使用pandas如何对某些参数（列）进行加权，以便基于加权方式获取输出

Question

在我的数据集中，所有参数都有定性变量

当我的所有参数（列）对于一行不同时，我们给我们该变量的权重

for column-Irrigated we giving us 40% weightage,
for soil we giving us 35% weightage and
for seed variety we giving us 25% weightage,

• 因此，当所有参数给出不同的值时，将根据我们计算的权重(40%)为Irrigated column值选择输出

• 如果重复2次以上，则输出将显示为重复2次的值

任何建议都会有帮助

>>> import pandas as pd
>>> data = {'District':  ['Ahmednagar', 'Aurangabad','Jalna','Buldhana','Amravati','Nashik','Pune','Palghar'],
        'Soil': ['B','A','D','D','A','B','D','A' ],
    'Irrigated': ['B','B','D','A','A','B','C','A' ],
    'Seed Variety': ['A','B','B','B','A','A','A','D']
        }
>>> data
{'District': ['Ahmednagar', 'Aurangabad', 'Jalna', 'Buldhana', 'Amravati', 'Nashik', 'Pune', 'Palghar'], 'Soil': ['B', 'A', 'D', 'D', 'A', 'B', 'D', 'A'], 'Seed Variety': ['A', 'B', 'B', 'B', 'A', 'A', 'A', 'D'], 'Irrigated': ['B', 'B', 'D', 'A', 'A', 'B', 'C', 'A']}
>>> df = pd.DataFrame (data, columns = ['District','Soil','Irrigated','Seed Variety'])
>>> df
     District  ... Seed Variety
0  Ahmednagar  ...            A
1  Aurangabad  ...            B
2       Jalna  ...            B
3    Buldhana  ...            B
4    Amravati  ...            A
5      Nashik  ...            A
6        Pune  ...            A
7     Palghar  ...            D

[8 rows x 4 columns]
>>> 

Answer 1

so when all parameters giving different value, then it will be select output for Irrigated column value [...] if more than 2 times repeated then output will be display as which value repeated 2 times.

因此，这意味着只有当其他两列“土壤”和“种子品种”具有相同的值时，产量才会不同于“灌溉”

因此，我首先填充“输出”以匹配“灌溉”，然后在后续操作中，将其设置为另一列的值，其中另外两列具有相同的值：

df['Output'] = df['Irrigated']
df.loc[df['Soil'] == df['Seed Variety'], 'Output'] = df['Soil']

应该这样做

稍后，如果要计算总百分比，可以将结果“输出”与源列进行比较，然后将其乘以每个权重：

df['Output(%)'] = (
    (df['Output'] == df['Soil']) * 35.0 +
    (df['Output'] == df['Irrigated']) * 40.0 +
    (df['Output'] == df['Seed Variety']) * 25.0
)