Python 在 Pandas DataFrame 中删除重复索引的最快方法
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Fastest Way to Drop Duplicated Index in a Pandas DataFrame
提问by RukTech
If I want to drop duplicated index in a dataframe the following doesn't work for obvious reasons:
如果我想删除数据帧中的重复索引，以下原因显然不起作用：
myDF.drop_duplicates(cols=index)
and
和
myDF.drop_duplicates(cols='index')
looks for a column named 'index'
查找名为“index”的列
If I want to drop an index I have to do:
如果我想删除索引，我必须这样做：
myDF['index'] = myDF.index
myDF= myDF.drop_duplicates(cols='index')
myDF.set_index = myDF['index']
myDF= myDF.drop('index', axis =1)
Is there a more efficient way?
有没有更有效的方法？
采纳答案by CT Zhu
Simply: DF.groupby(DF.index).first()
简单地： DF.groupby(DF.index).first()
回答by behzad.nouri
You can use numpy.uniqueto obtain the index of unique values and use ilocto get those indices:
您可以使用numpy.unique来获取唯一值的索引并使用iloc来获取这些索引：
>>> df
val
A 0.021372
B 1.229482
D -1.571025
D -0.110083
C 0.547076
B -0.824754
A -1.378705
B -0.234095
C -1.559653
B -0.531421
[10 rows x 1 columns]
>>> idx = np.unique(df.index, return_index=True)[1]
>>> df.iloc[idx]
val
A 0.021372
B 1.229482
C 0.547076
D -1.571025
[4 rows x 1 columns]
回答by danielstn
The 'duplicated' method works for dataframes and for series. Just select on those rows which aren't marked as having a duplicate index:
“重复”方法适用于数据框和系列。只需选择那些没有标记为具有重复索引的行：
df[~df.index.duplicated()]
