where with append within my loop, but I get the error ; TypeError: can't multiply sequence by non-int of type 'numpy.float64'

example data & preprocessing:

data1 = pd.DataFrame({"cust_id": ['x111'], #customer data
                      "state": ['B'],
                      "amount": [1000],
                      "year":[3],
                      "group":[10],
                      "loan_rate":[0.12]})

data1['state'] = pd.Categorical(data1['state'], 
                                        categories=state_list, 
                                        ordered=True).codes

state_list = ['A','B','C','D','E'] #possible states


lookup1 = pd.DataFrame({'year': [1, 2, 3, 4, 5],
                       'lim %': [0.1, 0.1, 0.1, 0.1, 0.1]}).set_index(['year'])

matrix_data = np.arange(125).reshape(5,5,5) #3d matrix by state(A-E) and year(1-5)

working loop calculation:

results={}
for cust_id, state, amount, start, group, loan_rate in data1.itertuples(name=None, index=False):
    res = [amount * matrix_data[start-1, state, :]]
    for year in range(start 1, len(matrix_data) 1,):
        res.append(lookup1.loc[year].iat[0] * np.array(res[-1])) #trying to edit this line
        res.append(res[-1] * loan_rate)
        res.append(res[-1]  60)
        res.append([res[-1] @ matrix_data[year-1]])
        results[cust_id] = res

Changes I am trying to make:

I am trying to edit this line ;

res.append(lookup1.loc[year].iat[0] * np.array(res[-1]))

to this:

res.append(np.where(np.isin(res,res[-1][0:3])),(lookup1.loc[year].iat[0] * res),res)

as I only want to multiply res[-1][0:3] by the lookup1 value, and the rest of the values in the array remain the same.

example output:

{'x111': [array([55000, 56000, 57000, 58000, 59000]),
  array([ 5500.,  5600.,  5700., 58000., 59000.]),...

CodePudding user response：

You're looking at the problem wrong.

Just make lookup1.loc[year].iat[0] an np.array too.

results={}
for cust_id, state, amount, start, group, loan_rate in data1.itertuples(name=None, index=False):
    res = [amount * matrix_data[start-1, state, :]]
    for year in range(start 1, len(matrix_data) 1,):
        temp = np.array([lookup1.loc[year].iat[0]]*len(matrix_data))
        temp[3] = temp[4] = 1
        res.append(temp * np.array(res[-1])) #trying to edit this line
        res.append(res[-1] * loan_rate)
        res.append(res[-1]  60)
        res.append([res[-1] @ matrix_data[year-1]])
        results[cust_id] = res