Concat
df = pd.DataFrame(np.random.randn(10, 4)) print(df) # break it into pieces pieces = [df[:3], df[3:7], df[7:]] print(pd.concat(pieces)) # 0 1 2 3 # 0 0.879526 -1.417311 -1.309299 0.287933 # 1 -1.194092 1.237536 -0.375177 -0.622846 # 2 1.449524 1.732103 1.866323 0.327194 # 3 -0.028595 1.047751 0.629286 -0.611354 # 4 -1.237406 0.878287 1.407587 -1.637072 # 5 0.536248 1.172208 0.405543 0.245162 # 6 0.166374 1.185840 0.132388 -0.832135 # 7 0.750722 -1.188307 1.306327 1.564907 # 8 -0.755132 -1.538270 -0.173119 1.341313 # 9 -0.572171 1.808220 0.688190 -0.672612 # 0 1 2 3 # 0 0.879526 -1.417311 -1.309299 0.287933 # 1 -1.194092 1.237536 -0.375177 -0.622846 # 2 1.449524 1.732103 1.866323 0.327194 # 3 -0.028595 1.047751 0.629286 -0.611354 # 4 -1.237406 0.878287 1.407587 -1.637072 # 5 0.536248 1.172208 0.405543 0.245162 # 6 0.166374 1.185840 0.132388 -0.832135 # 7 0.750722 -1.188307 1.306327 1.564907 # 8 -0.755132 -1.538270 -0.173119 1.341313 # 9 -0.572171 1.808220 0.688190 -0.672612
Join
类似 sql 里的 join (联表)
left = pd.DataFrame({‘key‘: [‘foo‘, ‘foo‘], ‘lval‘: [1, 2]}) right = pd.DataFrame({‘key‘: [‘foo‘, ‘foo‘], ‘rval‘: [4, 5]}) print(left) print(right) print(pd.merge(left, right, on=‘key‘)) # key lval # 0 foo 1 # 1 foo 2 # key rval # 0 foo 4 # 1 foo 5 # key lval rval # 0 foo 1 4 # 1 foo 1 5 # 2 foo 2 4 # 3 foo 2 5
Merge
df = pd.DataFrame(np.random.randn(8, 4), columns=[‘A‘,‘B‘,‘C‘,‘D‘]) print(df) s = df.iloc[3] print(s) df.append(s, ignore_index=True) print(df) # A B C D # 0 -1.744799 -0.745689 -0.066827 -0.993191 # 1 0.843984 0.902578 0.845040 1.336861 # 2 0.865214 1.151313 0.277192 -0.711557 # 3 0.917065 -0.948935 0.110977 0.047466 # 4 -1.309586 0.539592 1.956684 -0.117199 # 5 -0.431144 0.884499 -0.828626 -0.506894 # 6 -1.263993 -0.826366 1.426688 -0.434647 # 7 -0.567870 -0.086037 2.166162 -0.396294 # / # A 0.917065 # B -0.948935 # C 0.110977 # D 0.047466 # Name: 3, dtype: float64 # / # A B C D # 0 -1.744799 -0.745689 -0.066827 -0.993191 # 1 0.843984 0.902578 0.845040 1.336861 # 2 0.865214 1.151313 0.277192 -0.711557 # 3 0.917065 -0.948935 0.110977 0.047466 # 4 -1.309586 0.539592 1.956684 -0.117199 # 5 -0.431144 0.884499 -0.828626 -0.506894 # 6 -1.263993 -0.826366 1.426688 -0.434647 # 7 -0.567870 -0.086037 2.166162 -0.396294
原文地址:https://www.cnblogs.com/xkxf/p/8367206.html
时间: 2024-11-07 08:14:29