Python 从dataframe中的特定行创建新列

我有一个csv文件，其中每一行代表一个属性，后面是反映属性中房间的可变数量的后续行。我想为每个属性创建一个列，该列汇总每个房间的总建筑面积。数据的非结构化特性使得在

pandas

中很难实现这一点。以下是我目前的表格示例：

id  ba  store_desc      floor_area
0   1   Toy Shop        NaN
1   2   Retail Zone A   29.42
2   2   Retail Zone B   31.29
3   1   Grocery Store   NaN
4   2   Retail Zone A   68.00
5   2   Outside Garden  83.50
6   2   Office          7.30

以下是我正在尝试创建的表：

id  ba  store_desc      floor_area   gross_floor_area
0   1   Toy Shop        NaN          60.71
3   1   Grocery Store   NaN          158.8

有人对如何达到这个结果有什么建议吗？我完全迷路了

Sam

IIUC

df1=df[df['floor_area'].isnull()]

df1['gross_floor_area']=df.groupby(df['floor_area'].isnull().cumsum())['floor_area'].sum().values

df1
Out[463]: 
   id  ba    store_desc  floor_area  gross_floor_area
0   0   1       ToyShop         NaN             60.71
3   3   1  GroceryStore         NaN            158.80

IIUC

---

首先创建一个名为category的临时列，然后将其向前填充，按该列分组以获得总和，然后将其映射回相关的store_desc值

df['category'] = df[df.floor_area.isnull()]['store_desc']

df['category'].fillna(method='ffill',inplace=True)

df['gross_floor_area'] = df.store_desc.map(df.groupby('category').sum().floor_area)

df.drop('category',axis=1,inplace=True)

df[df.gross_floor_area.notnull()]

---

首先创建一个名为category的临时列，然后将其向前填充，按该列分组以获得总和，然后将其映射回相关的store_desc值

df['category'] = df[df.floor_area.isnull()]['store_desc']

df['category'].fillna(method='ffill',inplace=True)

df['gross_floor_area'] = df.store_desc.map(df.groupby('category').sum().floor_area)

df.drop('category',axis=1,inplace=True)

df[df.gross_floor_area.notnull()]