Question

具有如下数据框：

1   Jacke Chan  China       1
2   Jason       Great       2
3   Statham     Britain     2
4   Rock        United      3
5   Dwayne      States      3
6   Johnson     California  3
7   Jack Ma     China       4

我需要了解以下信息：

1   Jackie Chan            China
2   Jason Statham          Great Britain
3   Rock Dwayne Johnson    United States California
4   Jack Ma                China

Answer 1

这应该做到：

df = df.groupby(by=[3], as_index=False).agg(' '.join).drop(columns=[3])
print(df)

                     1                         2
0           Jacke Chan                     China
1        Jason Statham             Great Britain
2  Rock Dwayne Johnson  United States California
3              Jack Ma                     China

Answer 2

您可以尝试以下方法：

df = pd.DataFrame({'name ': {0: 'Jacke Chan',
  1: 'Jason',
  2: 'Statham',
  3: 'Rock',
  4: 'Dwayne',
  5: 'Johnson',
  6: 'Jack Ma'},
 'country': {0: 'China',
  1: 'Great',
  2: 'Britain',
  3: 'United',
  4: 'States',
  5: 'California',
  6: 'China'},
 'no': {0: 1, 1: 2, 2: 2, 3: 3, 4: 3, 5: 3, 6: 4}})


df.groupby("no").agg(" ".join).reset_index()

Answer 3

这也将起作用

df_new=df.groupby(3, sort=False)[1].apply(' '.join)
fd_new=df.groupby(3, sort=False)[2].apply(' '.join)

合并熊猫数据框的行的内容

3 个答案: