diff --git a/notebooks/regression/regression_MLP.ipynb b/notebooks/regression/regression_MLP.ipynb index e69de29bb2d1d6434b8b29ae775ad8c2e48c5391..84c4460c9f6138cd07e22d9d38173d297ee1278f 100644 --- a/notebooks/regression/regression_MLP.ipynb +++ b/notebooks/regression/regression_MLP.ipynb @@ -0,0 +1,743 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "id": "237b9a57", + "metadata": {}, + "source": [ + "### Loading and Preparing data" + ] + }, + { + "cell_type": "code", + "execution_count": 96, + "id": "68f700e3", + "metadata": {}, + "outputs": [], + "source": [ + "# Load and prepare the data\n", + "import pandas as pd\n", + "from sklearn.model_selection import train_test_split\n", + "\n", + "df = pd.read_csv(\"../../data/processed/preprocessed_incident_event_scaled_svm_mlp.csv\")" + ] + }, + { + "cell_type": "code", + "execution_count": 97, + "id": "225bfec6", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Total rows: 141707\n", + "Total columns: 37\n", + "All columns:\n", + "['reassignment_count', 'reopen_count', 'sys_mod_count', 'impact', 'knowledge', 'u_priority_confirmation', 'opened_month', 'opened_weekend', 'hour_sin', 'hour_cos', 'day_sin', 'day_cos', 'number_freq', 'caller_id_freq', 'assigned_to_freq', 'opened_by_freq', 'resolved_by_freq', 'u_symptom_freq', 'closed_code_freq', 'location_freq', 'category_freq', 'subcategory_freq', 'assignment_group_freq', 'urgency_priority_score', 'incident_state_Awaiting Evidence', 'incident_state_Awaiting Problem', 'incident_state_Awaiting User Info', 'incident_state_Awaiting Vendor', 'incident_state_Closed', 'incident_state_New', 'incident_state_Resolved', 'notify_Send Email', 'contact_type_Email', 'contact_type_IVR', 'contact_type_Phone', 'contact_type_Self service', 'time_to_resolution_log']\n" + ] + } + ], + "source": [ + "# Shape of the dataset\n", + "print(f\"Total rows: {df.shape[0]}\")\n", + "print(f\"Total columns: {df.shape[1]}\")\n", + "\n", + "# All column names\n", + "print(\"All columns:\")\n", + "print(df.columns.tolist())" + ] + }, + { + "cell_type": "markdown", + "id": "bbe68766", + "metadata": {}, + "source": [ + "### Correlation with time_to_resolution_log" + ] + }, + { + "cell_type": "code", + "execution_count": 98, + "id": "2eee877d", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "<Figure size 1152x1008 with 2 Axes>" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "import seaborn as sns\n", + "import matplotlib.pyplot as plt\n", + "\n", + "full_df = pd.concat([X, y], axis=1)\n", + "numeric_df = full_df.select_dtypes(include=['number'])\n", + "\n", + "# Correlation matrix\n", + "corr_matrix = numeric_df.corr()\n", + "\n", + "# Plotting heatmap\n", + "plt.figure(figsize=(16, 14))\n", + "sns.heatmap(\n", + " corr_matrix,\n", + " cmap='coolwarm',\n", + " center=0,\n", + " annot=True,\n", + " fmt=\".2f\",\n", + " annot_kws={\"size\": 8}\n", + ")\n", + "plt.title(\"Correlation Matrix with Values (Features + Target)\")\n", + "plt.tight_layout()\n", + "plt.show()\n", + "\n" + ] + }, + { + "cell_type": "markdown", + "id": "1a0c8892", + "metadata": {}, + "source": [ + "### Feature Engineering\n", + "\n", + "- We computed the Pearson correlation between all numeric features and the target variable time_to_resolution_log.\n", + "- Features with a correlation coefficient below 0.1 are considered weak predictors and should be removed from the dataset. These included frequency encodings (e.g., caller_id_freq, category_freq), time-based encodings (hour_sin, day_cos), and several one-hot encoded incident states and contact types.\n", + "- These features showed little to no linear relationship with the target and could introduce noise or complexity into the model without meaningful contribution. This pruning step simplifies the input space and can improve model interpretability and generalization." + ] + }, + { + "cell_type": "code", + "execution_count": 99, + "id": "b29cc8b3", + "metadata": {}, + "outputs": [], + "source": [ + "features_to_drop = [\n", + " 'knowledge', 'u_priority_confirmation', 'opened_weekend', 'hour_sin', 'hour_cos',\n", + " 'day_sin', 'day_cos', 'location_freq', 'category_freq', 'subcategory_freq',\n", + " 'closed_code_freq', 'u_symptom_freq', 'caller_id_freq', 'incident_state_Awaiting Evidence',\n", + " 'incident_state_Awaiting Problem', 'incident_state_Awaiting User Info',\n", + " 'incident_state_Awaiting Vendor', 'incident_state_New', 'urgency_priority_score',\n", + " 'notify_Send Email', 'contact_type_Email', 'contact_type_Phone',\n", + " 'contact_type_IVR', 'contact_type_Self service', 'opened_by_freq', 'assigned_to_freq', 'reassignment_count'\n", + "]\n", + "\n", + "df = df.drop(columns=features_to_drop)" + ] + }, + { + "cell_type": "markdown", + "id": "355b7564", + "metadata": {}, + "source": [ + "**Dropped Features – Summary**\n", + "\n", + "1. Very Low Correlation (< 0.05): \n", + "Features like knowledge, u_priority_confirmation, opened_weekend, notify_Send Email, and urgency_priority_score were dropped due to negligible or no correlation with the target variable.\n", + "\n", + "2. Time Encodings (hour/day sin/cos): \n", + "Encodings like hour_sin, hour_cos, day_sin, and day_cos showed no predictive value for resolution time and were dropped.\n", + "\n", + "3. Weak Frequency Encodings: \n", + "Features such as caller_id_freq, location_freq, category_freq, and subcategory_freq had low variance in relation to resolution time and were excluded.\n", + "\n", + "4. Uninformative Contact Channels: \n", + "contact_type_Email, contact_type_Phone, contact_type_IVR, and contact_type_Self service had very weak or no correlation and added unnecessary categorical noise.\n", + "\n", + "5. Low-Impact Incident States: \n", + "One-hot encoded incident states like incident_state_New, Awaiting Evidence, Awaiting Vendor, etc., showed no significant correlation and were removed.\n", + "\n", + "6. Redundant Frequency Features: \n", + "assigned_to_freq and opened_by_freq were dropped due to very low correlation, while stronger related features like resolved_by_freq were retained.\n", + "\n", + "7. Multicollinearity with Top Feature: \n", + "reassignment_count was dropped due to high correlation (r = 0.61) with number_freq, which had a stronger relationship with the target." + ] + }, + { + "cell_type": "markdown", + "id": "47283d86", + "metadata": {}, + "source": [ + "#### Updated Correlation matrix" + ] + }, + { + "cell_type": "code", + "execution_count": 100, + "id": "4ed98627", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "<Figure size 1008x864 with 2 Axes>" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "import seaborn as sns\n", + "import matplotlib.pyplot as plt\n", + "\n", + "numeric_df = df.select_dtypes(include=['number'])\n", + "corr_matrix = numeric_df.corr()\n", + "\n", + "# Plotting updated heatmap\n", + "plt.figure(figsize=(14, 12))\n", + "sns.heatmap(\n", + " corr_matrix,\n", + " cmap='coolwarm',\n", + " center=0,\n", + " annot=True,\n", + " fmt=\".2f\",\n", + " annot_kws={\"size\": 8}\n", + ")\n", + "plt.title(\"Updated Correlation Matrix (After Feature Dropping)\")\n", + "plt.tight_layout()\n", + "plt.show()\n" + ] + }, + { + "cell_type": "code", + "execution_count": 101, + "id": "8730baa2", + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "<div>\n", + "<style scoped>\n", + " .dataframe tbody tr th:only-of-type {\n", + " vertical-align: middle;\n", + " }\n", + "\n", + " .dataframe tbody tr th {\n", + " vertical-align: top;\n", + " }\n", + "\n", + " .dataframe thead th {\n", + " text-align: right;\n", + " }\n", + "</style>\n", + "<table border=\"1\" class=\"dataframe\">\n", + " <thead>\n", + " <tr style=\"text-align: right;\">\n", + " <th></th>\n", + " <th>reopen_count</th>\n", + " <th>sys_mod_count</th>\n", + " <th>impact</th>\n", + " <th>opened_month</th>\n", + " <th>number_freq</th>\n", + " <th>resolved_by_freq</th>\n", + " <th>assignment_group_freq</th>\n", + " <th>incident_state_Closed</th>\n", + " <th>incident_state_Resolved</th>\n", + " <th>time_to_resolution_log</th>\n", + " </tr>\n", + " </thead>\n", + " <tbody>\n", + " <tr>\n", + " <th>0</th>\n", + " <td>-0.10573</td>\n", + " <td>-1.016534</td>\n", + " <td>-0.012218</td>\n", + " <td>-1.909515</td>\n", + " <td>-0.886579</td>\n", + " <td>-2.424589</td>\n", + " <td>-1.255453</td>\n", + " <td>-0.462661</td>\n", + " <td>-0.471249</td>\n", + " <td>2.417401</td>\n", + " </tr>\n", + " <tr>\n", + " <th>1</th>\n", + " <td>-0.10573</td>\n", + " <td>-0.533365</td>\n", + " <td>-0.012218</td>\n", + " <td>-1.909515</td>\n", + " <td>-0.886579</td>\n", + " <td>-2.424589</td>\n", + " <td>-1.255453</td>\n", + " <td>-0.462661</td>\n", + " <td>2.122020</td>\n", + " <td>2.417401</td>\n", + " </tr>\n", + " <tr>\n", + " <th>2</th>\n", + " <td>-0.10573</td>\n", + " <td>-0.291780</td>\n", + " <td>-0.012218</td>\n", + " <td>-1.909515</td>\n", + " <td>-0.886579</td>\n", + " <td>-2.424589</td>\n", + " <td>-1.255453</td>\n", + " <td>-0.462661</td>\n", + " <td>2.122020</td>\n", + " <td>2.417401</td>\n", + " </tr>\n", + " <tr>\n", + " <th>3</th>\n", + " <td>-0.10573</td>\n", + " <td>-0.050196</td>\n", + " <td>-0.012218</td>\n", + " <td>-1.909515</td>\n", + " <td>-0.886579</td>\n", + " <td>-2.424589</td>\n", + " <td>-1.255453</td>\n", + " <td>2.161408</td>\n", + " <td>-0.471249</td>\n", + " <td>2.417401</td>\n", + " </tr>\n", + " <tr>\n", + " <th>4</th>\n", + " <td>-0.10573</td>\n", + " <td>-1.016534</td>\n", + " <td>-0.012218</td>\n", + " <td>-1.909515</td>\n", + " <td>0.468326</td>\n", + " <td>-0.438353</td>\n", + " <td>1.207647</td>\n", + " <td>-0.462661</td>\n", + " <td>-0.471249</td>\n", + " <td>3.407842</td>\n", + " </tr>\n", + " </tbody>\n", + "</table>\n", + "</div>" + ], + "text/plain": [ + " reopen_count sys_mod_count impact opened_month number_freq \\\n", + "0 -0.10573 -1.016534 -0.012218 -1.909515 -0.886579 \n", + "1 -0.10573 -0.533365 -0.012218 -1.909515 -0.886579 \n", + "2 -0.10573 -0.291780 -0.012218 -1.909515 -0.886579 \n", + "3 -0.10573 -0.050196 -0.012218 -1.909515 -0.886579 \n", + "4 -0.10573 -1.016534 -0.012218 -1.909515 0.468326 \n", + "\n", + " resolved_by_freq assignment_group_freq incident_state_Closed \\\n", + "0 -2.424589 -1.255453 -0.462661 \n", + "1 -2.424589 -1.255453 -0.462661 \n", + "2 -2.424589 -1.255453 -0.462661 \n", + "3 -2.424589 -1.255453 2.161408 \n", + "4 -0.438353 1.207647 -0.462661 \n", + "\n", + " incident_state_Resolved time_to_resolution_log \n", + "0 -0.471249 2.417401 \n", + "1 2.122020 2.417401 \n", + "2 2.122020 2.417401 \n", + "3 -0.471249 2.417401 \n", + "4 -0.471249 3.407842 " + ] + }, + "execution_count": 101, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# Dropping rows where target is missing\n", + "df = df.dropna(subset=[\"time_to_resolution_log\"])\n", + "df.head()" + ] + }, + { + "cell_type": "code", + "execution_count": 102, + "id": "346344da", + "metadata": {}, + "outputs": [], + "source": [ + "# Separating features and target\n", + "X = df.drop(columns=[\"time_to_resolution_log\"])\n", + "y = df[\"time_to_resolution_log\"]" + ] + }, + { + "cell_type": "code", + "execution_count": 103, + "id": "cd63d661", + "metadata": {}, + "outputs": [], + "source": [ + "# Train-test split (80/20)\n", + "X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, random_state=42)" + ] + }, + { + "cell_type": "code", + "execution_count": 104, + "id": "9ccc0022", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Training samples: 110852\n", + "Testing samples: 27714\n" + ] + } + ], + "source": [ + "print(f\"Training samples: {X_train.shape[0]}\")\n", + "print(f\"Testing samples: {X_test.shape[0]}\")" + ] + }, + { + "cell_type": "markdown", + "id": "fe0deadc", + "metadata": {}, + "source": [ + "### Training MLP Model" + ] + }, + { + "cell_type": "code", + "execution_count": 105, + "id": "dda4274c", + "metadata": {}, + "outputs": [], + "source": [ + "from sklearn.neural_network import MLPRegressor\n", + "from sklearn.metrics import mean_squared_error, mean_absolute_error, r2_score\n", + "\n", + "mlp = MLPRegressor(\n", + " hidden_layer_sizes=(100,),\n", + " activation='relu',\n", + " solver='adam',\n", + " max_iter=1000,\n", + " random_state=42\n", + ")\n" + ] + }, + { + "cell_type": "code", + "execution_count": 106, + "id": "dbb01765", + "metadata": {}, + "outputs": [], + "source": [ + "# Train the model\n", + "mlp.fit(X_train, y_train)\n", + "\n", + "# Predict on test set\n", + "y_pred = mlp.predict(pd.DataFrame(X_test, columns=X_train.columns))" + ] + }, + { + "cell_type": "markdown", + "id": "e9d6ee8f", + "metadata": {}, + "source": [ + "### Evaluation Metrics" + ] + }, + { + "cell_type": "code", + "execution_count": 107, + "id": "1c0448a6", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Mean Squared Error (MSE): 1.5598\n", + "Mean Absolute Error (MAE): 0.9132\n", + "R² Score: 0.7018\n" + ] + } + ], + "source": [ + "# Evaluation metrics\n", + "mse = mean_squared_error(y_test, y_pred)\n", + "mae = mean_absolute_error(y_test, y_pred)\n", + "r2 = r2_score(y_test, y_pred)\n", + "\n", + "print(f\"Mean Squared Error (MSE): {mse:.4f}\")\n", + "print(f\"Mean Absolute Error (MAE): {mae:.4f}\")\n", + "print(f\"R² Score: {r2:.4f}\")" + ] + }, + { + "cell_type": "markdown", + "id": "df08031f", + "metadata": {}, + "source": [ + "##### Metrics plot" + ] + }, + { + "cell_type": "code", + "execution_count": 108, + "id": "0585076b", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "<Figure size 504x360 with 1 Axes>" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "import matplotlib.pyplot as plt\n", + "metrics = {\n", + " 'MSE': mse,\n", + " 'MAE': mae,\n", + " 'R² Score': r2\n", + "}\n", + "\n", + "plt.figure(figsize=(7, 5))\n", + "bars = plt.bar(metrics.keys(), metrics.values(), color=['steelblue', 'darkorange', 'forestgreen'])\n", + "plt.title(\"MLP Regression Evaluation Metrics\")\n", + "plt.ylabel(\"Score / Error\")\n", + "plt.grid(axis='y', linestyle='--', alpha=0.6)\n", + "\n", + "for bar in bars:\n", + " yval = bar.get_height()\n", + " plt.text(bar.get_x() + bar.get_width()/2, yval + 0.02, f\"{yval:.4f}\", ha='center', va='bottom')\n", + "\n", + "plt.tight_layout()\n", + "plt.show()\n" + ] + }, + { + "cell_type": "markdown", + "id": "712ef03e", + "metadata": {}, + "source": [ + "**Observation:**\n", + "\n", + "The bar chart summarizes the evaluation metrics for the trained MLP regression model:\n", + "\n", + "1. Mean Squared Error (MSE): 1.5598 \n", + "Indicates the average squared difference between actual and predicted values. A lower MSE is preferred, and this value reflects a moderate level of error.\n", + "\n", + "2. Mean Absolute Error (MAE): 0.9132 \n", + "Represents the average absolute difference between predicted and actual resolution times (in log scale). This suggests that on average, predictions are off by less than 1 unit, which is reasonable for this context.\n", + "\n", + "3. R² Score: 0.7018 \n", + "This means the model explains approximately 70.2% of the variance in the target variable. It shows that the MLP model is capturing most of the important patterns in the data, though there is still room for improvement." + ] + }, + { + "cell_type": "markdown", + "id": "632b3b82", + "metadata": {}, + "source": [ + "### Visualize Model Predictions" + ] + }, + { + "cell_type": "markdown", + "id": "98ff8e8a", + "metadata": {}, + "source": [ + "#### 1. Binned Line Plot – Mean Prediction per Bin" + ] + }, + { + "cell_type": "code", + "execution_count": 109, + "id": "e649fe13", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "<Figure size 720x432 with 1 Axes>" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "import numpy as np\n", + "import pandas as pd\n", + "import matplotlib.pyplot as plt\n", + "\n", + "results_df = pd.DataFrame({'Actual': y_test, 'Predicted': y_pred})\n", + "results_df['Actual_bin'] = pd.qcut(results_df['Actual'].to_numpy(), q=20, duplicates='drop')\n", + "binned_means = results_df.groupby('Actual_bin')[['Actual', 'Predicted']].mean()\n", + "\n", + "plt.figure(figsize=(10, 6))\n", + "plt.plot(binned_means['Actual'].to_numpy(), label='Mean Actual', marker='o')\n", + "plt.plot(binned_means['Predicted'].to_numpy(), label='Mean Predicted', marker='x')\n", + "plt.xlabel('Binned Actual Resolution Time (quantiles)')\n", + "plt.ylabel('Time to Resolution (log)')\n", + "plt.title('Mean Actual vs Predicted Time to Resolution by Bin')\n", + "plt.legend()\n", + "plt.grid(True)\n", + "plt.tight_layout()\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "id": "131709b2", + "metadata": {}, + "source": [ + "**Observation:**\n", + "The plot shows a generally increasing trend for both actual and predicted means across the quantile bins. The predicted values closely follow the actual values for most of the range, especially in the middle bins. However, in the extreme low and high quantiles, the model slightly underestimates resolution times. This suggests that while the model captures the overall pattern well, it tends to smooth out more extreme cases — a common behavior for MLPs trained on log-transformed targets." + ] + }, + { + "cell_type": "markdown", + "id": "25825315", + "metadata": {}, + "source": [ + "#### 2. Distribution Comparison – Actual vs Predicted" + ] + }, + { + "cell_type": "code", + "execution_count": 110, + "id": "2e30c26a", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "<Figure size 576x360 with 1 Axes>" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "import seaborn as sns\n", + "plt.figure(figsize=(8, 5))\n", + "sns.kdeplot(results_df['Actual'], label='Actual', linewidth=2)\n", + "sns.kdeplot(results_df['Predicted'], label='Predicted', linewidth=2)\n", + "plt.title(\"Distribution Comparison: Actual vs Predicted\")\n", + "plt.xlabel(\"Time to Resolution (log)\")\n", + "plt.legend()\n", + "plt.grid(True)\n", + "plt.tight_layout()\n", + "plt.show()\n" + ] + }, + { + "cell_type": "markdown", + "id": "d460d280", + "metadata": {}, + "source": [ + "**Observation:** \n", + "\n", + "The predicted and actual distributions are broadly aligned, indicating that the model captures the overall trend of resolution times well. However, the predicted curve is slightly shifted left in some regions, suggesting a mild underestimation of longer resolution times. The model performs best in the common resolution range but underrepresents extreme values." + ] + }, + { + "cell_type": "markdown", + "id": "aaebc4d8", + "metadata": {}, + "source": [ + "#### 3. Top Feature Influences (Permutation MAE)" + ] + }, + { + "cell_type": "code", + "execution_count": 111, + "id": "c64999a8", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "<Figure size 576x360 with 1 Axes>" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "from sklearn.inspection import permutation_importance\n", + "\n", + "result = permutation_importance(mlp, X_test, y_test, scoring='neg_mean_absolute_error', n_repeats=10, random_state=42)\n", + "\n", + "# Visualizing top influential features\n", + "importances = pd.Series(result.importances_mean, index=X_test.columns)\n", + "top10 = importances.abs().sort_values(ascending=False).head(10)\n", + "\n", + "plt.figure(figsize=(8, 5))\n", + "top10.plot(kind='barh', color='coral')\n", + "plt.gca().invert_yaxis()\n", + "plt.title(\"Top 10 Feature Influences (Permutation MAE)\")\n", + "plt.xlabel(\"Impact on MAE (Higher = More Important)\")\n", + "plt.tight_layout()\n", + "plt.show()\n" + ] + }, + { + "cell_type": "markdown", + "id": "f1ef10b3", + "metadata": {}, + "source": [ + "**Observation:** \n", + "\n", + "The plot shows that sys_mod_count and number_freq are the most influential features, significantly affecting prediction error when permuted. Features like incident_state_Closed and assignment_group_freq also contribute meaningfully. In contrast, features such as reopen_count, impact, and opened_month have minimal impact on model performance." + ] + }, + { + "cell_type": "markdown", + "id": "5e491a57", + "metadata": {}, + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.9.6" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +}