展开数据表，添加新行并按组替换NA值

pip install pandas

import pandas as pd
import numpy as np  # 用于创建 NA 值

data = {
    'Group': ['A', 'A', 'B', 'B', 'B'],
    'Value': [10, np.nan, 20, np.nan, 30]
}
df = pd.DataFrame(data)
print(df)

new_rows = pd.DataFrame({
    'Group': ['A', 'B'],
    'Value': [np.nan, np.nan]
})

# 追加新行
df = df.append(new_rows, ignore_index=True)
print(df)

# 计算每组的平均值并填充 NA
df['Value'] = df.groupby('Group')['Value'].transform(lambda x: x.fillna(x.mean()))
print(df)

import pandas as pd
import numpy as np

# 创建数据
data = {
    'Group': ['A', 'A', 'B', 'B', 'B'],
    'Value': [10, np.nan, 20, np.nan, 30]
}
df = pd.DataFrame(data)

# 添加新行
new_rows = pd.DataFrame({
    'Group': ['A', 'B'],
    'Value': [np.nan, np.nan]
})
df = df.append(new_rows, ignore_index=True)

# 按组替换 NA
df['Value'] = df.groupby('Group')['Value'].transform(lambda x: x.fillna(x.mean()))

print(df)