How to create a ranking variable/function for different periods in a panel data?

I have a dataset, df, that looks like this:

WhereQTDPERCAPITA is simply Quantity/Population. I have multiple cities (4149 to be more precise).

The quantities change according to every month, and so does the population.

I would like to create a new variable that serve as a ranking, ranging from [0,1], where 0 is the city with the lowest QTDPERCAPITA in that month, and 1 is the city with the most quantity per capita in that month. Essentially, I want to create a new column that looks like this:

How can I create this column such that the RANKING changes every month? I was thinking of a for loop that extracts the QTDPERCAPITA for every city on every unique date, and creates a new column, df['RANKING'] with the same date and city.

>Solution :

You can use:

# MinMax scaler: (rank - min) / (max - min)
ranking = lambda x: (x.rank() - 1) / (len(x) - 1)

# Rank between [0, 1] -> 0 the lowest, 1 the highest
df['RANKING'] = df.groupby('Date')['QTDPERCAPITA'].apply(ranking)

# Rank between [1, 4149] -> 1 the lowest, 4149 the highest
# df['RANKING'] = df.groupby('Date')['QTDPERCAPITA'].rank('dense')

Output: