{
  "nbformat": 4,
  "nbformat_minor": 5,
  "metadata": {
    "colab": {
      "provenance": []
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "language_info": {
      "name": "python"
    }
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "# Chapter 3 - Swim Data Regression\n",
        "\n",
        "This notebook is self-contained. It recreates the small swim-block table used in the chapter and predicts the missing 100 m time from training-zone distribution."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {},
      "outputs": [],
      "source": [
        "import pandas as pd\n",
        "from sklearn.linear_model import LinearRegression\n",
        "\n",
        "data = pd.DataFrame({\n",
        "    \"Block\": [1, 2, 3, 4, 5, 6],\n",
        "    \"Z0\": [35, 37, 35, 34, 32, 32],\n",
        "    \"Z1\": [25, 35, 27, 42, 45, 47],\n",
        "    \"Z2\": [12, 10, 10, 9, 9, 11],\n",
        "    \"Z3\": [10, 12, 10, 10, 10, 9],\n",
        "    \"Z4\": [2, 2, 2, 2, 2, 2],\n",
        "    \"Z5\": [2, 3, 3, 3, 4, 4],\n",
        "    \"Total\": [86, 99, 87, 100, 102, 105],\n",
        "    \"100m Time\": [55.4, 54.2, 54.8, 52.9, 52.7, None],\n",
        "})\n",
        "data"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {},
      "outputs": [],
      "source": [
        "training_data = data.dropna(subset=[\"100m Time\"])\n",
        "features = [\"Z0\", \"Z1\", \"Z2\", \"Z3\", \"Z4\", \"Z5\"]\n",
        "\n",
        "model = LinearRegression()\n",
        "model.fit(training_data[features], training_data[\"100m Time\"])\n",
        "\n",
        "new_block = data.loc[data[\"100m Time\"].isna(), features]\n",
        "prediction = model.predict(new_block)[0]\n",
        "print(f\"Coefs: {model.coef_}\")\n",
        "print(f\"Intercept: {model.intercept_:.2f}\")\n",
        "print(f\"Predicted 100 m time for block 6: {prediction:.2f} s\")"
      ]
    }
  ]
}