Python Pandas连接行并合并值

import pandas as pd

# 创建两个DataFrame对象
df1 = pd.DataFrame({'A': [1, 2, 3], 'B': [4, 5, 6]})
df2 = pd.DataFrame({'A': [7, 8, 9], 'B': [10, 11, 12]})

# 使用concat函数连接两个DataFrame对象
result = pd.concat([df1, df2])

print(result)

   A   B
0  1   4
1  2   5
2  3   6
0  7  10
1  8  11
2  9  12

import pandas as pd

# 创建两个DataFrame对象
df1 = pd.DataFrame({'A': [1, 2, 3], 'B': [4, 5, 6]})
df2 = pd.DataFrame({'A': [2, 3, 4], 'C': [7, 8, 9]})

# 使用merge函数合并两个DataFrame对象
result = pd.merge(df1, df2, on='A')

print(result)

   A  B  C
0  2  5  7
1  3  6  8

import pandas as pd

# 创建两个DataFrame对象
df1 = pd.DataFrame({'A': [1, 2, 3], 'B': [4, 5, 6]}, index=['a', 'b', 'c'])
df2 = pd.DataFrame({'C': [7, 8, 9], 'D': [10, 11, 12]}, index=['b', 'c', 'd'])

# 使用join函数合并两个DataFrame对象
result = df1.join(df2)

print(result)

   A  B    C     D
a  1  4  NaN   NaN
b  2  5  7.0  10.0
c  3  6  8.0  11.0