diff --git a/docs/source/examples/predict_bike_trips.ipynb b/docs/source/examples/predict_bike_trips.ipynb
index fe8b4331..82cd97d6 100644
--- a/docs/source/examples/predict_bike_trips.ipynb
+++ b/docs/source/examples/predict_bike_trips.ipynb
@@ -419,10 +419,11 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "values = best_pipeline.predict(fm).values.round()\n",
+    "y_pred = best_pipeline.predict(fm)\n",
+    "y_pred = y_pred.to_series().values.round()\n",
     "\n",
     "prediction = fm[[]]\n",
-    "prediction['trip_count (estimate)'] = values\n",
+    "prediction['trip_count (estimate)'] = y_pred\n",
     "prediction.head()"
    ]
   },
@@ -452,7 +453,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.7.6"
+   "version": "3.7.5"
   }
  },
  "nbformat": 4,
diff --git a/docs/source/examples/predict_next_purchase.ipynb b/docs/source/examples/predict_next_purchase.ipynb
index 730483fe..fc5f0ba6 100644
--- a/docs/source/examples/predict_next_purchase.ipynb
+++ b/docs/source/examples/predict_next_purchase.ipynb
@@ -442,10 +442,11 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "values = best_pipeline.predict(fm).values\n",
+    "y_pred = best_pipeline.predict(fm)\n",
+    "y_pred = y_pred.to_series().values\n",
     "\n",
     "prediction = fm[[]]\n",
-    "prediction['bought_product (estimate)'] = values\n",
+    "prediction['bought_product (estimate)'] = y_pred\n",
     "prediction.head()"
    ]
   },
@@ -480,7 +481,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.7.6"
+   "version": "3.7.5"
   }
  },
  "nbformat": 4,
diff --git a/docs/source/examples/predict_turbofan_degredation.ipynb b/docs/source/examples/predict_turbofan_degredation.ipynb
index 224768da..3b026bdb 100644
--- a/docs/source/examples/predict_turbofan_degredation.ipynb
+++ b/docs/source/examples/predict_turbofan_degredation.ipynb
@@ -488,10 +488,11 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "values = best_pipeline.predict(fm).values\n",
+    "y_pred = best_pipeline.predict(fm)\n",
+    "y_pred = y_pred.to_series().values\n",
     "\n",
     "prediction = fm[[]]\n",
-    "prediction['rul (estimate)'] = values\n",
+    "prediction['rul (estimate)'] = y_pred\n",
     "prediction.head()"
    ]
   },
@@ -527,7 +528,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.7.6"
+   "version": "3.7.5"
   }
  },
  "nbformat": 4,