Pandas合并列中的行

import pandas as pd

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

# 沿着列方向合并
result1 = pd.concat([df1, df2], axis=1)

# 沿着行方向合并
result2 = pd.concat([df1, df2], axis=0)

import pandas as pd

df1 = pd.DataFrame({'key': ['A', 'B', 'C'], 'value1': [1, 2, 3]})
df2 = pd.DataFrame({'key': ['B', 'C', 'D'], 'value2': [4, 5, 6]})

# 内连接合并
result1 = pd.merge(df1, df2, on='key', how='inner')

# 左连接合并
result2 = pd.merge(df1, df2, on='key', how='left')

import pandas as pd

df1 = pd.DataFrame({'A': [1, 2, 3], 'B': [4, 5, 6]}, index=[0, 1, 2])
df2 = pd.DataFrame({'C': [7, 8, 9], 'D': [10, 11, 12]}, index=[1, 2, 3])

# 左连接合并
result1 = df1.join(df2, how='left')

# 内连接合并
result2 = df1.join(df2, how='inner')