删除重复的 pandas 数据框

问题描述

使用drop_duplicates从数据框中删除重复的列时，我收到一条错误消息.

I am getting an error message when using drop_duplicates to drop duplicate columns from my dataframe.

ValueError: Buffer has wrong number of dimensions (expected 1, got 2)

下面是一个最小的示例(请注意，我这里没有重复的列名，因为那样的话就不会添加该列，所以我的var1在我的实际数据帧中将被称为var0)

Below is a min example (notice that I don't have duplicate column names here, since that column won't be added then, so I var1 would be called var0 in my actual dataframe)

dict1 = [{'var0': 0, 'var1': 0, 'var2': 2},
         {'var0': 0, 'var1': 0, 'var2': 4},
         {'var0': 0, 'var1': 0, 'var2': 8},
         {'var0':0, 'var1': 0, 'var2': 12},]
df = pd.DataFrame(dict1, index=['s1', 's2','s1','s2'])
df.T.drop_duplicates().T

推荐答案

问题出在索引上，当您转置DataFrame时，会得到重复的列名，这些列名将其弄乱了.见下文

The problem is with your indexing, when you transpose your DataFrame you will get duplicate column names which are messing it up. See below

dict1 = [{'var0': 0, 'var1': 0, 'var2': 2},
         {'var0': 0, 'var1': 0, 'var2': 4},
         {'var0': 0, 'var1': 0, 'var2': 8},
         {'var0':0, 'var1': 0, 'var2': 12},]
df = pd.DataFrame(dict1, index=['s1', 's2','s1','s2'])
df.reset_index().T.drop_duplicates().T.set_index('index')

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