[PYTHON/PANDAS] merge 함수 : on/how 인자를 사용해 RIGHT OUTER JOIN 데이터 만들기

■ merge 함수에사 on/how 인자를 사용해 RIGHT OUTER JOIN 데이터를 만드는 방법을 보여준다.

▶ main.py


import pandas as pd
import numpy  as np

dataFrame1 = pd.DataFrame({"key" : ["A", "B", "C", "D"], "value" : np.random.randn(4)})
dataFrame2 = pd.DataFrame({"key" : ["B", "D", "D", "E"], "value" : np.random.randn(4)})

print(dataFrame1)

"""
  key     value
0   A  1.604546
1   B -1.037901
2   C -0.910113
3   D -0.925161
"""

print()

print(dataFrame2)

"""
  key     value
0   B -0.448881
1   D -0.173234
2   D  0.109069
3   E -0.766205
"""

print()

dataFrame3 = pd.merge(dataFrame1, dataFrame2, on = "key", how = "right") # RIGHT OUTER JOIN

print(dataFrame3)

"""
  key   value_x   value_y
0   B -1.037901 -0.448881
1   D -0.925161 -0.173234
2   D -0.925161  0.109069
3   E       NaN -0.766205
"""

import pandas as pd

import numpy as np

dataFrame1 = pd.DataFrame({"key" : ["A", "B", "C", "D"], "value" : np.random.randn(4)})

dataFrame2 = pd.DataFrame({"key" : ["B", "D", "D", "E"], "value" : np.random.randn(4)})

print(dataFrame1)

"""

key value

0 A 1.604546

1 B -1.037901

2 C -0.910113

3 D -0.925161

"""

print()

print(dataFrame2)

"""

key value

0 B -0.448881

1 D -0.173234

2 D 0.109069

3 E -0.766205

"""

print()

dataFrame3 = pd.merge(dataFrame1, dataFrame2, on = "key", how = "right") # RIGHT OUTER JOIN

print(dataFrame3)

"""

key value_x value_y

0 B -1.037901 -0.448881

1 D -0.925161 -0.173234

2 D -0.925161 0.109069

3 E NaN -0.766205

"""

▶ requirements.txt


numpy==2.1.2
pandas==2.2.3
python-dateutil==2.9.0.post0
pytz==2024.2
six==1.16.0
tzdata==2024.2

numpy==2.1.2

pandas==2.2.3

python-dateutil==2.9.0.post0

pytz==2024.2

six==1.16.0

tzdata==2024.2

※ pip install pandas 명령을 실행했다.