您可以使用pivot()。为此，请为每个“乘车标识”类型创建一个列“person_IDx”，其中的值以“person_ID1，person_ID2，...，person_IDn”的顺序表示：

df = pd.DataFrame(data=[["ride_1","person1"],["ride_1","person2"],["ride_1","person3"],["ride_2","person1"],["ride_2","person4"],["ride_3","person1"],["ride_3","person5"],["ride_3","person2"],["ride_3","person3"]], columns=["ride_ID","person_ID"])

df["person_IDx"] = 1

df["person_IDx"] = df.groupby("ride_ID")["person_IDx"].transform("cumsum").apply(lambda x: f"person_ID{x}")

df = df.pivot(index="ride_ID", columns="person_IDx", values="person_ID").reset_index().rename_axis(columns={"person_IDx":""})

[Out]:
  ride_ID person_ID1 person_ID2 person_ID3 person_ID4
0  ride_1    person1    person2    person3        NaN
1  ride_2    person1    person4        NaN        NaN
2  ride_3    person1    person5    person2    person3