How to change only the maximum value of a group in pandas dataframe

You can use idxmax() to get the idx of the maximum for each group, and increment only these items, like this:

max_idxs = df.groupby(['Item'])['Count'].idxmax()
df['New_Count']=df['Count'] # copy entire column
df['New_Count'][max_idxs]+=1 # increment only the maximum item for each group by 1

Use idxmax:

idx = df.groupby("Item")["Count"].idxmax()
df["New_Count"] = df["Count"]
df.loc[idx, "New_Count"] += 1

This will only increment the first occurrence of th maximum in each group. If you want to increment all the maximum values in the case of a tie, you can use transform instead. Just replace the first line above with:

idx = df.groupby("Item")["Count"].transform(max) == df["Count"]

Here's another way not using groupby but using duplicated

df.loc[~df.sort_values('Count', ascending=False).duplicated('Item'), 'Count'] += 1

Output:

  Item  Count
0    A     61
1    A     20
2    A     21
3    B     34
4    B     33
5    B     32