diff --git a/examples/01_skpro_intro.ipynb b/examples/01_skpro_intro.ipynb
index 15122e1fb..85e3ea56e 100644
--- a/examples/01_skpro_intro.ipynb
+++ b/examples/01_skpro_intro.ipynb
@@ -618,6 +618,7 @@
     "# example object 2: ResidualDouble regressor\n",
     "from sklearn.ensemble import RandomForestRegressor\n",
     "from sklearn.linear_model import LinearRegression\n",
+    "\n",
     "from skpro.regression.residual import ResidualDouble\n",
     "\n",
     "reg_mean = LinearRegression()\n",
@@ -1431,7 +1432,7 @@
     "estimator = ResidualDouble(LinearRegression())\n",
     "\n",
     "# tuning grid - do we fit an intercept in the linear regression?\n",
-    "param_grid = {\"estimator__fit_intercept\" : [True, False]}\n",
+    "param_grid = {\"estimator__fit_intercept\": [True, False]}\n",
     "\n",
     "# metric to be optimized\n",
     "crps_metric = CRPS()\n",
@@ -1490,7 +1491,7 @@
     "# only difference to GridSearchCV is the param_distributions argument\n",
     "\n",
     "# specification of the random search parameter sampler\n",
-    "param_distributions = {\"estimator__fit_intercept\" : [True, False]}\n",
+    "param_distributions = {\"estimator__fit_intercept\": [True, False]}\n",
     "\n",
     "# specification of the random search tuner\n",
     "rscv = RandomizedSearchCV(\n",