Ordering values across different groups in Pandas - python-3.x

Question

I am trying to order values of different cars across different regions, as an example. Following is the sample data set.
import pandas as pd
region = ['east','west', 'central', 'east', 'west', 'central', 'east', 'west', 'central']
automobile = ['bmw', 'bmw', 'bmw', 'tesla', 'tesla', 'tesla', 'lucid', 'lucid', 'lucid']
price = [250, 350, 300, 500, 550, 575, 950, 900, 850]
df_test = pd.DataFrame({'region':region,
'automobile':automobile,
'price':price} )
display(df_test)
I would like to make sure that for each automobile, the price across three reqions is synchronized such
that East <= Central <= West (as they are for BMW). If they are not sync'd', price on the East should be
the base price. Eg. for Lucid, its price in Central should be 950 and then in West should be 950 as well. For Testla,
the price in West needs to be raised to match Central i.e. 575.
I think I should use GROUPBY but just cant make any progress. I imagine that a function like ffill() could be used after pivoting the data, but I hope there is a simpler solution.
Any help would appreciated.
Thank you

Answer 1

You can use cummax with groupby, but you need to sort your data in the correct order with categorical dtype:
# assign the order for the regions
df_test['region'] = pd.Categorical(df_test['region'], ordered=True, categories=['east','central', 'west'])
df['price'] = (df_test.sort_values(['automobile','region']) # sort data in the correct order
.groupby('automobile')['price'].cummax() # use cummax to correct the values
)
Output:
region automobile price
0 east bmw 250
1 west bmw 350
2 central bmw 300
3 east tesla 500
4 west tesla 575
5 central tesla 575
6 east lucid 950
7 west lucid 950
8 central lucid 950