pandas to_numeric

여러컬럼

import pandas as pd

df = pd.DataFrame({
    'A': ['a', 'a', 'b', 'b', 'c', 'c','x'],
    'B': ['x', 'y', 'x', 'y', 'x', 'y','y'],
    'C': [10.5, '20', 30.2, 'aaa', '50.1', '60',None],
    'D': [1.0, '2', 3.2, 'bbb', 5.1, '6',None]
})
numeric_cols = ['C', 'D']
#방법1
df = df.assign(**{col: pd.to_numeric(df[col], errors='coerce').fillna(0).astype(int) for col in numeric_cols})
#방법2
df[numeric_cols] = df[numeric_cols].apply(lambda col: pd.to_numeric(col, errors='coerce').fillna(0).astype(int))

grouped = df.groupby(['A', 'B'])
result = grouped[numeric_cols].sum().reset_index()

print(result)

컬럼하나

import pandas as pd

df = pd.DataFrame({
    'A': ['a', 'a', 'b', 'b', 'c', 'c','x'],
    'B': ['x', 'y', 'x', 'y', 'x', 'y','y'],
    'C': ['10.5', '20', 30.2, 'aaa', 50.1, '60',None]
})

df['A'] = df['A'].astype(str)
df['B'] = df['B'].astype(str)

df['C'] = pd.to_numeric(df['C'], errors='coerce').fillna(0).astype(int)

grouped = df.groupby(['A', 'B'])
result = grouped['C'].sum().reset_index()

print(result)