根据另一列填充 NaN 值

Question

我有这个 pd.DataFrame：

test4 = pd.DataFrame({'condition': ['good', np.nan, np.nan, 'excellent', 'good', np.nan], 
                      'odometer': [np.nan, 35000, 20000, 100000, 500000, 50]})

输出：

condition   odometer
0   good    NaN
1   NaN 35000.0
2   NaN 20000.0
3   excellent   100000.0
4   good    500000.0
5   NaN 50.0

而且我无法使用“里程表”列中的值填充“条件”列中的 NaN 值。条件是：

odometer <=30000, then condition = 'good'
odometer > 30000 & odometer <=150000, then value = 'excellent'
odometer > 150000 & odometer <=10000000, then value = 'good'

最后应该是这样的：

condition   odometer
0   good    NaN
1   excellent   35000.0
2   good    20000.0
3   excellent   100000.0
4   good    500000.0
5   good    50.0

我尝试了不同的东西，但都没有奏效。例如：

def f(change):
    if change['condition'] == np.nan:
        condition = change['odometer']
        value = change['condition']
        if   condition <=30000 value = 'good'
        elif condition > 30000 & condition <=150000 value = 'excellent'
        elif condition > 150000 & condition <=10000000 value = 'good'
        return value
    return change['condition']

test4['condition'] = test4.apply(f)

我做错了什么？有没有办法让它工作？谢谢。

Answer 1

我找到了答案：

m1 = (test4['odometer'] > 30000) & (test4['odometer'] <= 150000)
m2 = (test4['odometer'] <= 30000) | (test4['odometer'] > 150000)

test4.loc[m1,'condition'] = test4.loc[m1,'condition'].fillna('excellent')
test4.loc[m2,'condition'] = test4.loc[m2,'condition'].fillna("good")