英文:
How to use Pandas to find relative share of rooms in individual floors
问题
我有一个名为df的数据框，其结构如下：
Floor Room Area
0 1 Living room 25
1 1 Kitchen 20
2 1 Bedroom 15
3 2 Bathroom 21
4 2 Bedroom 14
我想要添加一个名为floor_share的系列，用于表示给定楼层的相对份额/比率，以便数据框变成以下形式：
Floor Room Area floor_share
0 1 Living room 18 0.30
1 1 Kitchen 18 0.30
2 1 Bedroom 24 0.40
3 2 Bathroom 10 0.67
4 2 Bedroom 20 0.33
如果可以使用一行代码（或任何其他习惯的方法）来完成此操作，我将非常高兴学习如何实现。
当前的解决方法
我已经找到了一个可以产生正确结果的方法，首先通过以下方式找到每个楼层的总面积：
floor_area_sums = df.groupby('Floor')['Area'].sum()
这将产生以下结果：
Floor
1 60
2 35
Name: Area, dtype: int64
然后，我初始化了一个新的系列为0，并在遍历数据框行时找到正确的值：
df["floor_share"] = 0
for idx, row in df.iterrows():
df.loc[idx, 'floor_share'] = df.loc[idx, 'Area'] / floor_area_sums[row.Floor]
英文:
I have a dataframe df with the following structure
Floor Room Area
0 1 Living room 25
1 1 Kitchen 20
2 1 Bedroom 15
3 2 Bathroom 21
4 2 Bedroom 14
and I want to add a series floor_share with the relative share/ratio of the given floor, so that the dataframe becomes
Floor Room Area floor_share
0 1 Living room 18 0,30
1 1 Kitchen 18 0,30
2 1 Bedroom 24 0,40
3 2 Bathroom 10 0,67
4 2 Bedroom 20 0,33
If it is possible to do this with a one-liner (or any other idiomatic manner), I'll be very happy to learn how.
Current workaround
What I have done that produces the correct results is to first find the total floor areas by
floor_area_sums = df.groupby('Floor')['Area'].sum()
which gives
Floor
1 60
2 35
Name: Area, dtype: int64
I then initialize a new series to 0, and find the correct values while iterating through the dataframe rows.
df["floor_share"] = 0
for idx, row in df.iterrows():
df.loc[idx, 'floor_share'] = df.loc[idx, 'Area']/floor_area_sums[row.Floor]
答案1
得分: 0
IIUC 使用：
df["floor_share"] = df['Area'].div(df.groupby('Floor')['Area'].transform('sum'))
print(df)
结果：
Floor Room Area floor_share
0 1 Living room 18 0.300000
1 1 Kitchen 18 0.300000
2 1 Bedroom 24 0.400000
3 2 Bathroom 10 0.333333
4 2 Bedroom 20 0.666667
英文:
IIUC use:
df["floor_share"] = df['Area'].div(df.groupby('Floor')['Area'].transform('sum'))
print (df)
Floor Room Area floor_share
0 1 Living room 18 0.300000
1 1 Kitchen 18 0.300000
2 1 Bedroom 24 0.400000
3 2 Bathroom 10 0.333333
4 2 Bedroom 20 0.666667
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