KeyError: "['Q19286'] not found in axis"

Dawnstar

1. import pandas as pd
   
2. 
   
3. path = 'G:\\deleted entries\\test\\'
   
4. 
   
5. df1 = pd.read_table(path + 'phosphorylation-len20.txt')
   
6. df1_col = list(df1)#获取DataFrame列标签
   
7. df1_col.insert(0,df1_col.pop(df1_col.index("Uniprot Entry")))#改变列标签为指定顺序
   
8. df1.index = df1['Uniprot Entry']
   
9. print(df1.index)#将这一列设置为索引
   
10. print(df1)
    
11. df2 = pd.read_table(path + 'deleted.txt')
    
12. print(df2.columns)
    
13. x = ''
    
14. for x in df1.index.tolist(): #筛选两列重复值
    
15.     if x in df2["Uniprot Entry"].tolist():
    
16.         df1 = df1.drop(x)  

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#根据索引删除行的方式，删除这些重复的行

df2的'Uniprot Entry'列与df1的'Uniprot Entry'列存在重复值。

目的：筛选这两列的重复值，删除其在df1中所在行。

但运行以上代码会出现报错：
Traceback (most recent call last):

  File "<ipython-input-25-58024f1969bb>", line 1, in <module>
    runfile('G:/Posttranslational modification/uniprot deleted entries/test/test.py')

  File "d:\ProgramData\Anaconda3\lib\site-packages\spyder_kernels\customize\spydercustomize.py", line 827, in runfile
    execfile(filename, namespace)

  File "d:\ProgramData\Anaconda3\lib\site-packages\spyder_kernels\customize\spydercustomize.py", line 110, in execfile
    exec(compile(f.read(), filename, 'exec'), namespace)

  File "G:/Posttranslational modification/uniprot deleted entries/test/test.py", line 30, in <module>
    df1 = df1.drop(x)

  File "d:\ProgramData\Anaconda3\lib\site-packages\pandas\core\frame.py", line 4102, in drop
    errors=errors,

  File "d:\ProgramData\Anaconda3\lib\site-packages\pandas\core\generic.py", line 3914, in drop
    obj = obj._drop_axis(labels, axis, level=level, errors=errors)

  File "d:\ProgramData\Anaconda3\lib\site-packages\pandas\core\generic.py", line 3965, in _drop_axis
    raise KeyError("{} not found in axis".format(labels))

KeyError: "['Q19286'] not found in axis"


找不到原因在哪儿，希望有了解的各路大神帮忙指点一二。

Dawnstar

问题出在

1. for x in df1.index.tolist(): #筛选两列重复值
   
2.     if x in df2["Uniprot Entry"].tolist():

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因为筛选重复值时，重复值出现的次数不是唯一的，要将筛选的重复值中的重复项只保留唯一值就可以了，将代码变为：

1. a = [x for x in df1.index.tolist() if x in df2["Uniprot Entry"].tolist()]
   
2. b = {}.fromkeys(a).keys() #删除列表中重复数据
   
3. for i in b:
   
4.     df1 = df1.drop(i)      

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结果就正确了。