Add Missing Columns to the dataframe

You can create a combined column list like this

col_list = (df1.append([df2,df3])).columns.tolist()

Now add the columns to each dataframe

df1 = df1.loc[:, col_list].fillna(0)
print(df1)

    A   B   C   a   item
0   2   0.0 0.0 1   A
1   3   0.0 0.0 1   B
2   4   0.0 0.0 0   C


df2 = df2.loc[:, col_list].fillna(0)
print(df2)

    A   B   C   a   item
0   0.0 2   0.0 1   E
1   0.0 6   0.0 0   F

df3 = df3.loc[:, col_list].fillna(0)
print(df3)

    A   B   C   a   item
0   0.0 0.0 3   1   G
1   0.0 0.0 4   0   H

1) Take the union of each dataframe's columns.

col_list = list(set().union(dfA.columns, dfB.columns, dfC.columns))
col_list.sort()
['A', 'B', 'C', 'a']

2) Use the reindex function.

dfA2 = dfA.reindex(columns=col_list, fill_value=0)
   A  B  C  a
A  2  0  0  1
B  3  0  0  1
C  4  0  0  0

dfB2 = dfB.reindex(columns=col_list, fill_value=0)
   A  B  C  a
E  0  2  0  1
F  0  6  0  0

dfC2 = dfC.reindex(columns=col_list, fill_value=0)
   A  B  C  a
G  0  0  3  1
H  0  0  4  0

3) You can use reindex to drop, add, or duplicate columns.

dfA3 = dfA.reindex(columns=['C', 'A', 'A', 'D'], fill_value=0)
   C  A  A  D
A  0  2  2  0
B  0  3  3  0
C  0  4  4  0