组合两列不同的数据帧

import pandas as pd

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

# 垂直合并
result = pd.concat([df1, df2])
print(result)

import pandas as pd

# 创建两个数据帧
df1 = pd.DataFrame({'key': ['K0', 'K1', 'K2'], 'A': ['A0', 'A1', 'A2']})
df2 = pd.DataFrame({'key': ['K0', 'K1', 'K2'], 'B': ['B0', 'B1', 'B2']})

# 水平合并
result = pd.merge(df1, df2, on='key')
print(result)

result = pd.merge(df1, df2, on='key', suffixes=('_left', '_right'))

# 检查并清理数据
df1 = df1.drop_duplicates(subset='key')
df2 = df2.drop_duplicates(subset='key')
result = pd.merge(df1, df2, on='key')

# 分块处理
chunksize = 1000
for chunk in pd.read_csv('large_file.csv', chunksize=chunksize):
    result = pd.concat([result, chunk])