在合并期间仅向第一个组合添加值

Question

我有两个 dfs:

df_1

date            id          value
2021-01-01      A1          100
2021-01-01      A1          200
2021-01-01      A1          300
2021-01-02      A1          100
2021-01-02      A1          200
2021-01-03      A1          500
2021-01-03      A1          800

df_2

date            id          value_to_add
2021-01-01      A1          150 
2021-01-03      A1          350

我正在尝试维护 df_1 的结构并在合并期间在第一次出现时添加 value_to_add 以便在填充 NaN 和除了第一个值之外的所有值都带有 0:

date            id          value       value_to_add
2021-01-01      A1          100         150 
2021-01-01      A1          200         0               # 0 because the 150 have been already added
2021-01-01      A1          300         0
2021-01-02      A1          100         0               # 0 because value_to_add does not exist
2021-01-02      A1          200         0
2021-01-03      A1          500         350 
2021-01-03      A1          800         0               # 0 because the 350 have been already added

我的第一个想法是删除 ['date', 'id'] 子集的副本，然后将 df_2 合并到它，但我不确定如何返回到 [=14= 的原始结构].

所以问题如下 - 能够在 pd.merge 操作 期间第一次出现键时合并。我找不到关于这个主题的任何内容，坦率地说，我不确定如何才能做到这一点。

Answer 1

您可以通过 DataFrame.duplicated with invert mask and Index.union 过滤重复值以避免删除从 merge 添加的新列：

df_1.loc[~df_1.duplicated(['date', 'id']),
         df_1.columns.union(df_2.columns)] = df_1.merge(df_2, how='left')
df_1 = df_1.fillna(0)
print (df_1)
         date  id  value  value_to_add
0  2021-01-01  A1    100         150.0
1  2021-01-01  A1    200           0.0
2  2021-01-01  A1    300           0.0
3  2021-01-02  A1    100           0.0
4  2021-01-02  A1    200           0.0
5  2021-01-03  A1    500         350.0
6  2021-01-03  A1    800           0.0

辅助计数器列的另一个想法：

df_1 = df_1.assign(g = df_1.groupby(['date', 'id']).cumcount()).merge(df_2.assign(g=0), how='left')
df_1 = df_1.drop('g', 1).fillna(0)
print (df_1)
         date  id  value  value_to_add
0  2021-01-01  A1    100         150.0
1  2021-01-01  A1    200           0.0
2  2021-01-01  A1    300           0.0
3  2021-01-02  A1    100           0.0
4  2021-01-02  A1    200           0.0
5  2021-01-03  A1    500         350.0
6  2021-01-03  A1    800           0.0

Answer 2

s =df_1.set_index(['date','id']).join(df_2.set_index(['date','id']))

s=s.assign(value_to_add=np.where(~s['value_to_add'].duplicated(keep='first'),s['value_to_add'],np.nan)).fillna(0)

在合并期间仅向第一个组合添加值

Adding value only to a first combination during merge

python

merge

pandas