#python #pandas
#python #панды
Вопрос:
Я пытаюсь сопоставить offer_id
с соответствующей транзакцией. Это набор данных:
time event offer_id amount
2077 0 offer received f19421c1d4aa40978ebb69ca19b0e20d NaN
15973 6 offer viewed f19421c1d4aa40978ebb69ca19b0e20d NaN
15974 6 transaction NaN 3.43
18470 12 transaction NaN 6.01
18471 12 offer completed f19421c1d4aa40978ebb69ca19b0e20d NaN
43417 108 transaction NaN 11.00
44532 114 transaction NaN 1.69
50587 150 transaction NaN 3.23
55277 168 offer received 9b98b8c7a33c4b65b9aebfe6a799e6d9 NaN
96598 258 transaction NaN 2.18
Правило заключается в том, что при просмотре предложения транзакция принадлежит этому идентификатору предложения. Если предложение получено, но не просмотрено, транзакция не принадлежит идентификатору предложения. Я надеюсь time
, что переменная прояснит это. Это желаемый результат:
time event offer_id amount
2077 0 offer received f19421c1d4aa40978ebb69ca19b0e20d NaN
15973 6 offer viewed f19421c1d4aa40978ebb69ca19b0e20d NaN
15974 6 transaction f19421c1d4aa40978ebb69ca19b0e20d 3.43
18470 12 transaction f19421c1d4aa40978ebb69ca19b0e20d 6.01
18471 12 offer completed f19421c1d4aa40978ebb69ca19b0e20d NaN
43417 108 transaction NaN 11.00
44532 114 transaction NaN 1.69
50587 150 transaction NaN 3.23
55277 168 offer received 9b98b8c7a33c4b65b9aebfe6a799e6d9 NaN
96598 258 transaction NaN 2.18
Комментарии:
1. То есть до тех пор, пока предложение не будет завершено, верно?
2. да, именно так, после этого необходимо получить и просмотреть новое предложение
Ответ №1:
Пример кода:
import pandas as pd
import numpy as np
d = {'time': [0, 6, 6, 12, 12, 108, 144, 150, 168, 258],
'event': ["offer received", "offer viewed", "transaction", "transaction", "offer completed", "transaction", "transaction", "transaction", "offer received", "transaction"],
'offer_id': ["f19421c1d4aa40978ebb69ca19b0e20d", "f19421c1d4aa40978ebb69ca19b0e20d", np.nan, np.nan, "f19421c1d4aa40978ebb69ca19b0e20d", np.nan, np.nan, np.nan, "9b98b8c7a33c4b65b9aebfe6a799e6d9", np.nan]}
df = pd.DataFrame(d)
print("Original data:n{}n".format(df))
is_offer_viewed = False
now_offer_id = np.nan
for index, row in df.iterrows():
if row['event'] == "offer viewed":
is_offer_viewed = True
now_offer_id = row['offer_id']
elif row['event'] == "transaction" and is_offer_viewed:
df.at[index, 'offer_id'] = now_offer_id
elif row['event'] == "offer completed":
is_offer_viewed = False
now_offer_id = np.nan
print("Processed data:n{}n".format(df))
Выводит:
Original data:
time event offer_id
0 0 offer received f19421c1d4aa40978ebb69ca19b0e20d
1 6 offer viewed f19421c1d4aa40978ebb69ca19b0e20d
2 6 transaction NaN
3 12 transaction NaN
4 12 offer completed f19421c1d4aa40978ebb69ca19b0e20d
5 108 transaction NaN
6 144 transaction NaN
7 150 transaction NaN
8 168 offer received 9b98b8c7a33c4b65b9aebfe6a799e6d9
9 258 transaction NaN
Processed data:
time event offer_id
0 0 offer received f19421c1d4aa40978ebb69ca19b0e20d
1 6 offer viewed f19421c1d4aa40978ebb69ca19b0e20d
2 6 transaction f19421c1d4aa40978ebb69ca19b0e20d
3 12 transaction f19421c1d4aa40978ebb69ca19b0e20d
4 12 offer completed f19421c1d4aa40978ebb69ca19b0e20d
5 108 transaction NaN
6 144 transaction NaN
7 150 transaction NaN
8 168 offer received 9b98b8c7a33c4b65b9aebfe6a799e6d9
9 258 transaction NaN
Комментарии:
1. @DataMastery Рад помочь 🙂