Python 熊猫-在数据框中追加字符串：ValueError:无法从重复的轴重新索引

我有一个data.frame，看起来与此类似（除了更长，颜色名称更多）：

我希望data.frame如下所示：

ffnew = pd.DataFrame({'OldCol':['darkbrown','lightbeige','lightbrown / beige','beige','brown','beige / cognac'], 'NewCol':['brown','beige','beige / brown','sand','brown','sand / brown']})

我尝试了以下方法：

ff.loc[ff['OldCol'].str.contains(r'brown|cognac',na=False) & ff['NewCol'].str.contains(r'nan'), 'NewCol'] = 'brown'
ff.loc[ff['OldCol'].str.contains(r'brown|cognac',na=False) & ~ff['NewCol'].str.contains(r'nan|brown'), 'NewCol'] = ff['NewCol']+'/ brown'

ff.loc[ff['OldCol'].str.contains(r'beige|sand',na=False) & ff['NewCol'].str.contains(r'nan'), 'NewCol'] = 'beige'
ff.loc[ff['OldCol'].str.contains(r'beige|sand',na=False) & ~ff['NewCol'].str.contains(r'nan|beige'), 'NewCol'] = ff['NewCol'] +'/ beige'

在较长的data.frame中，通常会出现以下错误：

ValueError:无法从重复轴重新编制索引

有人能帮忙吗？

---

非常感谢

索引中的重复项存在问题。您可以将索引的所有值替换为to

Regular index

（

0,1,2..len（df）-1

）。旧值通过参数drop=True删除：

ff.reset_index(drop=True, inplace=True)

测试：

---

如果我的回答有帮助，别忘了。谢谢

ff.reset_index(drop=True, inplace=True)

ff = pd.DataFrame({'OldCol':['darkbrown','lightbeige','lightbrown / beige','beige','brown','beige / cognac'], 'NewCol':['nan','nan','nan','nan','nan','nan']})
ffnew = pd.DataFrame({'OldCol':['darkbrown','lightbeige','lightbrown / beige','beige','brown','beige / cognac'], 'NewCol':['brown','beige','beige / brown','sand','brown','sand / brown']})
ff.index = [0,0,2,3,4,5]
#ValueError: cannot reindex from a duplicate axis
ff.reset_index(drop=True, inplace=True)