如何合并包含 Pandas 中特定值的行 [重复]答案

【问题标题】：How can I merge rows that contains a specific value in Pandas [duplicate]如何合并包含 Pandas 中特定值的行 [重复]
【发布时间】：2022-11-27 10:31:59
【问题描述】：

我想合并包含特定值的行，但是，我希望合并的行具有新列。

例子

import pandas as pd


df = pd.DataFrame([{'Day': "Monday", 'Item_1':   "Shirt", 'Item_2': "Mug",   'Item_3': "Pen"},
                   {'Day': "Monday", 'Item_1':   "Shoes", 'Item_2': "Tea",   'Item_3': "Book"},
                   {'Day': "Tuesday", 'Item_1':"Charger", 'Item_2': "Router",'Item_3': "Phone"},
                   {'Day': "Tuesday", 'Item_1':"Monitor", 'Item_2': "Toy",   'Item_3': "Chair"},
                   {'Day': "Friday", 'Item_1':   "Shirt", 'Item_2': "TV",    'Item_3': "Desk"}])

df


Day Item_1  Item_2  Item_3
0   Monday  Shirt   Mug Pen
1   Monday  Shoes   Tea Book
2   Tuesday Charger Router  Phone
3   Tuesday Monitor Toy Chair
4   Friday  Shirt   TV  Desk

我希望像这样合并同一天的任何行


Day  Item_1     Item_2     Item_3     Item_1_1     Item_2_1     Item_3_1
Monday   Shirt      Mug        Pen    Shoes        Tea      Book
Tuesday  Charger    Router     Phone  Monitor      Toy      Chair
Friday   Shirt      TV         Desk   NaN          NaN      NaN

有没有办法这样做？

【问题讨论】：

标签： python pandas dataframe machine-learning

【解决方案1】：

我想你可以在这里使用groupby：

df = (df
      .groupby('Day', sort=False)
      .apply(lambda x: x.to_numpy())
      .apply(np.concatenate)
      .apply(pd.Series)
      .reset_index(drop=True)
      )

# fix col names
df.columns = ['Day'] + [f'Item_{x}' for x in range(1, df.shape[1])]

print(df)

       Day   Item_1  Item_2 Item_3   Item_4   Item_5 Item_6 Item_7
0   Monday    Shirt     Mug    Pen   Monday    Shoes    Tea   Book
1  Tuesday  Charger  Router  Phone  Tuesday  Monitor    Toy  Chair
2   Friday    Shirt      TV   Desk      NaN      NaN    NaN    NaN

【讨论】：