How do I groupby a column and get the top 10 records in each of the categories in that column? 

The column I want to groupby has 3 categories 'high', 'med' and 'low'.

I have another column with numeric data that I'm using to rank the data.

Here is the head of my dataframe:

```
country   designation     points    province               title             year    price   price_category
Italy     Vulkà Bianco     98        Sicily     Nicosia 2013 Vulkà Bianco    2013     65     high

```

My code here returns the top 2 from the numeric column, but I'm losing all the other columns. Is there a way to do it without losing the other columns?

```
df.groupby('price_category')['points'].nlargest(2)

```

Here is my output I've lost all the other columns:

```
category_column        
high        36528     100
            42197     100
low         5011       95
            15196      95
med         114981     97
            9901       96

```

I need this ^ but without losing my other columns.