我正在尝试使用生命周期库运行BG / NBD模型。 我所有的分析都基于以下示例,但有我自己的数据: https://towardsdatascience.com/whats-a-customer-worth-8daf183f8a4f
以某种方式,我收到以下错误,并且在阅读了50多篇stackoverflow文章而没有找到任何答案之后,我想问自己一个问题: 我究竟做错了什么? :(
预先感谢! :)
我试图更改属于数据框的所有列的类型,而没有进行任何更改。
df2 = df
df2.head()
person_id effective_date accounting_sales_total
0 219333 2018-08-04 1049.89
1 333219 2018-12-21 4738.97
2 344405 2018-07-16 253.99
3 455599 2017-07-14 2199.96
4 766665 2017-08-15 1245.00
from lifetimes.utils import calibration_and_holdout_data
summary_cal_holdout = calibration_and_holdout_data(df2, 'person_id', 'effective_date',
calibration_period_end='2017-12-31',
observation_period_end='2018-12-31')
print(summary_cal_holdout.head())
---------------------------------------------------------------------------
AttributeError Traceback (most recent call last)
<ipython-input-85-cdcb400098dc> in <module>()
7 summary_cal_holdout = calibration_and_holdout_data(df2, 'person_id', 'effective_date',
8 calibration_period_end='2017-12-31',
----> 9 observation_period_end='2018-12-31')
10
11 print(summary_cal_holdout.head())
/usr/local/envs/py3env/lib/python3.5/site-packages/lifetimes/utils.py in calibration_and_holdout_data(transactions, customer_id_col, datetime_col, calibration_period_end, observation_period_end, freq, datetime_format, monetary_value_col)
122 combined_data.fillna(0, inplace=True)
123
--> 124 delta_time = (to_period(observation_period_end) - to_period(calibration_period_end)).n
125 combined_data["duration_holdout"] = delta_time
126
AttributeError: 'int' object has no attribute 'n'
答案 0 :(得分:0)
这实际上可以正常运行:)
data = {'person_id':[219333, 333219, 344405, 455599, 766665],
'effective_date':['2018-08-04', '2018-12-21', '2018-07-16', '2017-07-14', '2017-08-15'],
'accounting_sales_total':[1049.89, 4738.97, 253.99, 2199.96, 1245.00]}
df2 = pd.DataFrame(data)
from lifetimes.utils import calibration_and_holdout_data
summary_cal_holdout = calibration_and_holdout_data(df2, 'person_id', 'effective_date',
calibration_period_end='2017-12-31',
observation_period_end='2018-12-31')
print(summary_cal_holdout.head())
返回:
frequency_cal recency_cal T_cal frequency_holdout \
person_id
455599 0.0 0.0 170.0 0.0
766665 0.0 0.0 138.0 0.0
duration_holdout
person_id
455599 365
766665 365
这意味着您的问题可能与软件包版本控制有关,请尝试:
pip install lifetimes --upgrade