如何针对硬编码的integer值执行多个if/else语句?

我有一个像这样的df:

  sentiment
0 -0.1929
1  0
2  0.3

如何将数据框中每一行的每个情感得分与硬编码整数进行比较,并创建一个新的列?

例如:

if df.sentiment >= 0.2:
   df['cate'] = 'positive'
elif df.sentiment <= -0.2:
   df['cate'] = 'negative'
else:
   df['cate'] = 'neutral'

新的数据帧应该如下所示:

   sentiment      cate
    0 -0.1929     negative
    1  0          netural
    2  0.3        positive

我一直在尝试这段代码:

for row in df_sentences.iterrows():
    if df_sentences['sentiment'] >= 0.2:
        df_sentences['category'] = 'positive'
    elif df_sentences['sentiment'] <= 0.2:
        df_sentences['category'] = 'negative'
    else: 
        df_sentences['category'] = 'negative'

但得到错误:

ValueError: The truth value of a Series is ambiguous. Use a.empty, a.bool(), a.item(), a.any() or a.all().