问题描述
鉴于以下数据，如何获得上一年的中位数平方米价格？
city_code createdYear squaremeterPrice squaremeterPrice_grouped_city_for_the_current_year
0 26 2014 33273 39632.0
1 26 2014 37500 39632.0
2 26 2014 47428 39632.0
3 26 2014 39554 39632.0
4 26 2014 38893 39632.0
5 26 2013 34231 28841.0
6 26 2014 34344 39632.0
7 26 2014 44574 39632.0
8 26 2014 25202 39632.0
9 26 2014 39632 39632.0
10 26 2014 44504 39632.0
11 26 2013 23451 28841.0
...
为了获得平方，我使用了以下代码：Price_grouped_city_for_the_current_year
# adding the yearly average sqm price
median_squaremeterPrice_per_city = df.groupby(["city_code"])["squaremeterPrice"].median().to_frame("squaremeterPrice_grouped_city_for_the_current_year").reset_index()
df = df.merge(median_squaremeterPrice_per_city,left_on=["city_code"],right_on=["city_code"])
df
我们的预期输出如下：
city_code createdYear squaremeterPrice squaremeterPrice_grouped_city_for_the_current_year squaremeterPrice_grouped_city_for_1_year_prior
0 26 2014 33273 39632.0 28841.0
1 26 2014 37500 39632.0 28841.0
2 26 2014 47428 39632.0 28841.0
3 26 2014 39554 39632.0 28841.0
4 26 2014 38893 39632.0 28841.0
5 26 2013 34231 28841.0 whatever was the 2012 price
6 26 2014 34344 39632.0 28841.0
7 26 2014 44574 39632.0 28841.0
8 26 2014 25202 39632.0 28841.0
9 26 2014 39632 39632.0 28841.0
10 26 2014 44504 39632.0 28841.0
11 26 2013 23451 28841.0 whatever was the 2012 price
...
解决方法
相反，您的解决方案按city_code和createdYear列与median进行分组，并为上一年在1的年份中添加MultiIndex，最后使用{{ 3}}中的新列：
median_squaremeterPrice_per_city_and_year = (df.groupby(["city_code","createdYear"])["squaremeterPrice"]
.median()
.rename('squaremeterPrice_grouped_city_for_the_current_year'))
median_squaremeterPrice_per_city_and__prev_year =( median_squaremeterPrice_per_city_and_year
.rename(lambda x: x+1,level=1)
.rename('squaremeterPrice_grouped_city_for_the_prev_year'))
print (median_squaremeterPrice_per_city_and__prev_year)
df1 = (df.join(median_squaremeterPrice_per_city_and_year,on=['city_code','createdYear'])
.join(median_squaremeterPrice_per_city_and__prev_year,'createdYear']))
print (df1)
city_code createdYear squaremeterPrice \
0 26 2014 33273
1 26 2014 37500
2 26 2014 47428
3 26 2014 39554
4 26 2014 38893
5 26 2013 34231
6 26 2014 34344
7 26 2014 44574
8 26 2014 25202
9 26 2014 39632
10 26 2014 44504
11 26 2013 23451
squaremeterPrice_grouped_city_for_the_current_year \
0 39223.5
1 39223.5
2 39223.5
3 39223.5
4 39223.5
5 28841.0
6 39223.5
7 39223.5
8 39223.5
9 39223.5
10 39223.5
11 28841.0
squaremeterPrice_grouped_city_for_the_prev_year
0 28841.0
1 28841.0
2 28841.0
3 28841.0
4 28841.0
5 NaN
6 28841.0
7 28841.0
8 28841.0
9 28841.0
10 28841.0
11 NaN