pandas groupby sum fillna astype

 

data = {
    'Name': ['Alice', 'Bob', 'Charlie', 'David', 'Eve', 'Frank'],
    'Department': ['Sales', 'Sales', 'IT', 'IT', 'HR', 'HR'],
    'Score': ['100', '200', '300', '400', '500', None]
}

df = pd.DataFrame(data)

# 데이터 타입을 int로 변환하고, None 값을 0으로 채우기
df['Score'] = df['Score'].astype(int).fillna(0)

grouped = df.groupby(['Department'])['Score'].sum().reset_index()
print(grouped)

  Department  Score
0        HR   1000
1         IT   1000
2      Sales   1000

sum column1개

import pandas as pd

data = {'A': ['a', 'b', 'c', 'a', 'b'], 
        'B': ['a', 'b', 'c', 'a', 'b'],
        'C1': ['10', '20', '30', 'abc', '50']}
df = pd.DataFrame(data)

# 결측치 처리
df['C1'] = df['C1'].fillna(0).astype(int)

# groupby 수행
grouped = df.groupby(['A', 'B'])
result = grouped['C1'].sum().reset_index()
print(result)

sum column 복수

import pandas as pd

data = {'A': ['a', 'b', 'c', 'a', 'b'], 
        'B': ['a', 'b', 'c', 'a', 'b'],
        'C1': ['10', '20', '30', 'abc', '50'],
        'C2': [1, 2, 3, 'def', 5]}
df = pd.DataFrame(data)

# 결측치 처리
df['C1'] = df['C1'].fillna(0).astype(int)
df['C2'] = df['C2'].fillna(0).astype(int)

# groupby 수행
grouped = df.groupby(['A', 'B'])
result = grouped[['C1', 'C2']].sum().reset_index()
print(result)