
"service_pv_30"
,
"mexpert_pv_30"
,
"organization_pv_30"
,
"doctor_ad_money_30_days"
,
"service_pv_30"
,
"mexpert_pv_30"
,
"organization_pv_30"
,
"doctor_discount_30_days"
]
"doctor_discount_30_days"
]
data
=
df
.
loc
[:,
columns
]
data
=
df
.
loc
[:,
columns
]
renames
=
{
'doctor_id'
:
'机构管理者id'
,
'score'
:
'得分'
,
'ctr'
:
'点击率'
,
'commission'
:
'单pv佣金贡献'
,
'cpt'
:
'单pv的CPT消耗'
,
'hospital_id'
:
'医院id'
,
'hospital_exposure_pv_30'
:
'该医院卡片的曝光-30天'
,
'service_exposure_pv_30'
:
'该医院名下所有美购的曝光-30天'
,
'expert_exposure_pv_30'
:
'机构名下所有医生卡片曝光-30天'
,
'service_ctr_30'
:
'机构名下所有美购ctr-30天'
,
'hospital_ctr_30'
:
'医院卡片ctr-30天'
,
'expert_ctr_30'
:
'机构名下所有医生ctr-30天'
,
'merchant_id'
:
'商户id'
,
'budan_payment_30_days'
:
'30天已补订单佣金'
,
'doctor_ad_money_30_days'
:
'商户名下非医生、机构账号的验证订单抽成之和'
,
'service_pv_30'
:
'该商户名下所有美购的美购详情页PV'
,
'mexpert_pv_30'
:
'该商户名下所有医生主页PV'
,
'organization_pv_30'
:
'该商户名下机构主页PV'
,
'doctor_discount_30_days'
:
'该商户的CPT纯消耗金额'
}
data
=
data
.
rename
(
columns
=
renames
)
data
=
data
.
drop_duplicates
()
print
(
data
.
head
(
6
))
print
(
data
.
head
(
6
))
data
.
to_csv
(
'/tmp/hospital.csv'
,
index
=
False
)
data
.
to_csv
(
'/tmp/hospital.csv'
,
index
=
False
,
encoding
=
"utf_8_sig"
)
if
__name__
==
"__main__"
:
if
__name__
==
"__main__"
:
doctor
()
#
doctor()
hospital
()
hospital
()
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