swaplevel()和reorder_levels()有什么不同？

import pandas as pd

# 创建一个多级索引的DataFrame
data = {'A': [1, 2, 3, 4],
        'B': [5, 6, 7, 8]}
index = pd.MultiIndex.from_tuples([('x', 'a'), ('x', 'b'), ('y', 'a'), ('y', 'b')])
df = pd.DataFrame(data, index=index)

# 交换索引级别的顺序
df_swapped = df.swaplevel(0, 1)

print(df_swapped)

     A  B
a x  1  5
b x  2  6
a y  3  7
b y  4  8

import pandas as pd

# 创建一个多级索引的DataFrame
data = {'A': [1, 2, 3, 4],
        'B': [5, 6, 7, 8]}
index = pd.MultiIndex.from_tuples([('x', 'a'), ('x', 'b'), ('y', 'a'), ('y', 'b')])
df = pd.DataFrame(data, index=index)

# 重新排序索引级别的顺序
df_reordered = df.reorder_levels([1, 0])

print(df_reordered)

     A  B
a x  1  5
b x  2  6
a y  3  7
b y  4  8