Pandas DataFrame进行数据拼接方法详解

import pandas as pd

# 纵向拼接（行追加）
df1 = pd.DataFrame({'A': ['A0', 'A1'], 'B': ['B0', 'B1']})
df2 = pd.DataFrame({'A': ['A2', 'A3'], 'B': ['B2', 'B3']})
result_vertical = pd.concat([df1, df2], ignore_index=True)

# 横向拼接（列合并）
df3 = pd.DataFrame({'C': ['C0', 'C1'], 'D': ['D0', 'D1']}, index=[0,1])
result_horizontal = pd.concat([df1, df3], axis=1)

# 内连接（保留共有键）
left = pd.DataFrame({'key': ['K0', 'K1'], 'A': ['A0', 'A1']})
right = pd.DataFrame({'key': ['K0', 'K2'], 'B': ['B0', 'B2']})
result_inner = pd.merge(left, right, on='key', how='inner')

# 外连接（保留所有键，缺值填NaN）
result_outer = pd.merge(left, right, on='key', how='outer')

result_outer

left_df = pd.DataFrame({'value': [1, 2]}, index=['A', 'B'])
right_df = pd.DataFrame({'value': [7, 8]}, index=['A', 'C'])
joined = left_df.join(right_df, how='inner', lsuffix='_left', rsuffix='_right')

joined

df1 = pd.DataFrame({'A': [1, None, 3], 'B': [4, 5, None]}, index=['X', 'Y', 'Z'])
df2 = pd.DataFrame({'A': [None, 10, 11], 'B': [7, 8, 9]}, index=['Y', 'Z', 'W'])
filled = df1.combine_first(df2)

filled