我们有两个数据框。我们希望所有列都由Dataframe1
组成,但只需要target_name
中的一列(Dataframe2
)。但是,当我们这样做时,它给我们提供了重复的值。
Dataframe1值:
user_id subject_id x y w h g
0 858580 23224814 58.133331 57.466675 181.000000 42.000000 1
1 858580 23224814 293.133331 176.466675 80.000000 34.000000 2
2 313344 28539152 834.049316 37.493195 63.005920 36.444595 1
3 313344 28539152 104.003235 45.072937 242.956024 26.754082 2
4 313344 28539152 635.436829 80.038574 108.716065 35.240089 3
5 313344 28539152 351.910156 80.162117 201.371887 32.738373 4
6 861687 28539165 125.313393 39.836521 231.202873 43.087811 1
7 861687 28539165 623.450500 44.040207 151.332825 34.680435 2
8 1254304 28539165 128.893204 45.765110 225.686691 35.547726 1
Dataframe2值:
Unnamed: 0 user_id subject_id good x y w h T0 T1 T2 T3 T4 T5 T6 T7 T8 target_name target_name_length target_name3
0 0 858580 23224814 1 58.133331 57.466675 181.000000 42.000000 NaN 1801 No, there are still more names to be marked Male 1881 John Abbott NaN NaN NaN John Abbott 11 John Abbott
1 1 858580 23224814 1 293.133331 176.466675 80.000000 34.000000 NaN NaN Yes, I've marked all the names Female NaN NaN Edith Joynt Edith Abbot NaN Edith Joynt 11 Edith Joynt
2 2 340348 30629031 1 152.968750 26.000000 224.000000 41.000000 NaN 1852 No, there are still more names to be marked Male 1924 William Sparrow NaN NaN NaN William Sparrow 15 William Sparrow
3 3 340348 30629031 1 497.968750 325.000000 87.000000 29.000000 NaN NaN Yes, I've marked all the names Female NaN NaN Minnie NaN NaN Minnie 6 Minnie
4 4 340348 28613182 1 103.968750 31.000000 162.000000 38.000000 NaN 1819 No, there are still more names to be marked Male 1876 Albert [unclear]Gles[/unclear] NaN NaN NaN Albert Gles 30 Albert Gles
5 5 340348 28613182 1 107.968750 76.000000 72.000000 25.000000 NaN 1819 Yes, I've marked all the names Female 1884 NaN Eliza [unclear]Gles[/unclear] NaN NaN Eliza Gles 29 Eliza Gles
6 6 340348 30628864 1 172.968750 29.000000 192.000000 41.000000 NaN 1840 No, there are still more names to be marked Male 1918 John Slaltery NaN NaN NaN John Slaltery 13 John Slaltery
7 7 340348 30628864 1 115.968750 214.000000 149.000000 31.000000 NaN NaN No, there are still more names to be marked Male NaN [unclear]P.[/unclear] Slaltery NaN NaN NaN P. Slaltery 30 unclear]P. Slaltery
8 8 340348 30628864 1 537.968750 218.000000 64.000000 26.000000 NaN NaN Yes, I've marked all the names Female 1901 NaN Elizabeth Slaltery NaN NaN Elizabeth Slaltery 18 Elizabeth Slaltery
这是我们尝试使用的代码:
如果您想将target
列盲目添加到dataframe1
,则>>
dataframe1['target'] = dataframe2['target']
只需确保两个数据框具有相同数量的行,并且它们按任何给定的公共列排序。例如:在两个数据框中都找到
user_id