以优化方式填充pandas数据帧

import pandas as pd

# 创建一个示例数据帧
df = pd.DataFrame({
    'A': [1, None, 3],
    'B': [None, 5, None]
})

# 使用特定值填充缺失值
df_filled = df.fillna(0)
print(df_filled)

# 使用前向填充
df_ffill = df.fillna(method='ffill')
print(df_ffill)

# 使用后向填充
df_bfill = df.fillna(method='bfill')
print(df_bfill)

# 替换特定值
df_replaced = df.replace({None: 0})
print(df_replaced)

# 自定义填充函数
def custom_fill(row):
    if pd.isna(row['A']):
        return row['B']
    elif pd.isna(row['B']):
        return row['A']
    else:
        return row['A']

# 应用自定义填充函数
df_custom_filled = df.apply(custom_fill, axis=1)
print(df_custom_filled)

df.fillna(0, inplace=True)

import numpy as np

df['A'] = np.where(pd.isna(df['A']), df['B'], df['A'])