Fix format issues

Azure · Oct 28, 2024 · 0ee9809 · 0ee9809
1 parent c5ff12b
commit 0ee9809
Showing 1 changed file with 20 additions and 9 deletions.
diff --git a/...jobs/automl-forecasting-forecast-function/auto-ml-forecasting-function-gap-training.ipynb b/...jobs/automl-forecasting-forecast-function/auto-ml-forecasting-function-gap-training.ipynb
@@ -139,6 +139,7 @@
     "n_test_periods = forecast_horizon\n",
     "\n",
     "from helper import get_timeseries\n",
+    "\n",
     "X_train, y_train, X_test, y_test = get_timeseries(\n",
     "    train_len=n_train_periods,\n",
     "    test_len=n_test_periods,\n",
@@ -167,6 +168,7 @@
    "source": [
     "# Plot the example time series\n",
     "import matplotlib.pyplot as plt\n",
+    "\n",
     "whole_data = X_train.copy()\n",
     "target_label = \"y\"\n",
     "whole_data[target_label] = y_train\n",
@@ -204,8 +206,8 @@
    "outputs": [],
    "source": [
     "# For vizualisation of the time series\n",
-    "df_train['data_type'] = 'Training'  # Add a column to label training data\n",
-    "df_test['data_type'] = 'Testing'  # Add a column to label testing data\n",
+    "df_train[\"data_type\"] = \"Training\"  # Add a column to label training data\n",
+    "df_test[\"data_type\"] = \"Testing\"  # Add a column to label testing data\n",
     "\n",
     "# Concatenate the training and testing DataFrames\n",
     "df_plot = pd.concat([df_train, df_test])\n",
@@ -215,13 +217,19 @@
     "ax = plt.gca()  # Get current axis\n",
     "\n",
     "# Group by both 'data_type' and 'time_series_id'\n",
-    "for (data_type, time_series_id), df in df_plot.groupby(['data_type', 'time_series_id']):\n",
-    "    df.plot(x='date', y=TARGET_COLUMN_NAME, label=f\"{data_type} - {time_series_id}\", ax=ax, legend=False)\n",
+    "for (data_type, time_series_id), df in df_plot.groupby([\"data_type\", \"time_series_id\"]):\n",
+    "    df.plot(\n",
+    "        x=\"date\",\n",
+    "        y=TARGET_COLUMN_NAME,\n",
+    "        label=f\"{data_type} - {time_series_id}\",\n",
+    "        ax=ax,\n",
+    "        legend=False,\n",
+    "    )\n",
     "\n",
     "# Customize the plot\n",
-    "plt.xlabel('Date')\n",
-    "plt.ylabel('Value')\n",
-    "plt.title('Train and Test Data')\n",
+    "plt.xlabel(\"Date\")\n",
+    "plt.ylabel(\"Value\")\n",
+    "plt.title(\"Train and Test Data\")\n",
     "\n",
     "# Manually create the legend after plotting\n",
     "plt.legend(title=\"Data Type and Time Series ID\")\n",
@@ -239,6 +247,7 @@
     "import mltable\n",
     "import os\n",
     "\n",
+    "\n",
     "def create_ml_table(data_frame, file_name, output_folder):\n",
     "    os.makedirs(output_folder, exist_ok=True)\n",
     "    data_path = os.path.join(output_folder, file_name)\n",
@@ -270,10 +279,10 @@
     "\n",
     "my_training_data_input.__dict__\n",
     "\n",
-    "#Test data\n",
+    "# Test data\n",
     "os.makedirs(\"data\", exist_ok=True)\n",
     "create_ml_table(\n",
-    "    X_test, #df_test,\n",
+    "    X_test,  # df_test,\n",
     "    \"X_test.parquet\",\n",
     "    \"./data/testing-mltable-folder\",\n",
     ")\n",
@@ -429,6 +438,7 @@
    "outputs": [],
    "source": [
     "import mlflow\n",
+    "\n",
     "MLFLOW_TRACKING_URI = ml_client.workspaces.get(\n",
     "    name=ml_client.workspace_name\n",
     ").mlflow_tracking_uri\n",
@@ -540,6 +550,7 @@
    "source": [
     "# Create local folder\n",
     "import os\n",
+    "\n",
     "local_dir = \"./artifact_downloads\"\n",
     "if not os.path.exists(local_dir):\n",
     "    os.mkdir(local_dir)"