{ "cells": [ { "cell_type": "markdown", "id": "5c291475-8c7c-461c-9b12-545a887b2432", "metadata": {}, "source": [ "# Jupyter Lab\n", "\n", "## A Quick Start Guide\n", "\n", "Welcome to the wonderful world of Jupyter lab! \n", "This is a Data Science playground where you can easily write code that builds and builds. It's an ideal environment for: \n", "- Research & Development\n", "- Prototyping\n", "- Learning (that's us!)\n", "\n", "It's not typically used for shipping production code, and in Week 8 we'll explore the bridge between Jupyter and python code.\n", "\n", "A file in Jupyter Lab, like this one, is called a **Notebook**.\n", "\n", "A long time ago, Jupyter used to be called \"IPython\", and so the extensions of notebooks are \".ipynb\" which stands for \"IPython Notebook\".\n", "\n", "On the left is a File Browser that lets you navigate around the weeks and choose different notebooks. But you probably know that already, or you wouldn't have got here!\n", "\n", "The notebook consists of a series of square boxes called \"cells\". Some of them contain text, like this cell, and some of them contain code, like the cell below.\n", "\n", "Click in a cell with code and press `Shift + Return` (or `Shift + Enter`) to run the code and print the output.\n", "\n", "Do that now for the cell below this:" ] }, { "cell_type": "code", "execution_count": null, "id": "33d37cd8-55c9-4e03-868c-34aa9cab2c80", "metadata": {}, "outputs": [], "source": [ "2 + 2" ] }, { "cell_type": "markdown", "id": "9e95df7b-55c6-4204-b8f9-cae83360fc23", "metadata": {}, "source": [ "## Congrats!\n", "\n", "Now run the next cell which sets a value, followed by the cell after it to print the value" ] }, { "cell_type": "code", "execution_count": null, "id": "585eb9c1-85ee-4c27-8dc2-b4d8d022eda0", "metadata": {}, "outputs": [], "source": [ "# Set a value for a variable\n", "\n", "favorite_fruit = \"bananas\"" ] }, { "cell_type": "code", "execution_count": null, "id": "a067d2b1-53d5-4aeb-8a3c-574d39ff654a", "metadata": {}, "outputs": [], "source": [ "# Use the variable\n", "\n", "print(f\"My favorite fruit is {favorite_fruit}\")" ] }, { "cell_type": "code", "execution_count": null, "id": "4c5a4e60-b7f4-4953-9e80-6d84ba4664ad", "metadata": {}, "outputs": [], "source": [ "# Now change the variable\n", "\n", "favorite_fruit = f\"anything but {favorite_fruit}\"" ] }, { "cell_type": "markdown", "id": "9442d5c9-f57d-4839-b0af-dce58646c04f", "metadata": {}, "source": [ "# Now go back and rerun the prior cell with the print statement\n", "\n", "See how it prints something different, even though favorite_fruit was changed afterwards? \n", "The order that code appears in the notebook doesn't matter. What matters is the order that the code is **executed**." ] }, { "cell_type": "code", "execution_count": null, "id": "8e5ec81d-7c5b-4025-bd2e-468d67b581b6", "metadata": {}, "outputs": [], "source": [ "# More coming here soon!" ] }, { "cell_type": "code", "execution_count": null, "id": "b51950ca-b512-4829-974f-442bd50e29a5", "metadata": {}, "outputs": [], "source": [] } ], "metadata": { "kernelspec": { "display_name": "Python 3 (ipykernel)", "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": "3.11.10" } }, "nbformat": 4, "nbformat_minor": 5 }