Creating the dataframe:

df = pd.DataFrame({'Set': [1, 1, 1, 2, 2, 2, 2, 2], 'Value': [1, 2, 3, 1, 2, 3, 4, 5]})

results in the DataFrame as shown below.

Next I perform a groupby operation by Set, and the first group is shown below.

grouped_by_Set = df.groupby('Set')
grouped_by_Set.get_group(1)

Now I want to select all but the last entry in the Value column per group. I can select the first three (for example) and last entry per group using grouped_by_Set.nth([0, 1, 2]) and grouped_by_Set.nth(-1), however selecting all but the last entry per group does not work with grouped_by_Set.nth(0:-1). I cannot specify the entries explicitly as the groups have different lengths.

CodePudding user response：

IIUC, you can do with iloc in apply

print(df.groupby('Set').apply(lambda x: x.iloc[:-1]).reset_index(drop=True))
   Set  Value
0    1      1
1    1      2
2    2      1
3    2      2
4    2      3
5    2      4

or you could use duplicated and keep='last' to create a mask, then use this mask with loc

print(df.loc[df.duplicated(subset='Set', keep='last')])
   Set  Value
0    1      1
1    1      2
3    2      1
4    2      2
5    2      3
6    2      4

CodePudding user response：

You could use tail(1) to get the last entry of every group and then use the index to deselect it from the original dataframe by inversing isin:

df[~df.index.isin(df.groupby("Set").tail(1).index)]

# Output:
    Set Value
0   1   1
1   1   2
3   2   1
4   2   2
5   2   3
6   2   4

CodePudding user response：

Try this using reset_index(drop=True) .max() methods, the idea is to use the index for each group in order to set the start and the end of the slice operation:

grouped_by_Set = df.groupby('Set')
group = grouped_by_Set.get_group(1).reset_index(drop=True)
start = group.index[0]
end = group.index.max()
df_output = group.iloc[start:end, :]
print(df_output)

Output:

Group 1:

Group 2: