I have a large data set : <https://raw.githubusercontent.com/rfordatascience/tidytuesday/master/data/2022/2022-07-19/technology.csv>

here is the head of the dataset:
[head](https://i.stack.imgur.com/gBIzc.png)

I have to grouped this dataset by the variables and taken the averages of each country's technology adoption with this:

```
df.groupby(['variable','iso3c'])[['value']].mean()

```

here is the output

```
                           value
variable     iso3c              
BCG          AFG       45.763158
             AGO       56.648649
             ALB       93.875000
             ARE       86.650000
             ARG       93.700000
...                          ...
visitorrooms VNM    46920.636364
             YEM     5527.280000
             ZAF    48431.850000
             ZMB     3518.000000
             ZWE     4696.440000

```

Now, I want to sort within the variables by largest values to smallest. I thought of doing this:

```
df.groupby(['variable','iso3c'])[['value']].mean().sort_values(['variable','value'])

```

but this is the output

```
                           value
variable     iso3c              
BCG          SWE    1.722500e+01
             SOM    3.812500e+01
             AFG    4.576316e+01
             TCD    4.586111e+01
             ETH    5.141026e+01
...                          ...
visitorrooms ESP    5.755948e+05
             JPN    6.531027e+05
             DEU    7.400641e+05
             ITA    9.286496e+05
             USA    3.040499e+06

[16933 rows x 1 columns]

```

I have no idea what happens to the values here. How do I fix this?