将多个数据框合并为一个而不创建重复列

Question

我有三个数据框：

array = {'name': ['Trevor', 'John', 'Trevor', 'John', 'Trevor', 'Trevor', 'John'], 'day': ['2020-10-11 08:00:00', '2020-10-11 08:00:00', '2020-10-11 08:00:00', '2020-10-11 08:00:00', '2020-10-11 08:00:00'
        , '2020-10-11 12:34:00', '2020-10-11 09:12:00'], 'number': [5,0,3,5,1,8,6]}
df = pd.DataFrame(array)
array1 = {'name': ['Trevor'], 'color': ['red']}
df1 = pd.DataFrame(array1)
array2 = {'name': ['John'], 'color': ['blue']}
df2 = pd.DataFrame(array2)
df

我想将 df1 & df2 合并到现实世界中的 df 我有数百个 df1、df2、df3...)，所以输出将是：

    name    day              number color
0   Trevor  2020-10-11 08:00:00 5   red
1   John    2020-10-11 08:00:00 0   blue
2   Trevor  2020-10-11 08:00:00 3   red
3   John    2020-10-11 08:00:00 5   blue
4   Trevor  2020-10-11 08:00:00 1   red
5   Trevor  2020-10-11 12:34:00 8   red
6   John    2020-10-11 09:12:00 6   blue

Answer 1

看起来像merge 和concat：

df.merge(pd.concat([df1,df2]), on='name', how='left')

输出：

     name                  day  number color
0  Trevor  2020-10-11 08:00:00       5   red
1    John  2020-10-11 08:00:00       0  blue
2  Trevor  2020-10-11 08:00:00       3   red
3    John  2020-10-11 08:00:00       5  blue
4  Trevor  2020-10-11 08:00:00       1   red
5  Trevor  2020-10-11 12:34:00       8   red
6    John  2020-10-11 09:12:00       6  blue

---

更新：每次收到新的df# 时尝试更新loc：

df.loc[df['name'].isin(df1['name']), 'color'] = df1['color'].iloc[0]

df.loc[df['name'].isin(df2['name']), 'color'] = df2['color'].iloc[0]

Answer 2

pd.merge(df,df1.append(df2), how='left', on='name')