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pandas:删除与之前的原始数据具有相同列值的行

[英]pandas: delete a row having same value of a column as in previous raw

这是我的df:

data = { 'utime': [1461098442,1461098443,1461098443,1461098444,1461098445],
  'lat': [41.1790265,41.1791703,41.1791464,41.1791703,41.1791419],
  'lon': [-8.5951883,-8.5951229,-8.5951376,-8.5951229,-8.5951365]
}

df = pd.DataFrame(data)
df

       utime        lat        lon
0   1461098442  41.179026   -8.595188
1   1461098443  41.179170   -8.595123
2   1461098443  41.179146   -8.595138
3   1461098444  41.179170   -8.595123
4   1461098445  41.179142   -8.595137

同时收到两个样本(unix epoch 1461098443 ),所以我想保留 1,删除另一个。

所以我有

       utime        lat        lon
0   1461098442  41.179026   -8.595188
1   1461098443  41.179170   -8.595123
3   1461098444  41.179170   -8.595123
4   1461098445  41.179142   -8.595137

drop_duplicates 应该有所帮助(阅读https://pandas.pydata.org/docs/reference/api/pandas.DataFrame.drop_duplicates.ZFC35FDC70D5FC69D269883A822C7A

df.drop_duplicates(subset='utime')
df = df.groupby('utime', as_index=False).agg('first')
        utime        lat       lon
0  1461098442  41.179026 -8.595188
1  1461098443  41.179170 -8.595123
2  1461098444  41.179170 -8.595123
3  1461098445  41.179142 -8.595137

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