使用序列覆盖多索引数据帧的切片

import pandas as pd

# 创建一个示例多索引数据帧
arrays = [
    ['A', 'A', 'B', 'B'],
    ['one', 'two', 'one', 'two']
]
index = pd.MultiIndex.from_arrays(arrays, names=('first', 'second'))
df = pd.DataFrame({'value': [10, 20, 30, 40]}, index=index)

# 使用序列覆盖切片
selected_rows = df.loc[(['A', 'B'], ['one'])]
print(selected_rows)

# 使用更宽松的条件
selected_rows = df.loc[(slice(None), 'one'), :]
print(selected_rows)

# 检查索引是否存在
if all(idx in df.index for idx in sequence):
    selected_rows = df.loc[sequence]
else:
    print("Some indices are missing in the DataFrame.")

import pandas as pd

# 创建一个示例多索引数据帧
arrays = [
    ['A', 'A', 'B', 'B'],
    ['one', 'two', 'one', 'two']
]
index = pd.MultiIndex.from_arrays(arrays, names=('first', 'second'))
df = pd.DataFrame({'value': [10, 20, 30, 40]}, index=index)

# 使用序列覆盖切片
sequence = [('A', 'one'), ('B', 'one')]
selected_rows = df.loc[sequence]
print("Selected Rows:\n", selected_rows)

# 处理缺失索引
sequence_with_missing = [('A', 'one'), ('C', 'one')]
if all(idx in df.index for idx in sequence_with_missing):
    selected_rows = df.loc[sequence_with_missing]
else:
    print("Some indices are missing in the DataFrame.")