Question

我正在尝试编写一个for循环来迭代我的索引，只保留那些有重复的索引。

我当前的数据框是两个合并在一起的

                  0.0102700     0.0308099     0.0616199      0.123240  \   
5000000000010  4.330760e-05  4.442720e-05  9.232970e-05  1.994190e-04   
5000000000238  6.006910e-04  6.041130e-04  1.220220e-03  2.500240e-03
...

              0.00902317     0.0270695     0.0451159     0.0631622  \ 
5000000000010  6.962980e-05  7.063750e-05  7.165970e-05  7.269680e-05   
5000000000234  4.638970e-04  4.716010e-04  4.794320e-04  4.873930e-04

 New = pd.concat([SFR_low, SFR_high])
 New = New.sort_index()
 print(New)

                 0.00902317     0.0102700     0.0270695     0.0308099  \
5000000000010  6.962980e-05           NaN  7.063750e-05           NaN   
5000000000010           NaN  4.330760e-05           NaN  4.442720e-05   
5000000000081  6.299210e-05           NaN  6.299320e-05           NaN   
5000000000082           NaN  8.176550e-04           NaN  8.172630e-04

我需要一个新的数据框，只保留具有重复索引的行。

Answer 1

使用Index.duplicated参数keep=False：

print (df.index[df.index.duplicated(keep=False)])
Int64Index([1000, 1000, 1002, 1002], dtype='int64')


for i in df.index[df.index.duplicated(keep=False)]:
    print (i)
1000
1000
1002
1002

如果需要过滤具有重复索引的行，请使用boolean indexing：

print (New.index.duplicated(keep=False))
[ True  True False False]

print (New[New.index.duplicated(keep=False)])
               0.00902317  0.0102700  0.0270695  0.0308099  0.0451159  \
5000000000010         NaN   0.000043        NaN   0.000044        NaN   
5000000000010     0.00007        NaN   0.000071        NaN   0.000072   

               0.0616199  0.0631622  0.123240  
5000000000010   0.000092        NaN  0.000199  
5000000000010        NaN   0.000073       NaN

Answer 2

li = [1000,1000,1001,1002,1002]
for i in li:
    temp = i
    count = 0
    for j in li:
        if j is temp:
            count +=1
    if count > 1:
        print i

这可以解决您的要求吗？

Answer 3

在询问前先尝试一些代码：有很多重复的问题

a = [1000,1000,1001,1002,1002]
c = [x for x in a if a.count(x) > 1]
print c

在Python中迭代索引

3 个答案: