python - 基于Python Pandas DataFrame中日期的值计算？

Question

我有如下客户协议(protocol)的 DataFrame:

rng = pd.date_range('2020-12-01', periods=5, freq='D')
df = pd.DataFrame({ "ID" : ["1", "2", "1", "2", "2"],
                   "value" : [100, 200, 300, 400, 500],
                   "status" : ["active", "finished", "active", "finished", "active"],
                   "Date": rng})

我需要根据上面的 df 计算创建新的 DataFrame:

1. New1 = 状态为“有效”的最后一个协议(protocol)的值
2. New2 = 状态为“完成”的最后一个协议(protocol)的值

为了更精确，我需要像下面这样创建 df:

Answer 1

尝试使用这么长的时间:

df1 = df.loc[df['status'] == "active"]
df2 = df.loc[df['status'] == "finished"]
df1 = df1.groupby("ID")['value'].last()
df2 = df2.groupby("ID")['value'].last()
IDs = df["ID"].drop_duplicates()
new_df = pd.DataFrame({"ID": IDs, "New1": df1.reindex(IDs).tolist(), "New2": df2.reindex(IDs).tolist()})
print(new_df)

输出:

  ID  New1   New2
0  1   300    NaN
1  2   500  400.0