我希望通过指定特定列来删除重复的条目。 该列标记为“sent_name”
print(new_df)
sent_name \
0 Abbey Road Station, London, UK
1 Abbey Wood Station, London, UK
2 Acton Station, London, UK
3 Acton Central Station, London, UK
Name Lat Lng \
0 Abbey Road, London E15, UK 51.531930 0.003760
1 Abbey Wood, London SE2, UK 51.491060 0.121420
2 Station Parade, West Acton London Underground ... 51.518055 -0.281053
3 Acton Central, London W3, UK 51.508720 -0.262950
type
0 [u'transit_station', u'point_of_interest', u'e...
1 [u'transit_station', u'point_of_interest', u'e...
2 [u'train_station', u'transit_station', u'point...
3 [u'transit_station', u'point_of_interest', u'e...
我试过了
new_df.drop_duplicates(["sent_name"])
和
new_df.drop_duplicates(subset="sent_name")
在检查时,这些都不会删除所有重复项。
例如,
1038 Woodford Station, London, UK
1040 Woodford Station, London, UK
1041 Woodford Station, London, UK
1043 Woodford Station, London, UK
1044 Woodford Station, London, UK
1038 South Woodford London Underground Station, Geo... 51.591789 0.027315
1040 Woodford, Woodford, Woodford Green, Greater Lo... 51.606900 0.034000
1041 South Woodford, London E18, UK 51.591910 0.027360
1043 South Woodford (Stop C), London E18, UK 51.591312 0.029013
1044 South Woodford (Stop D), London E18, UK 51.592010 0.027658
1038 [u'train_station', u'transit_station', u'point...
1040 [u'transit_station', u'point_of_interest', u'e...
1041 [u'transit_station', u'point_of_interest', u'e...
1043 [u'transit_station', u'point_of_interest', u'e...
1044 [u'transit_station', u'point_of_interest', u'e...
答案 0 :(得分:1)
您需要将drop_duplicates
的结果分配为默认值inplace=False
,并且几乎所有pandas ops都会返回副本。
所以:
new_df = new_df.drop_duplicates(["sent_name"])
或
new_df.drop_duplicates(["sent_name"], inplace=True)
将起作用