Update Mission155Solutions.ipynb

Mission155Solutions.ipynb

@@ -4,7 +4,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "## Introduction To The Data Set"
+    "## Introduction To The Dataset"
    ]
   },
   {
@@ -762,7 +762,7 @@
     }
    ],
    "source": [
-    "# Confirm that there's no more missing values!\n",
+    "# Confirm that there are no more missing values!\n",
     "numeric_cars.isnull().sum()"
    ]
   },
@@ -827,15 +827,15 @@
     "    knn = KNeighborsRegressor()\n",
     "    np.random.seed(1)\n",
     "        \n",
-    "    # Randomize order of rows in data frame.\n",
+    "    # Randomize order of rows in DataFrame.\n",
     "    shuffled_index = np.random.permutation(df.index)\n",
     "    rand_df = df.reindex(shuffled_index)\n",
     "\n",
     "    # Divide number of rows in half and round.\n",
     "    last_train_row = int(len(rand_df) / 2)\n",
     "    \n",
-    "    # Select the first half and set as training set.\n",
-    "    # Select the second half and set as test set.\n",
+    "    # Select the first half, and set as training set.\n",
+    "    # Select the second half, and set as test set.\n",
     "    train_df = rand_df.iloc[0:last_train_row]\n",
     "    test_df = rand_df.iloc[last_train_row:]\n",
     "    \n",
@@ -956,15 +956,15 @@
     "def knn_train_test(train_col, target_col, df):\n",
     "    np.random.seed(1)\n",
     "        \n",
-    "    # Randomize order of rows in data frame.\n",
+    "    # Randomize order of rows in DataFrame.\n",
     "    shuffled_index = np.random.permutation(df.index)\n",
     "    rand_df = df.reindex(shuffled_index)\n",
     "\n",
     "    # Divide number of rows in half and round.\n",
     "    last_train_row = int(len(rand_df) / 2)\n",
     "    \n",
-    "    # Select the first half and set as training set.\n",
-    "    # Select the second half and set as test set.\n",
+    "    # Select the first half, and set as training set.\n",
+    "    # Select the second half, and set as test set.\n",
     "    train_df = rand_df.iloc[0:last_train_row]\n",
     "    test_df = rand_df.iloc[last_train_row:]\n",
     "    \n",
@@ -1100,15 +1100,15 @@
     "def knn_train_test(train_cols, target_col, df):\n",
     "    np.random.seed(1)\n",
     "    \n",
-    "    # Randomize order of rows in data frame.\n",
+    "    # Randomize order of rows in DataFrame.\n",
     "    shuffled_index = np.random.permutation(df.index)\n",
     "    rand_df = df.reindex(shuffled_index)\n",
     "\n",
     "    # Divide number of rows in half and round.\n",
     "    last_train_row = int(len(rand_df) / 2)\n",
     "    \n",
-    "    # Select the first half and set as training set.\n",
-    "    # Select the second half and set as test set.\n",
+    "    # Select the first half, and set as training set.\n",
+    "    # Select the second half, and set as test set.\n",
     "    train_df = rand_df.iloc[0:last_train_row]\n",
     "    test_df = rand_df.iloc[last_train_row:]\n",
     "    \n",
@@ -1266,15 +1266,15 @@
     "def knn_train_test(train_cols, target_col, df):\n",
     "    np.random.seed(1)\n",
     "    \n",
-    "    # Randomize order of rows in data frame.\n",
+    "    # Randomize order of rows in DataFrame.\n",
     "    shuffled_index = np.random.permutation(df.index)\n",
     "    rand_df = df.reindex(shuffled_index)\n",
     "\n",
     "    # Divide number of rows in half and round.\n",
     "    last_train_row = int(len(rand_df) / 2)\n",
     "    \n",
-    "    # Select the first half and set as training set.\n",
-    "    # Select the second half and set as test set.\n",
+    "    # Select the first half, and set as training set.\n",
+    "    # Select the second half, and set as test set.\n",
     "    train_df = rand_df.iloc[0:last_train_row]\n",
     "    test_df = rand_df.iloc[last_train_row:]\n",
     "    \n",
@@ -1364,7 +1364,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.7.6"
+   "version": "3.8.5"
   }
  },
  "nbformat": 4,