我有3个数据帧在df1
df2
DF3
我正在寻找以下输出df1
我已经尝试了多种方法，但无法实现这一点，我是Python编码新手，有什么方法可以实现这一点吗？在我尝试的代码下面，它确实匹配并返回find/not found，但还无法为匹配行分配df1[col4]=df2[col4]。
for i in df3.index:
if "," in df3.loc[i,"col_combination"]:
print("multi column values to handle later")
else:
df1['col4'] = np.where(df1[df3.loc[i, "col_combination"]].isin(df2[df3.loc[i, "col_combination"]]),'found','not found')
del df1['col4']
# read every condition in df3
# and merge related df2 columns to df1
# with the condition column
for i, row in df3.iterrows():
priority = row['priority']
col_list = row['col_combination'].split(',')
df1 = pd.merge(df1, df2[col_list + ['col4']], on=col_list, how='left')
# rename every merge df1's new col4 to priority no.
df1.rename(columns={'col4':priority}, inplace=True)
print(df1)
# srno col1 col2 col3 1 2
# 0 1 a1 a2 a3 g1 NaN
# 1 2 b1 c2 c3 NaN g3
# 2 3 d1 b2 NaN NaN g2
# 3 4 e1 e2 e3 NaN NaN
priority_list = df3['priority'].tolist()
obj = df1[priority_list[0]]
# use combine_first to merge priority(columns) 1, 2
for priority in priority_list[1:]:
obj = obj.combine_first(df1[priority])
# re-assign
df1['col4'] = obj
print(df1)
# srno col1 col2 col3 1 2 col4
# 0 1 a1 a2 a3 g1 NaN g1
# 1 2 b1 c2 c3 NaN g3 g3
# 2 3 d1 b2 NaN NaN g2 g2
# 3 4 e1 e2 e3 NaN NaN NaN
# finally del priority columns
df1.drop(priority_list, axis=1, inplace=True)
