{
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "# Loading CSV Data in Python\n",
        "\n",
        "In this notebook, you will load `wage_sample.csv` and inspect the first rows."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {},
      "outputs": [],
      "source": [
        "import pandas as pd\n",
        "\n",
        "df = pd.read_csv(\"wage_sample.csv\")\n",
        "print(df.head())"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {},
      "outputs": [],
      "source": [
        "print(\"Rows:\", len(df))\n",
        "print(\"Columns:\", list(df.columns))"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "## Think about it\n",
        "\n",
        "- Which column is the outcome variable if we want to explain wages?\n",
        "- Which columns might help explain wage differences?"
      ]
    }
  ],
  "metadata": {
    "kernelspec": {
      "display_name": "Python 3",
      "language": "python",
      "name": "python3"
    },
    "language_info": {
      "name": "python",
      "version": "3.11"
    }
  },
  "nbformat": 4,
  "nbformat_minor": 5
}