如何用全局变量作为apply函数的附加参数处理指定的列？

df = pd.read_csv('https://raw.githubusercontent.com/selva86/datasets/master/Cars93_miss.csv')
print(df[['Min.Price', 'Max.Price']].head())
# 全局变量
d = {'Min.Price': np.nanmean, 'Max.Price': np.nanmedian}
# 列名Min.Price的缺失值用平均值代替，Max.Price的缺失值用中值代替
df[['Min.Price', 'Max.Price']] = df[['Min.Price', 'Max.Price']].apply(lambda x, d: x.fillna(d[x.name](x)), args=(d, ))
print(df[['Min.Price', 'Max.Price']].head())

#>	   Min.Price  Max.Price
	0       12.9       18.8
	1       29.2       38.7
	2       25.9       32.3
	3        NaN       44.6
	4        NaN        NaN

#>	   Min.Price  Max.Price
	0  12.900000      18.80
	1  29.200000      38.70
	2  25.900000      32.30
	3  17.118605      44.60
	4  17.118605      19.15