music_and_mental_health.ipynb

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      "source": [
        "# Import libraries\n",
        "import pandas as pd\n",
        "import numpy as np\n",
        "from sklearn.model_selection import train_test_split, cross_val_score, GridSearchCV\n",
        "from sklearn.ensemble import RandomForestClassifier\n",
        "from sklearn.metrics import accuracy_score, confusion_matrix, classification_report, mean_squared_error # Import mean_squared_error\n",
        "from sklearn.pipeline import Pipeline\n",
        "from sklearn.preprocessing import OneHotEncoder\n",
        "import matplotlib.pyplot as plt\n",
        "from imblearn.over_sampling import SMOTE\n",
        "import seaborn as sns"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "\n",
        "# Load the dataset\n",
        "df = pd.read_csv(\"/content/drive/MyDrive/music and mental health.csv\")\n",
        "\n",
        "# Drop the timestamp and permissions columns\n",
        "df = df.drop([\"Timestamp\", \"Permissions\"], axis=1)\n",
        "\n",
        "# Define the target variable as a binary variable indicating whether the respondent has any mental health condition\n",
        "df[\"Mental health\"] = df[[\"Anxiety\", \"Depression\", \"Insomnia\", \"OCD\"]].any(axis=1).astype(int)"
      ],
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      "source": [
        "df.head()"
      ],
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              "    Age Primary streaming service  Hours per day While working  \\\n",
              "0  18.0                   Spotify            3.0           Yes   \n",
              "1  63.0                   Pandora            1.5           Yes   \n",
              "2  18.0                   Spotify            4.0            No   \n",
              "3  61.0             YouTube Music            2.5           Yes   \n",
              "4  18.0                   Spotify            4.0           Yes   \n",
              "\n",
              "  Instrumentalist Composer         Fav genre Exploratory Foreign languages  \\\n",
              "0             Yes      Yes             Latin         Yes               Yes   \n",
              "1              No       No              Rock         Yes                No   \n",
              "2              No       No  Video game music          No               Yes   \n",
              "3              No      Yes              Jazz         Yes               Yes   \n",
              "4              No       No               R&B         Yes                No   \n",
              "\n",
              "     BPM  ...  Frequency [R&B]  Frequency [Rap] Frequency [Rock]  \\\n",
              "0  156.0  ...        Sometimes  Very frequently            Never   \n",
              "1  119.0  ...        Sometimes           Rarely  Very frequently   \n",
              "2  132.0  ...            Never           Rarely           Rarely   \n",
              "3   84.0  ...        Sometimes            Never            Never   \n",
              "4  107.0  ...  Very frequently  Very frequently            Never   \n",
              "\n",
              "  Frequency [Video game music] Anxiety Depression Insomnia  OCD Music effects  \\\n",
              "0                    Sometimes     3.0        0.0      1.0  0.0           NaN   \n",
              "1                       Rarely     7.0        2.0      2.0  1.0           NaN   \n",
              "2              Very frequently     7.0        7.0     10.0  2.0     No effect   \n",
              "3                        Never     9.0        7.0      3.0  3.0       Improve   \n",
              "4                       Rarely     7.0        2.0      5.0  9.0       Improve   \n",
              "\n",
              "  Mental health  \n",
              "0             1  \n",
              "1             1  \n",
              "2             1  \n",
              "3             1  \n",
              "4             1  \n",
              "\n",
              "[5 rows x 32 columns]"
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              "      <th>Age</th>\n",
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              "      <th>Depression</th>\n",
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              "      <th>Music effects</th>\n",
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              "      <th>0</th>\n",
              "      <td>18.0</td>\n",
              "      <td>Spotify</td>\n",
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              "      <th>1</th>\n",
              "      <td>63.0</td>\n",
              "      <td>Pandora</td>\n",
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              "      <td>Yes</td>\n",
              "      <td>No</td>\n",
              "      <td>No</td>\n",
              "      <td>Rock</td>\n",
              "      <td>Yes</td>\n",
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              "      <td>119.0</td>\n",
              "      <td>...</td>\n",
              "      <td>Sometimes</td>\n",
              "      <td>Rarely</td>\n",
              "      <td>Very frequently</td>\n",
              "      <td>Rarely</td>\n",
              "      <td>7.0</td>\n",
              "      <td>2.0</td>\n",
              "      <td>2.0</td>\n",
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              "      <th>2</th>\n",
              "      <td>18.0</td>\n",
              "      <td>Spotify</td>\n",
              "      <td>4.0</td>\n",
              "      <td>No</td>\n",
              "      <td>No</td>\n",
              "      <td>No</td>\n",
              "      <td>Video game music</td>\n",
              "      <td>No</td>\n",
              "      <td>Yes</td>\n",
              "      <td>132.0</td>\n",
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              "      <td>Never</td>\n",
              "      <td>Rarely</td>\n",
              "      <td>Rarely</td>\n",
              "      <td>Very frequently</td>\n",
              "      <td>7.0</td>\n",
              "      <td>7.0</td>\n",
              "      <td>10.0</td>\n",
              "      <td>2.0</td>\n",
              "      <td>No effect</td>\n",
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              "      <th>3</th>\n",
              "      <td>61.0</td>\n",
              "      <td>YouTube Music</td>\n",
              "      <td>2.5</td>\n",
              "      <td>Yes</td>\n",
              "      <td>No</td>\n",
              "      <td>Yes</td>\n",
              "      <td>Jazz</td>\n",
              "      <td>Yes</td>\n",
              "      <td>Yes</td>\n",
              "      <td>84.0</td>\n",
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              "      <td>Sometimes</td>\n",
              "      <td>Never</td>\n",
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              "      <td>107.0</td>\n",
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              "      <td>Never</td>\n",
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        "\n",
        "\n",
        "## ***VISUALIZATION***"
      ],
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        "id": "9FPxDb80Ydo7"
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      "cell_type": "code",
      "source": [
        "# Plot a bar chart of the ratings of anxiety by music genre\n",
        "plt.figure(figsize=(10,6))\n",
        "plt.bar(df.groupby(\"Fav genre\")[\"Anxiety\"].mean().index,\n",
        "        df.groupby(\"Fav genre\")[\"Anxiety\"].mean().values)\n",
        "plt.xlabel(\"Music genre\")\n",
        "plt.ylabel(\"Anxiety rating (1=None, 2=Mild, 3=Moderate, 4=Severe)\")\n",
        "plt.title(\"Relation between music genre and anxiety\")\n",
        "plt.show()\n",
        "\n",
        "# Plot a bar chart of the ratings of depression by music genre\n",
        "plt.figure(figsize=(10,6))\n",
        "plt.bar(df.groupby(\"Fav genre\")[\"Depression\"].mean().index,\n",
        "        df.groupby(\"Fav genre\")[\"Depression\"].mean().values)\n",
        "plt.xlabel(\"Music genre\")\n",
        "plt.ylabel(\"Depression rating (1=None, 2=Mild, 3=Moderate, 4=Severe)\")\n",
        "plt.title(\"Relation between music genre and depression\")\n",
        "plt.show()\n",
        "\n",
        "# Plot a bar chart of the ratings of insomnia by music genre\n",
        "plt.figure(figsize=(10,6))\n",
        "plt.bar(df.groupby(\"Fav genre\")[\"Insomnia\"].mean().index,\n",
        "        df.groupby(\"Fav genre\")[\"Insomnia\"].mean().values)\n",
        "plt.xlabel(\"Music genre\")\n",
        "plt.ylabel(\"Insomnia rating (1=None, 2=Mild, 3=Moderate, 4=Severe)\")\n",
        "plt.title(\"Relation between music genre and insomnia\")\n",
        "plt.show()\n",
        "\n",
        "# Plot a bar chart of the ratings of OCD by music genre\n",
        "plt.figure(figsize=(10,6))\n",
        "plt.bar(df.groupby(\"Fav genre\")[\"OCD\"].mean().index,\n",
        "        df.groupby(\"Fav genre\")[\"OCD\"].mean().values)\n",
        "plt.xlabel(\"Music genre\")\n",
        "plt.ylabel(\"OCD rating (1=None, 2=Mild, 3=Moderate, 4=Severe)\")\n",
        "plt.title(\"Relation between music genre and OCD\")\n",
        "plt.show()\n"
      ],
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        "id": "H66yf61da2CW",
        "outputId": "441fdab8-82a8-4b9d-c846-9094a3b8de09"
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      "execution_count": null,
      "outputs": [
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              "<Figure size 1000x600 with 1 Axes>"
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            "image/png": 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\n"
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1000x600 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1000x600 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1000x600 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Drop the original mental health columns\n",
        "df = df.drop([\"Anxiety\", \"Depression\", \"Insomnia\", \"OCD\"], axis=1)\n",
        "\n",
        "# Split the data into features and target\n",
        "X = df.drop(\"Mental health\", axis=1)\n",
        "y = df[\"Mental health\"]\n",
        "\n",
        "# Define a one-hot encoder object\n",
        "encoder = OneHotEncoder(handle_unknown=\"ignore\")\n",
        "\n",
        "# Fit and transform the features with the encoder\n",
        "X_enc = encoder.fit_transform(X)"
      ],
      "metadata": {
        "id": "M1DojtDhYMBm"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "# Create a histogram of the age feature\n",
        "sns.histplot(X[\"Age\"])\n",
        "plt.show()\n"
      ],
      "metadata": {
        "id": "7FtScQXXYbxv",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 449
        },
        "outputId": "7bb2c7a2-19b1-449f-9e38-44fe6badc90e"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Select the columns of interest\n",
        "cols = [\"Fav genre\", \"Mental health\"]\n",
        "\n",
        "# Subset the dataframe with the selected columns\n",
        "df = df[cols]\n",
        "\n",
        "# Create a figure with a larger size\n",
        "plt.figure(figsize=(12, 6))\n",
        "\n",
        "# Create a countplot of the favorite genre by the mental health target\n",
        "sns.countplot(data=df, x=\"Fav genre\", hue=\"Mental health\")\n",
        "\n",
        "# Rotate the x-axis labels by 90 degrees\n",
        "plt.xticks(rotation=90)\n",
        "\n",
        "# Show the plot\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 656
        },
        "id": "8t_Cw1yQeNfJ",
        "outputId": "8010db9d-ca40-4920-d070-7d1aeec94728"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1200x600 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "# Training\n"
      ],
      "metadata": {
        "id": "mGSJQNFjeZAj"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# Apply SMOTE on the encoded features and target to create balanced data\n",
        "sm = SMOTE(random_state=42)\n",
        "X_res, y_res = sm.fit_resample(X_enc, y)\n",
        "# Print the value counts of the resampled target\n",
        "print(y_res.value_counts())\n",
        "# Split the resampled data into train and test sets\n",
        "X_train, X_test, y_train, y_test = train_test_split(X_res, y_res, test_size=0.2, random_state=42)\n",
        "# Define a random forest classifier with the best parameters from grid search\n",
        "model = RandomForestClassifier(n_estimators=50, max_depth=3, min_samples_leaf=5, random_state=42)\n",
        "# Fit the model on the train set\n",
        "model.fit(X_train, y_train)\n",
        "# Make predictions on the test set\n",
        "y_pred = model.predict(X_test)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "U4-snQdFedJh",
        "outputId": "270c8b4e-31c7-478d-aaa9-459aebb16671"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "1    726\n",
            "0    726\n",
            "Name: Mental health, dtype: int64\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "# Evaluation\n"
      ],
      "metadata": {
        "id": "7FCh5azGeozC"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# Evaluate the model performance\n",
        "print(\"Confusion matrix:\\n\", confusion_matrix(y_test, y_pred))\n",
        "print(\"Classification report:\\n\", classification_report(y_test, y_pred))\n",
        "print(\"MSE:\", mean_squared_error(y_test, y_pred))\n",
        "print(\"RMSE\", (np.sqrt(mean_squared_error(y_test, y_pred))))"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "zxsRbY0gexIB",
        "outputId": "e2a91cfa-8a85-4906-e923-218168af51fd"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Accuracy: 0.9965635738831615\n",
            "Confusion matrix:\n",
            " [[143   0]\n",
            " [  1 147]]\n",
            "Classification report:\n",
            "               precision    recall  f1-score   support\n",
            "\n",
            "           0       0.99      1.00      1.00       143\n",
            "           1       1.00      0.99      1.00       148\n",
            "\n",
            "    accuracy                           1.00       291\n",
            "   macro avg       1.00      1.00      1.00       291\n",
            "weighted avg       1.00      1.00      1.00       291\n",
            "\n",
            "MSE: 0.003436426116838488\n",
            "RMSE 0.058621038176054914\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [],
      "metadata": {
        "id": "2VcQUBMUgB2b"
      },
      "execution_count": null,
      "outputs": []
    }
  ]
}