Range of int as keys for dict

I have a column which rejected amounts (these are just 5 exmaples)

I want to add a column, given points based on the price.

For example, if price is betwen 0 and 100 -> 0.

what i did was :

dict_reject_amount = {0:0,\
                      range(1,101):1,\
                      range(101,201):2,\
                      range(201,301):3,\
                      range(301,401):4,\
                      range(401,501):5,\
                      range(501,601):6,\
                      range(601,701):7,\
                      range(701,801):8,\
                      range(801,901):9,\
                      range(901,100000):9}

convert to int, floats do not matter

new['rejected_int'] = new['rejected'].astype(int)

new['reject_amount_points']= new['rejected_int'].map(dict_reject_amount)

Unfortunately it didn’t work.

>Solution :

You can use replace to apply the dict values

new['reject_amount_points'] = df['rejected_int'].replace(dict_reject_amount)