python - Pandas 数据框列表理解中的 If ElseIf Else 条件

Question

我有一个包含 11 列的数据框:Status1-Status5、Time1-Time5 和 Time_Min

df = pd.DataFrame([[100,200,150,400,500,'a','b','a','c','a',100], [300,400,200,500,250,'b','b','c','c','c',200]], columns=['TIME_1', 'TIME_2', 'TIME_3', 'TIME_4', 'TIME_5','STATUS_1','STATUS_2','STATUS_3','STATUS_4','STATUS_5','TIME_MIN'])

我想重现我目前在 SAS 中执行以下操作的代码

IF TIME_1 = TIME_MIN THEN STATUS = STATUS_1;
ELSE IF TIME_2 = TIME_MIN THEN STATUS = STATUS_2;
ELSE IF TIME_3 = TIME_MIN THEN STATUS = STATUS_3;
ELSE IF TIME_4 = TIME_MIN THEN STATUS = STATUS_4;
ELSE STATUS = STATUS_5;

列 STATUS 的预期输出为

['a','c']

我尝试按照这些思路构建一些东西(需要用 else ifs 进行扩展)

df['STATUS'] = [a if x == y else b for x,y,a,b in df[['TIME_MIN','TIME_1','STATUS_1','STATUS_2']]]

但这只是给出了一个错误。我确定这是一个简单的修复，但我不太明白。

Answer 1

你可以写一个函数

def get_status(df):
    if df['TIME_1'] == df['TIME_MIN']:
        return df['STATUS_1']
    elif df['TIME_2'] == df['TIME_MIN']:
        return df['STATUS_2']
    elif df['TIME_3'] == df['TIME_MIN']:
        return df['STATUS_3']
    elif df['TIME_4'] == df['TIME_MIN']:
        return df['STATUS_4']
    else:
        return df['STATUS_5']

df['STATUS'] = df.apply(get_status, axis = 1)

或者使用非常嵌套的 np.where，

df['STATUS'] = np.where(df['TIME_1'] == df['TIME_MIN'], df['STATUS_1'],\ 
        np.where(df['TIME_2'] == df['TIME_MIN'], df['STATUS_2'],\
        np.where(df['TIME_3'] == df['TIME_MIN'], df['STATUS_3'],\
        np.where(df['TIME_4'] == df['TIME_MIN'], df['STATUS_4'], df['STATUS_5']))))