How to pivot data with minimum and maximum agregation in pandas dataframe?

Question

Here's my dataset

    cluster     longitude   latitude
0   0           106.113339  -1.940917
1   0           110.376900  -7.813083
2   0           110.338306  -7.808583
3   1           110.860550  -6.805350
4   1           109.247000  -7.420811
5   1           109.254000  -7.397000

Here's my expected output

cluster  min_longitude  min_latitude  max_longitude  max_latitude
0           106.113339     -7.813083     110.376900     -1.940917
1           109.247000     -7.420811     110.860550     -6.805350

Here's what I did

longitude = df.groupby('cluster').agg({'longitude':  ['min', 'max']}).reset_index()
longitude.columns = ['cluster', 'min_longitude', 'max_longitude']
latitude = dfgroupby('cluster').agg({'latitude':  ['min', 'max']}).reset_index()
latitude.columns = ['cluster', 'min_latitude', 'max_latitude']
df_merege = longitude.merge(latitude,  how='left', left_on=['cluster'], right_on = ['cluster'])

But it give simila value between min_longitude and max_longitude , and I don't know why