Python 通过在DataFrame上操作的类更改变量？

我有一个变量initial_值，等于1000，我想和B列上的值相加。只有当C列等于1而不是0时，initial_值和B列才会相加。因此，类运算后得到的初始值应为1030（或1000+10-30+70+10）。到目前为止，我已经尝试：

import pandas as pd
from __future__ import division
import numpy as np

    df = pd.DataFrame({"A":[40,50,60,70,20,30,40,10,10,80,60,40,50],\
 "B":[0,10,10,10,-50,10,10,-30,0,70,-20,-20,10], \
 "C":[0,0,0,1,0,0,0,1,0,1,0,0,1]})

A = df['A']
B = df['B']
C = df['C']

initial_value = 1000.00

class test:
    def __init__(self, A, B, C, initial_value):
        self.A = A
        self.B = B
        self.C = C
        self.initial_value = initial_value

    def test_values(self):
        self.initial_value = self.initial_value + self.B

        return self.initial_value

x = test(A, B, C, initial_value)
x.test_values()

print x

您可以将B列和C列相乘，然后将结果相加：

def test_values(self):
    self.initial_value = self.initial_value + self.B.mul(self.C).sum()
                                            # ^^^^^^^^^^^^^^^^^^^^^^^^
    return self.initial_value
​​
x = test(A, B, C, initial_value)
x.test_values()
# 1060.0

您可以将B列和C列相乘，然后将结果相加：

def test_values(self):
    self.initial_value = self.initial_value + self.B.mul(self.C).sum()
                                            # ^^^^^^^^^^^^^^^^^^^^^^^^
    return self.initial_value
​​
x = test(A, B, C, initial_value)
x.test_values()
# 1060.0

这将有助于：

def test_values(self):
    self.inital_value += sum(self.B*self.C)
    return self.initial_value

将C和B的乘积求和：

import pandas as pd
from __future__ import division
import numpy as np

df = pd.DataFrame({"A":[40,50,60,70,20,30,40,10,10,80,60,40,50],\
"B":[0,10,10,10,-50,10,10,-30,0,70,-20,-20,10], \
"C":[0,0,0,1,0,0,0,1,0,1,0,0,1]})

A = df['A']
B = df['B']
C = df['C']

initial_value = 1000.00

class test:
    def __init__(self, A, B, C, initial_value):
        self.A = A
        self.B = B
        self.C = C
        self.initial_value = initial_value

    def test_values(self):
        self.inital_value += sum(self.B*self.C)
        return self.initial_value

x = test(A, B, C, initial_value)
print(x.test_values())

这将有助于：

def test_values(self):
    self.inital_value += sum(self.B*self.C)
    return self.initial_value

将C和B的乘积求和：

import pandas as pd
from __future__ import division
import numpy as np

df = pd.DataFrame({"A":[40,50,60,70,20,30,40,10,10,80,60,40,50],\
"B":[0,10,10,10,-50,10,10,-30,0,70,-20,-20,10], \
"C":[0,0,0,1,0,0,0,1,0,1,0,0,1]})

A = df['A']
B = df['B']
C = df['C']

initial_value = 1000.00

class test:
    def __init__(self, A, B, C, initial_value):
        self.A = A
        self.B = B
        self.C = C
        self.initial_value = initial_value

    def test_values(self):
        self.inital_value += sum(self.B*self.C)
        return self.initial_value

x = test(A, B, C, initial_value)
print(x.test_values())