Pandas 행 병합

1 개요[ | ]

Concatenating objects
Pandas 데이터프레임 행 병합

2 예시 1[ | ]

from numpy import NaN
import pandas as pd

df1 = pd.DataFrame([
[ 'A', 'Alice', 90 , 60  ],
[ 'A', 'Bob'  , 80 , NaN ],
],columns=['Class','Name','English','Math'])

df2 = pd.DataFrame([
[ 'B', 'Carol', NaN, 60  ],
[ 'B', 'Dave' , 60 , NaN ],
],columns=['Class','Name','English','Math'])

df3 = pd.concat([df1, df2])
print( 'df3:\n', df3 )

df4 = pd.concat([df2, df1])
print( 'df4:\n', df4 )

3 예시 2[ | ]

import pandas as pd
df1 = pd.DataFrame({'A': ['A0', 'A1', 'A2', 'A3'],
                    'B': ['B0', 'B1', 'B2', 'B3'],
                    'C': ['C0', 'C1', 'C2', 'C3'],
                    'D': ['D0', 'D1', 'D2', 'D3']},
                   index=[0, 1, 2, 3])
df2 = pd.DataFrame({'A': ['A4', 'A5', 'A6', 'A7'],
                    'B': ['B4', 'B5', 'B6', 'B7'],
                    'C': ['C4', 'C5', 'C6', 'C7'],
                    'D': ['D4', 'D5', 'D6', 'D7']},
                   index=[4, 5, 6, 7])
df3 = pd.DataFrame({'A': ['A8', 'A9', 'A10', 'A11'],
                    'B': ['B8', 'B9', 'B10', 'B11'],
                    'C': ['C8', 'C9', 'C10', 'C11'],
                    'D': ['D8', 'D9', 'D10', 'D11']},
                   index=[8, 9, 10, 11])
pd.concat([df1, df2, df3])

4 같이 보기[ | ]

5 참고[ | ]

https://pandas.pydata.org/pandas-docs/stable/user_guide/merging.html