I have a dataframe df and I use several columns from it to groupby:
df['col1','col2','col3','col4'].groupby(['col1','col2']).mean()
In the above way, I almost get the table (dataframe) that I need. What is missing is an additional column that contains number of rows in each group. In other words, I have mean but I also would like to know how many were used to get these means. For example in the first group there are 8 values and in the second one 10 and so on.
In short: How do I get group-wise statistics for a dataframe?
On groupby object, the agg function can take a list to apply several aggregation methods at once. This should give you the result you need:
df[['col1', 'col2', 'col3', 'col4']].groupby(['col1', 'col2']).agg(['mean', 'count'])