Use merge:
print (pd.merge(df1, df2, left_on='id', right_on='id1', how='left').drop('id1', axis=1))
id name count price rating
0 1 a 10 100.0 1.0
1 2 b 20 200.0 2.0
2 3 c 30 300.0 3.0
3 4 d 40 NaN NaN
4 5 e 50 500.0 5.0
Another solution is simple rename column:
print (pd.merge(df1, df2.rename(columns={'id1':'id'}), on='id', how='left'))
id name count price rating
0 1 a 10 100.0 1.0
1 2 b 20 200.0 2.0
2 3 c 30 300.0 3.0
3 4 d 40 NaN NaN
4 5 e 50 500.0 5.0
If need only column price the simpliest is map:
df1['price'] = df1.id.map(df2.set_index('id1')['price'])
print (df1)
id name count price
0 1 a 10 100.0
1 2 b 20 200.0
2 3 c 30 300.0
3 4 d 40 NaN
4 5 e 50 500.0
Another 2 solutions:
print (pd.merge(df1, df2, left_on='id', right_on='id1', how='left')
.drop(['id1', 'rating'], axis=1))
id name count price
0 1 a 10 100.0
1 2 b 20 200.0
2 3 c 30 300.0
3 4 d 40 NaN
4 5 e 50 500.0
print (pd.merge(df1, df2[['id1','price']], left_on='id', right_on='id1', how='left')
.drop('id1', axis=1))
id name count price
0 1 a 10 100.0
1 2 b 20 200.0
2 3 c 30 300.0
3 4 d 40 NaN
4 5 e 50 500.0