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revise activity 1
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@zmuhls
zmuhls committed Oct 2, 2024
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{
"cells": [
{
"cell_type": "markdown",
"metadata": {
"id": "view-in-github",
"colab_type": "text"
},
"source": [
"<a href=\"https://colab.research.google.com/github/zmuhls/ccny-data-science/blob/main/activity_1.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
]
},
{
"cell_type": "markdown",
"id": "e06e8c55-6300-414a-b248-e610342edc6e",
"metadata": {
"id": "e06e8c55-6300-414a-b248-e610342edc6e"
},
"source": [
"# Activity 1"
]
},
{
"cell_type": "markdown",
"id": "8f0211dc-fa5f-4237-93a7-75a3cf040895",
"metadata": {
"id": "8f0211dc-fa5f-4237-93a7-75a3cf040895"
},
"source": [
"For this activity, we will be familiarizing ourselves with creating Python variables and data types.\n",
"\n",
"Please make sure you open this file in Jupyter Notebook or Google Colab -- you will have to either open Jupyter Notebook first or upload the file to Google Colab before being able to edit the file. In turn, make sure that you **print your output** for every response in the activity.\n",
"\n",
"-----\n",
"## Submission Instructions\n",
"1. Upload the completed activity to the \"Activities\" and \"Reflections\" folders of your GitHub portfolio;\n",
"2. Ensure your submission consists of two files: (a) one reflection in markdown uploaded to \"Reflections\" (e.g. `a1_reflection.md`); and (b) one Jupyter notebook with completed responses for each step of the activity (e.g. `a1_building_blocks.ipynb`)."
]
},
{
"cell_type": "markdown",
"id": "d00e1320-3c81-497c-9ab8-c09fe0a21e26",
"metadata": {
"id": "d00e1320-3c81-497c-9ab8-c09fe0a21e26"
},
"source": [
"## Please respond with your code in the cells."
]
},
{
"cell_type": "markdown",
"id": "eda0bdc8-c7d3-4c61-abaf-1fbae7a35034",
"metadata": {
"id": "eda0bdc8-c7d3-4c61-abaf-1fbae7a35034"
},
"source": [
"1. Create a variable for your first name called ```first```."
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "5150dcfe-7018-4c89-bb50-4c432379924d",
"metadata": {
"id": "5150dcfe-7018-4c89-bb50-4c432379924d"
},
"outputs": [],
"source": []
},
{
"cell_type": "markdown",
"id": "c61ee004-5faf-4710-8ae6-4a752b2ad673",
"metadata": {
"id": "c61ee004-5faf-4710-8ae6-4a752b2ad673"
},
"source": [
"2. Create a variable for your last name called ```last```."
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "9143791d-5460-41c0-9e80-3bc59318b2ec",
"metadata": {
"id": "9143791d-5460-41c0-9e80-3bc59318b2ec"
},
"outputs": [],
"source": []
},
{
"cell_type": "markdown",
"id": "1a81a966-5a53-471e-a479-78085f26ad85",
"metadata": {
"id": "1a81a966-5a53-471e-a479-78085f26ad85"
},
"source": [
"3. Create a variable for your age called ```age```."
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "d50476c7-f82c-4f8e-a20d-18f6e36de9b2",
"metadata": {
"id": "d50476c7-f82c-4f8e-a20d-18f6e36de9b2"
},
"outputs": [],
"source": []
},
{
"cell_type": "markdown",
"id": "8b92dcfb-7784-41bc-b58d-0678d0a85258",
"metadata": {
"id": "8b92dcfb-7784-41bc-b58d-0678d0a85258"
},
"source": [
"4. Using the variables you have created, create a new variable ```name``` by joining your first and last names together."
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "d21cd5ed-26aa-4ab4-a6e7-02f992bd0119",
"metadata": {
"id": "d21cd5ed-26aa-4ab4-a6e7-02f992bd0119"
},
"outputs": [],
"source": []
},
{
"cell_type": "markdown",
"id": "cf57471f-11a9-41d9-8342-a0b5ff28b8b0",
"metadata": {
"id": "cf57471f-11a9-41d9-8342-a0b5ff28b8b0"
},
"source": [
"5. Use string methods to convert the variable ```activity1 = \" THIS IS MY FIRST PYTHON ACTIVITY!! \"``` to lowercase and remove any leading or trailing white space, then print the output as a new variable: ```activity1_lower```."
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "19cf1155-0517-465f-aa6e-2b3bf0406d64",
"metadata": {
"id": "19cf1155-0517-465f-aa6e-2b3bf0406d64"
},
"outputs": [],
"source": [
"activity1 = \" WOOHOO! THIS IS MY FIRST PYTHON ACTIVITY!! \"\n"
]
},
{
"cell_type": "markdown",
"id": "927c8101-95a3-4d1d-b6d9-d390b94b2ad9",
"metadata": {
"id": "927c8101-95a3-4d1d-b6d9-d390b94b2ad9"
},
"source": [
"6. What data type is the variable ```age```? Declare the value and print the data type."
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "02a0e871-653a-433d-bf31-8430c6c55a49",
"metadata": {
"id": "02a0e871-653a-433d-bf31-8430c6c55a49"
},
"outputs": [],
"source": []
},
{
"cell_type": "markdown",
"id": "006b4e55-9d77-4007-86a5-e03408b737f1",
"metadata": {
"id": "006b4e55-9d77-4007-86a5-e03408b737f1"
},
"source": [
"7. What happens when you add ```10``` to your ```name```? Please demonstrate it in the cell below and add an inline comment that provides a brief explanation of the result. "
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "547478df-4528-4697-a480-80b383d6aa29",
"metadata": {
"id": "547478df-4528-4697-a480-80b383d6aa29"
},
"outputs": [],
"source": []
},
{
"cell_type": "markdown",
"source": [
"8. Declare a variable that asks for user input, then print the variable storing their response as the output"
],
"metadata": {
"id": "VOnDoeLieoBW"
},
"id": "VOnDoeLieoBW"
},
{
"cell_type": "code",
"source": [],
"metadata": {
"id": "FVPp8yrZfueN"
},
"id": "FVPp8yrZfueN",
"execution_count": null,
"outputs": []
},
{
"cell_type": "markdown",
"id": "20bd577c-9c9c-4084-90c0-d1dc38f59da5",
"metadata": {
"id": "20bd577c-9c9c-4084-90c0-d1dc38f59da5"
},
"source": [
"-------"
]
},
{
"cell_type": "markdown",
"id": "0f5f0cca-38e0-4ffd-8adf-e65469913076",
"metadata": {
"id": "0f5f0cca-38e0-4ffd-8adf-e65469913076"
},
"source": [
"## Side quest challenge\n",
"\n",
"This side quest is an extra credit challenge. You can still get full credit for this activity even if you do not complete this challenge."
]
},
{
"cell_type": "markdown",
"id": "6837c438-eeba-498d-9cc5-08aadf1420dc",
"metadata": {
"id": "6837c438-eeba-498d-9cc5-08aadf1420dc"
},
"source": [
"Use ***f-string formatting*** to display your ```name``` and ```age``` in a sentence. \n",
"\n",
"Check out Kyle Bradbury and Nick Eubank's [introduction to f-strings](https://nickeubank.github.io/practicaldatascience_book/notebooks/other/fstrings.html)."
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "5e88c0c0-288b-4f3b-82ff-8c8582855b1d",
"metadata": {
"id": "5e88c0c0-288b-4f3b-82ff-8c8582855b1d"
},
"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": "3.11.5"
},
"colab": {
"provenance": [],
"include_colab_link": true
}
},
"nbformat": 4,
"nbformat_minor": 5
}

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