从pandas中的多级DF中检索非空值，并组合多个列

import pandas as pd

# 创建多级DataFrame示例
data = {'A': {('row1', 'subrow1'): 1, ('row1', 'subrow2'): 2, ('row2', 'subrow1'): None},
        'B': {('row1', 'subrow1'): None, ('row1', 'subrow2'): 4, ('row2', 'subrow1'): 5},
        'C': {('row1', 'subrow1'): 6, ('row1', 'subrow2'): None, ('row2', 'subrow1'): 8}}

df = pd.DataFrame(data)

# 检索非空值并组合多个列
result = df[df.apply(lambda x: x.notnull().all(), axis=1)].apply(lambda x: '-'.join(x.dropna().astype(str)), axis=1)

import pandas as pd

# 创建多级DataFrame示例
data = {'A': {('row1', 'subrow1'): 1, ('row1', 'subrow2'): 2, ('row2', 'subrow1'): None},
        'B': {('row1', 'subrow1'): None, ('row1', 'subrow2'): 4, ('row2', 'subrow1'): 5},
        'C': {('row1', 'subrow1'): 6, ('row1', 'subrow2'): None, ('row2', 'subrow1'): 8}}

df = pd.DataFrame(data)

# 检索非空值并组合多个列
result = df[df.apply(lambda x: x.notnull().all(), axis=1)].apply(lambda x: '-'.join(x.dropna().astype(str)), axis=1)

print(result)

row1  subrow1    1-6
dtype: object