160 lines
4.0 KiB
Plaintext
160 lines
4.0 KiB
Plaintext
{
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"cells": [
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"# Optional Lab: Brief Introduction to Python and Jupyter Notebooks\n",
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"Welcome to the first optional lab! \n",
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"Optional labs are available to:\n",
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"- provide information - like this notebook\n",
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"- reinforce lecture material with hands-on examples\n",
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"- provide working examples of routines used in the graded labs"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## Goals\n",
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"In this lab, you will:\n",
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"- Get a brief introduction to Jupyter notebooks\n",
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"- Take a tour of Jupyter notebooks\n",
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"- Learn the difference between markdown cells and code cells\n",
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"- Practice some basic python\n"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"The easiest way to become familiar with Jupyter notebooks is to take the tour available above in the Help menu:"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"<figure>\n",
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" <center> <img src=\"./images/C1W1L1_Tour.PNG\" alt='missing' width=\"400\" ><center/>\n",
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"<figure/>"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"Jupyter notebooks have two types of cells that are used in this course. Cells such as this which contain documentation called `Markdown Cells`. The name is derived from the simple formatting language used in the cells. You will not be required to produce markdown cells. Its useful to understand the `cell pulldown` shown in graphic below. Occasionally, a cell will end up in the wrong mode and you may need to restore it to the right state:"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"<figure>\n",
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" <img src=\"./images/C1W1L1_Markdown.PNG\" alt='missing' width=\"400\" >\n",
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"<figure/>"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"The other type of cell is the `code cell` where you will write your code:"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 1,
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"This is code cell\n"
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]
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}
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],
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"source": [
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"#This is a 'Code' Cell\n",
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"print(\"This is code cell\")"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## Python\n",
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"You can write your code in the code cells. \n",
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"To run the code, select the cell and either\n",
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"- hold the shift-key down and hit 'enter' or 'return'\n",
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"- click the 'run' arrow above\n",
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"<figure>\n",
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" <img src=\"./images/C1W1L1_Run.PNG\" width=\"400\" >\n",
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"<figure/>\n",
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"\n",
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" "
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"### Print statement\n",
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"Print statements will generally use the python f-string style. \n",
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"Try creating your own print in the following cell. \n",
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"Try both methods of running the cell."
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]
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},
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{
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"cell_type": "code",
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"execution_count": 2,
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"f strings allow you to embed variables right in the strings!\n"
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]
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}
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],
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"source": [
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"# print statements\n",
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"variable = \"right in the strings!\"\n",
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"print(f\"f strings allow you to embed variables {variable}\")"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"# Congratulations!\n",
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"You now know how to find your way around a Jupyter Notebook."
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]
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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": "Python 3",
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"language": "python",
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"name": "python3"
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},
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"language_info": {
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"codemirror_mode": {
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"name": "ipython",
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"version": 3
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},
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"file_extension": ".py",
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"mimetype": "text/x-python",
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.7.6"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 5
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}
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