python - 如何使用 Pandas 添加 python 中未列出的数据帧循环的组合

Question

a = [["a1","b1"],["a2","b2"],["a3","b3"],["a4","b4"],["a5","b5"]]

df = pd.DataFrame({'A' : ["a1","a2","a3","a4"], 'B' : ["b1","b2","b3", "b4"] , 'mean' : ["13.4","12,1","10.0","11.5"]})

如何将列表“a”中没有的组合添加到数据框行？

我想使用contains()或isin()

预期结果不存在的列表将使用默认值 0 填充值的平均值。

pd.DataFrame({'A' : ["a1","a2","a3","a4","a5"], B' : ["b1","b2","b3", "b4","b5"] ,'mean' : ["13.4","12,1","10.0","11.5", "0"]}) 

Answer 1

创建DataFrame构造函数和DataFrame.append到原始，然后通过 DataFrame.drop_duplicates 删除重复项通过指定列并最后用 fillna 替换缺失值:

a = [["a1","b1"],["a2","b2"],["a3","b3"],["a4","b4"],["a5","b5"]]

df1 = df.append(pd.DataFrame(a,columns=['A','B'])).drop_duplicates(subset=['A','B']).fillna(0)

print (df1)
    A   B  mean
0  a1  b1  13.4
1  a2  b2  12,1
2  a3  b3  10.0
3  a4  b4  11.5
4  a5  b5     0

另一个关于合并的想法:

df1 = pd.DataFrame(a, columns=['A','B']).merge(df, how='left').fillna(0)