lint

ploomber · Feb 28, 2024 · 96456ee · 96456ee
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commit 96456ee
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diff --git a/src/sklearn_evaluation/plot/precision_recall.py b/src/sklearn_evaluation/plot/precision_recall.py
@@ -317,7 +317,7 @@ def plot(self, ax=None):
                 # User passes list of list for binary
                 r = r[0] if isinstance(r[0], (list, np.ndarray)) else r
                 p = p[0] if isinstance(p[0], (list, np.ndarray)) else p
-                label = f"{l}, AUC={auc(r,p):.2f}"
+                label = f"{l}, AUC={auc(r, p):.2f}"
                 ax = _plot_metrics_binary(p, r, label, ax)
 
         _set_ax_settings(ax, "Precision Recall compare")

diff --git a/src/sklearn_evaluation/plot/regression.py b/src/sklearn_evaluation/plot/regression.py
@@ -149,7 +149,7 @@ def prediction_error(y_true, y_pred, ax=None):
 
     # R2
     r2 = model.score(y_reshaped, y_pred)
-    plt.plot([], [], " ", label=f"R2 = {round(r2,5)}")
+    plt.plot([], [], " ", label=f"R2 = {round(r2, 5)}")
 
     _set_ax_settings(ax, "y_true", "y_pred", "Prediction Error")
     ax.legend(loc="upper left")