Merge Two Data Frames On Multiple Values

I have two data frames which look like this df1 name ID abb 0 foo 251803 I 1 bar 376811 R 2 baz 174254 Q 3

Solution 1:

Use join:

print (df1)
     name      ID  abb
0     foo  251803    I
1     bar  376811    R
2     baz  174254    Q
3  foofoo  337144  IRQ
4  barbar  306521   IQ

#each character to df, which is stacked to Series
s = df1.abb.apply(lambda x: pd.Series(list(x)))
           .stack()
           .reset_index(drop=True, level=1)
           .rename('abb')
print (s)
0    I
1    R
2    Q
3    I
3    R
3    Q
4    I
4    Q
Name: abb, dtype: object

df1 = df1.drop('abb', axis=1).join(s)
print (df1)
     name      ID abb
0     foo  251803   I
1     bar  376811   R
2     baz  174254   Q
3  foofoo  337144   I
3  foofoo  337144   R
3  foofoo  337144   Q
4  barbar  306521   I
4  barbar  306521   Q

Solution 2:

See this answer for various ways to explode on a column

rows= []
for i, rowin df1.iterrows():
    for a in row.abb:
        rows.append([row['ID'], a, row['name']])

df11 = pd.DataFrame(rows, columns=df1.columns)

df11.merge(df2)