python - how to drop duplicates in a dataframe and with a condition?

Question

I have a large dataframe with duplicated data, there are three columns: word, emotion and score.

I want to find the duplicates in the word column and keep only the words with the higher score.

df = pd.DataFrame({
    'word': ['love', 'sadness', 'love', 'love', 'sadness'],
    'emotion': ['trust', 'trust', 'confidente', 'joy', 'sad'],
    'score': [0.758, 0.250, 0.828, 0.921, 0.981]
})

df_result = pd.DataFrame({
    'word': ['love', 'sadness'],
    'emotion': ['joy', 'sad'],
    'score': [0.921, 0.981]
})

I tried to drop duplicates, but I couldn't add a condition where A < B

# something like
.drop_duplicates('word') # keep A < B
.sort_index()
.reset_index(drop=True)

There are similar questions for this in stackoverflow, but none of them is a similar to this problem.

question from:https://stackoverflow.com/questions/65946974/how-to-drop-duplicates-in-a-dataframe-and-with-a-condition

Answer 1

Try with sort_values

out = df.sort_values(['score']).drop_duplicates('word',keep='last')
Out[249]: 
      word emotion  score
3     love     joy  0.921
4  sadness     sad  0.981