Python 3.x 根据A列和A列中的值填写C列；B使用数据帧

我试图在pandas数据框架中创建一个新列，其值基于其他两列的值

我尝试使用嵌套的if语句来检查每列中的值，但结果只检查第一行，并根据第一个条目填充其余行

if np.where(df['Person A']=='Yes'):
    if np.where(df['Person B']=='Yes'):
        df['Consensus'] = 'Person A said yes, then Person B said yes'
    elif np.where(df['Person B']=='No'):
        df['Consensus'] = 'Person B said yes, then person B said no'

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让我知道如果我能澄清任何事情-我是第一次

这里有一个建议的解决方案：为您的逻辑创建一个函数，并将其应用于数据帧

执行：

构建数据帧和常量：

df = pd.DataFrame({"Person A":["Yes","Yes","Yes","Yes","No","No"],
               "Person B":["Yes","Yes","No","No","No","No"]})

yes = 'Person A said yes, then Person B said yes'
no = 'Person A said yes, then person B said no'

结果

    Person A    Person B
    0   Yes         Yes
    1   Yes         Yes
    2   Yes         No
    3   Yes         No
    4   No          No
    5   No          No

创建您的函数

def yourfunc(row):
    if row['Person A']=="Yes" and row['Person B']=="Yes":
        return yes
    if row['Person A']=="No" and row['Person B']=="No":
        return no
    return "TBA"

应用您的功能：

df['Consensus'] = df.apply(yourfunc, axis=1)

最终结果：

    Person A    Person B    Consensus
0   Yes         Yes         Person A said yes, then Person B said yes
1   Yes         Yes         Person A said yes, then Person B said yes
2   Yes         No          TBA
3   Yes         No          TBA
4   No          No          Person A said yes, then person B said no
5   No          No          Person A said yes, then person B said no

---

同路人

def f(x,y):
    if x =='Yes':
            if y =='Yes':
            return 'Person A said yes, then Person B said yes'
        elif y =='No':
            return = 'Person B said yes, then person B said no'

df['Consensus'] = df.apply(lambda row: f(row['Person A'], row['Person B']), axis=1)

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添加一些示例数据，以及您的预期输出