added `to_dict()` method to the `Regression` result class

this makes it easier to construct data frames out of a list of regression results.

README.md

@@ -11,6 +11,7 @@ counterpart.
 
 ```python
     from linear_regression import linear_regression
+    
     df = pd.DataFrame({"temperature":[...], "signal":[...]})
 
     regression = linear_regression(df, x="temperature", y="signal")

linear_regression.py

@@ -1,11 +1,11 @@
+import dataclasses
 import pandas as pd
 import pytest
 
-from dataclasses import dataclass
 from sklearn import linear_model
 
 
-@dataclass
+@dataclasses.dataclass
 class Regression:
     intercept: float
     coefficient: float
@@ -28,6 +28,9 @@ class Regression:
         msg = "predict() expects 1 argument, got 0"
         raise TypeError(msg)
 
+    def to_dict(self):
+        return dataclasses.asdict(self)
+
 
 def linear_regression(data: pd.DataFrame, *, x: str, y: str) -> Regression:
     """calculates a linear regression for two columns of a DataFrame"""