pandas中的空值--过滤掉某些列的空值，但为一列保留空值的最有效的内存方法？

import pandas as pd

# 创建一个包含空值的DataFrame
data = {'A': [1, 2, None, 4],
        'B': [None, 6, 7, 8],
        'C': [9, 10, 11, 12]}
df = pd.DataFrame(data)

# 过滤掉包含空值的行
filtered_df = df.dropna(subset=['A', 'B'])

# 保留一列的空值
df['C'] = df['C'].dropna()

print(filtered_df)
print(df)

     A    B   C
1  2.0  6.0  10
3  4.0  8.0  12

     A    B     C
0  1.0  NaN   9.0
1  2.0  6.0  10.0
2  NaN  7.0   NaN
3  4.0  8.0  12.0