Как сместить значения в столбце на основании условия в панде

Question

Привет У меня есть df, как это,

    Name    sl no   details                 score
0   Ram     1       ram is going to ooty    NaN
1   Ram     2       ram sings well          1.5
2   Ravi    1       ravi play cricket       1.0
3   Ravi    2       ravi is in chennai      NaN
4   Kumar   1       kumar passed the exam   NaN
5   Kumar   2       kumar is in town        NaN
6   Kumar   3       he left                 3.0

Я пытаюсь сместить значения в столбце оценки.значения должны быть перемещены в ячейку, где df[sl no]==1 or df[Name] is the first occurence of a name

Мой ожидаемый результат должен выглядеть следующим образом:

    Name    sl no   details                 score
0   Ram     1       ram is going to ooty    1.5
1   Ram     2       ram sings well          NaN
2   Ravi    1       ravi play cricket       1.0
3   Ravi    2       ravi is in chennai      NaN
4   Kumar   1       kumar passed the exam   3.0
5   Kumar   2       kumar is in town        NaN
6   Kumar   3       he left                 NaN

Пожалуйста, помогите.

Answer 1

Вы можете попробовать так:

df['score'] = (df['score'].replace('',np.nan).groupby(df['Name']).transform(lambda x: x.bfill().ffill()))
df.loc[df['sl no'] != 1, 'score'] = np.NaN

Сначала заполните столбец score теми же значениями:

    Name  sl no               details  score
0    Ram   1     ram is going to ooty    1.5
1    Ram   2           ram sings well    1.5
2   Ravi   1        ravi play cricket    1.0
3   Ravi   2       ravi is in chennai    1.0
4  Kumar   1    kumar passed the exam    3.0
5  Kumar   2         kumar is in town    3.0
6  Kumar   3                  he left    3.0

А затем удалите, где столбец sl no не равен 1

    Name  sl no              details  score
0    Ram   1    ram is going to ooty    1.5
1    Ram   2          ram sings well    NaN
2   Ravi   1       ravi play cricket    1.0
3   Ravi   2      ravi is in chennai    NaN
4  Kumar   1   kumar passed the exam    3.0
5  Kumar   2        kumar is in town    NaN
6  Kumar   3                 he left    NaN

Answer 2

next в понимании списка

Условно вызовите next на итераторе в понимании списка.

assert df['sl no'].eq(1).sum() == df['score'].notna().sum()

it = iter(df.score.dropna().tolist())
df['score'] = [
    next(it) if i else np.nan for i in df['sl no'].eq(1)
]

df
    Name  sl no                details  score
0    Ram      1   ram is going to ooty    1.5
1    Ram      2         ram sings well    NaN
2   Ravi      1      ravi play cricket    1.0
3   Ravi      2     ravi is in chennai    NaN
4  Kumar      1  kumar passed the exam    3.0
5  Kumar      2       kumar is in town    NaN
6  Kumar      3                he left    NaN

Если ваш assert утверждение не выполнено, что-то не так с вашими данными, а то, что вы просите, неосуществимо.

---

loc На основе назначения

v = df.score.dropna().tolist()

df['score'] = np.nan
df.loc[df['sl no'].eq(1), 'score'] = v

df
    Name  sl no                details  score
0    Ram      1   ram is going to ooty    1.5
1    Ram      2         ram sings well    NaN
2   Ravi      1      ravi play cricket    1.0
3   Ravi      2     ravi is in chennai    NaN
4  Kumar      1  kumar passed the exam    3.0
5  Kumar      2       kumar is in town    NaN
6  Kumar      3                he left    NaN