Groupy | simple yet powerful API wrapper for the GroupMe messaging | REST library

I am working on analysing the results of a model search. The results is saved in an excel file, but could easily be imported python (or another environment if necessary). The data look something like this (this is a simplified version in terms of number of columns and rows):

I want to analyse how kappa varies with test data, so i want to know the min, max and average kappa with constant number of classes, dataset type, and subject number constant. this would look something like this:

I have fooled around with pandas.groupy(), but i cant seem to quite figure out how to do this. Any help would be much appriciated!

I am using pandas groupby to group duplicate dates by their pm25 values to get one average. However when I use the groupby function, the structure of my dataframe changes, and I can no longer call the 'Date' Column.

Using groupby also changes the structure of my data: instead of being sorted by 1/1/19, 1/2/19, it is sorted by 1/1/19, 1/10/19, 1/11/19.

Here is my current code:

Before using df.groupby my df looks like:

df before groupy

I use groupby:

I have some data like this:

Having the following DF:

A conflict row is that two rows have same feature but with different label, like this:

I know a lot of questions have already been answered on this one but I still cant wrap my head around it why the following isnt working. My main goal was to join a price and product table and select the cheapest price for each product based on each 3 factors.

For quick testing I went ahead and just filtered my price table which contains the a ref to my corresponding product, price, rrp and some columns for knowing when to apply which price.

I'm trying to create weekly groups using xarray groupy based on a datetime64 time dimension. For some reason it is creating extra groups and putting some dates in the wrong groups. I'm using the S coordinate to group by weeks. For each year there should be five weekly groups, but it is creating seven groups.

Groups being created:

I have a dataframe like this:

I have a dataframe with 129971 rows. I want to groupy 'country', then use groupby\transform to fill missing values in the 'price' column with the mean from each group.

However, my 'country' column has 63 rows with NaN.

When I run this: