加入可預測變數
Python 中級預測分析
Nele Verbiest
Senior Data Scientist @PythonPredictions
符合時間軸的可預測變數（1）
符合時間軸的可預測變數（2）
加入存續時間
# Reference date reference_date = datetime.date(2018,4,1)# Add lifetime to the basetable basetable["lifetime"] = reference_date - basetable["member_since"] print(basetable.head())
donor_id member_since lifetime
1 2015-02-03 1153
2 2016-01-30 729
3 2016-02-23 768
加入偏好聯絡管道（1）
donor_id start_valid_date end_valid_date contact_channel
1 2014-02-03 2016-03-04 "phone"
1 2016-03-04 2016-05-08 "e-mail"
2 2016-02-23 2026-02-23 "e-mail"
reference_date = datetime.date(2018,4,1)# Select lines compliant with reference data contact_channel_reference_date = living_places[ (contact_channel["start_valid_date"]<=reference_date) & (living_places["end_valid_date"]>reference_date)]
加入偏好聯絡管道（2）
# Add contact channel place to the basetable
basetable =
pd.merge(
basetable,
living_places_reference_date[["donor_ID","contact_channel"]],
on="donor_ID"
)
print(basetable.head())
donor_id contact_channel
1 "phone"
2 "phone"
3 "e-mail"
