Error during calculating parametres (unsupported operand type)

I'm trying to calculate linear regression for my small data science project.

I have class

import numpy as np # I'm using the idea from https://devarea.com/linear-regression-with-numpy/#.XRfdcegzaUk class LinearRegression: def __init__(self, values): self.y = np.array(values) self.x = np.array([number for number in range(1, len(values)+1)]) self.values_to_return = [] def getlinear(self, x1): # Function that returns value def inner(x1): return self.m * x1 + self.b self.m = (len(self.x) * np.sum(self.x*self.y) - np.sum(self.x) * np.sum(self.y)) / (len(self.x)*np.sum(self.x*self.x) - np.sum(self.x) * np.sum(self.x)) self.b = (np.sum(self.y) - self.m*np.sum(self.x)) / len(self.x) return inner 

And I got error

File "c:/Users/Paweł/Documents/projects vscode/WorldBankDataKeras/tests.py", line 35, in country1 = data.CountryInformations('Poland') File "c:\Users\Paweł\Documents\projects vscode\WorldBankDataKeras\data.py", line 26, in init linear.return_values_of_linear_regression()) File "c:\Users\Paweł\Documents\projects vscode\WorldBankDataKeras\linear_regr.py", line 22, in return_values_of_linear_regression self.values_to_return.append(self.getlinear(x_param)) File "c:\Users\Paweł\Documents\projects vscode\WorldBankDataKeras\linear_regr.py", line 15, in getlinear self.m = (np.array(len(self.x)) * np.sum(self.x*self.y) - np.sum(self.x) * np.sum(self.y)) / (np.array(len(self.x))np.sum(self.xself.x) - np.sum(self.x) * np.sum(self.x)) TypeError: unsupported operand type(s) for *: 'int' and 'dict_values'

What do I do wrong?

EDIT:

When passing list(dictionary.values()) into the class I got

Traceback (most recent call last): File "c:/Users/Paweł/Documents/projects vscode/WorldBankDataKeras/tests.py", line 41, in graph.plot_graph_renewable_electricity_status() File "c:\Users\Paweł\Documents\projects vscode\WorldBankDataKeras\graph_plotting.py", line 115, in plot_graph_renewable_electricity_status linestyle='-') File "C:\Users\Paweł\AppData\Local\Programs\Python\Python37\lib\site-packages\matplotlib__init__.py", line 1810, in inner return func(ax, *args, **kwargs) File "C:\Users\Paweł\AppData\Local\Programs\Python\Python37\lib\site-packages\matplotlib\axes_axes.py", line 1612, in plot self.add_line(line) File "C:\Users\Paweł\AppData\Local\Programs\Python\Python37\lib\site-packages\matplotlib\axes_base.py", line 1895, in add_line self._update_line_limits(line) File "C:\Users\Paweł\AppData\Local\Programs\Python\Python37\lib\site-packages\matplotlib\axes_base.py", line 1917, in _update_line_limits path = line.get_path() File "C:\Users\Paweł\AppData\Local\Programs\Python\Python37\lib\site-packages\matplotlib\lines.py", line 945, in get_path self.recache() File "C:\Users\Paweł\AppData\Local\Programs\Python\Python37\lib\site-packages\matplotlib\lines.py", line 645, in recache y = _to_unmasked_float_array(yconv).ravel() File "C:\Users\Paweł\AppData\Local\Programs\Python\Python37\lib\site-packages\matplotlib\cbook__init__.py", line 1365, in _to_unmasked_float_array return np.asarray(x, float) File "C:\Users\Paweł\AppData\Local\Programs\Python\Python37\lib\site-packages\numpy\core\numeric.py", line 538, in asarray return array(a, dtype, copy=False, order=order) TypeError: float() argument must be a string or a number, not 'function'

EDIT 2:

class CountryInformations: def __init__(self, name): self.name = name xls_parsing = xls_parse.XLSParsing(self.name) self.population = xls_parsing.import_country_population() self.co2_emissions = xls_parsing.import_country_co2_emissions() self.renewable_electricity_status = xls_parsing.import_country_renewable_electricity_status() # I want to have linear regression values in format [year] : value self.population_linear_regression = self.population.copy() self.co2_emissions_linear_regression = self.co2_emissions.copy() self.renewable_electricity_status_linear_regression = self.renewable_electricity_status.copy() linear = linear_regr.LinearRegression(list(self.population_linear_regression.values())) # Replacing values in dict by values from linear regression self.population_linear_regression = dict.fromkeys(self.population_linear_regression, linear.return_values_of_linear_regression()) linear = linear_regr.LinearRegression(list(self.co2_emissions_linear_regression.values())) # Replacing values in dict by values from linear regression self.co2_emissions_linear_regression = dict.fromkeys(self.co2_emissions_linear_regression, linear.return_values_of_linear_regression()) linear = linear_regr.LinearRegression(list(self.renewable_electricity_status_linear_regression.values())) # Replacing values in dict by values from linear regression self.renewable_electricity_status_linear_regression = dict.fromkeys(self.renewable_electricity_status_linear_regression, linear.return_values_of_linear_regression()) def __str__(self): print_string = 'Country: {} \n \ Population: {}M \n \ CO2 Emissions: {}KT \n \ Renewable Electricity Status: {}%'.format(self.name, \ self.population, \ self.co2_emissions, \ self.renewable_electricity_status) return print_string