From 62cc21b7be4f87b1538d280d241c38696d6da0a2 Mon Sep 17 00:00:00 2001 From: njmason2 Date: Wed, 29 Oct 2025 16:49:24 -0400 Subject: [PATCH] proposal.md argument.ipynb --- .ipynb_checkpoints/argument-checkpoint.ipynb | 360 +++++++++++++++++++ .ipynb_checkpoints/proposal-checkpoint.md | 39 ++ argument.ipynb | 2 +- proposal.md | 12 + 4 files changed, 412 insertions(+), 1 deletion(-) create mode 100644 .ipynb_checkpoints/argument-checkpoint.ipynb create mode 100644 .ipynb_checkpoints/proposal-checkpoint.md diff --git a/.ipynb_checkpoints/argument-checkpoint.ipynb b/.ipynb_checkpoints/argument-checkpoint.ipynb new file mode 100644 index 0000000..4ed27b4 --- /dev/null +++ b/.ipynb_checkpoints/argument-checkpoint.ipynb @@ -0,0 +1,360 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "id": "worldwide-blood", + "metadata": {}, + "source": [ + "# Introduction" + ] + }, + { + "cell_type": "markdown", + "id": "understanding-numbers", + "metadata": {}, + "source": [ + "*✏️ Write 2-3 sentences describing your research.*" + ] + }, + { + "cell_type": "markdown", + "id": "greater-circular", + "metadata": {}, + "source": [ + "## Overarching Question: [✏️ PUT YOUR QUESTION HERE ✏️]" + ] + }, + { + "cell_type": "markdown", + "id": "appreciated-testimony", + "metadata": {}, + "source": [ + "*✏️ Write 2-3 sentences explaining why this question.*" + ] + }, + { + "cell_type": "markdown", + "id": "permanent-pollution", + "metadata": {}, + "source": [ + "# Data" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "technical-evans", + "metadata": {}, + "outputs": [], + "source": [ + "#Include any import statements you will need\n", + "import pandas as pd\n", + "import matplotlib.pyplot as plt" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "overhead-sigma", + "metadata": {}, + "outputs": [], + "source": [ + "### 💻 FILL IN YOUR DATASET FILE NAME BELOW 💻 ###\n", + "\n", + "file_name = \"YOUR_DATASET_FILE_NAME.csv\"\n", + "dataset_path = \"data/\" + file_name\n", + "\n", + "df = pd.read_csv(dataset_path)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "heated-blade", + "metadata": {}, + "outputs": [], + "source": [ + "df.head()" + ] + }, + { + "cell_type": "markdown", + "id": "continental-franklin", + "metadata": {}, + "source": [ + "**Data Overview**\n", + "\n", + "*✏️ Write 2-3 sentences describing this dataset. Be sure to include where the data comes from and what it contains.*" + ] + }, + { + "cell_type": "markdown", + "id": "infinite-instrument", + "metadata": {}, + "source": [ + "# Methods and Results" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "basic-canadian", + "metadata": {}, + "outputs": [], + "source": [ + "#Import any helper files you need here" + ] + }, + { + "cell_type": "markdown", + "id": "recognized-positive", + "metadata": {}, + "source": [ + "## First Research Question: [✏️ PUT YOUR QUESTION HERE ✏️]\n" + ] + }, + { + "cell_type": "markdown", + "id": "graduate-palmer", + "metadata": {}, + "source": [ + "### Methods" + ] + }, + { + "cell_type": "markdown", + "id": "endless-variation", + "metadata": {}, + "source": [ + "*Explain how you will approach this research question below. Consider the following:* \n", + " - *Which aspects of the dataset will you use?* \n", + " - *How will you reorganize/store the data?* \n", + " - *What data science tools/functions will you use and why?* \n", + " \n", + "✏️ *Write your answer below:*\n", + "\n" + ] + }, + { + "cell_type": "markdown", + "id": "portuguese-japan", + "metadata": {}, + "source": [ + "### Results " + ] + }, + { + "cell_type": "code", + "execution_count": 17, + "id": "negative-highlight", + "metadata": {}, + "outputs": [], + "source": [ + "#######################################################################\n", + "### 💻 YOUR WORK GOES HERE TO ANSWER THE FIRST RESEARCH QUESTION 💻 \n", + "### \n", + "### Your data analysis may include a statistic and/or a data visualization\n", + "#######################################################################" + ] + }, + { + "cell_type": "code", + "execution_count": 16, + "id": "victorian-burning", + "metadata": {}, + "outputs": [], + "source": [ + "# 💻 YOU CAN ADD NEW CELLS WITH THE \"+\" BUTTON " + ] + }, + { + "cell_type": "markdown", + "id": "collectible-puppy", + "metadata": {}, + "source": [ + "## Second Research Question: [✏️ PUT YOUR QUESTION HERE ✏️]\n" + ] + }, + { + "cell_type": "markdown", + "id": "demographic-future", + "metadata": {}, + "source": [ + "### Methods" + ] + }, + { + "cell_type": "markdown", + "id": "incorporate-roller", + "metadata": {}, + "source": [ + "*Explain how you will approach this research question below. Consider the following:* \n", + " - *Which aspects of the dataset will you use?* \n", + " - *How will you reorganize/store the data?* \n", + " - *What data science tools/functions will you use and why?* \n", + "\n", + "✏️ *Write your answer below:*\n" + ] + }, + { + "cell_type": "markdown", + "id": "juvenile-creation", + "metadata": {}, + "source": [ + "### Results " + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "id": "pursuant-surrey", + "metadata": {}, + "outputs": [], + "source": [ + "#######################################################################\n", + "### 💻 YOUR WORK GOES HERE TO ANSWER THE SECOND RESEARCH QUESTION 💻 \n", + "###\n", + "### Your data analysis may include a statistic and/or a data visualization\n", + "#######################################################################" + ] + }, + { + "cell_type": "code", + "execution_count": 15, + "id": "located-night", + "metadata": {}, + "outputs": [], + "source": [ + "# 💻 YOU CAN ADD NEW CELLS WITH THE \"+\" BUTTON " + ] + }, + { + "cell_type": "markdown", + "id": "infectious-symbol", + "metadata": {}, + "source": [ + "# Discussion" + ] + }, + { + "cell_type": "markdown", + "id": "furnished-camping", + "metadata": { + "code_folding": [] + }, + "source": [ + "## Considerations" + ] + }, + { + "cell_type": "markdown", + "id": "bearing-stadium", + "metadata": {}, + "source": [ + "*It's important to recognize the limitations of our research.\n", + "Consider the following:*\n", + "\n", + "- *Do the results give an accurate depiction of your research question? Why or why not?*\n", + "- *What were limitations of your datset?*\n", + "- *Are there any known biases in the data?*\n", + "\n", + "✏️ *Write your answer below:*" + ] + }, + { + "cell_type": "markdown", + "id": "beneficial-invasion", + "metadata": {}, + "source": [ + "## Summary" + ] + }, + { + "cell_type": "markdown", + "id": "about-raise", + "metadata": {}, + "source": [ + "*Summarize what you discovered through the research. Consider the following:*\n", + "\n", + "- *What did you learn about your media consumption/digital habits?*\n", + "- *Did the results make sense?*\n", + "- *What was most surprising?*\n", + "- *How will this project impact you going forward?*\n", + "\n", + "✏️ *Write your answer below:*" + ] + } + ], + "metadata": { + "jupytext": { + "cell_metadata_json": true, + "text_representation": { + "extension": ".Rmd", + "format_name": "rmarkdown", + "format_version": "1.2", + "jupytext_version": "1.9.1" + } + }, + "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": "3.9.7" + }, + "toc": { + "base_numbering": 1, + "nav_menu": {}, + "number_sections": false, + "sideBar": true, + "skip_h1_title": false, + "title_cell": "Table of Contents", + "title_sidebar": "Contents", + "toc_cell": false, + "toc_position": {}, + "toc_section_display": true, + "toc_window_display": false + }, + "varInspector": { + "cols": { + "lenName": 16, + "lenType": 16, + "lenVar": 40 + }, + "kernels_config": { + "python": { + "delete_cmd_postfix": "", + "delete_cmd_prefix": "del ", + "library": "var_list.py", + "varRefreshCmd": "print(var_dic_list())" + }, + "r": { + "delete_cmd_postfix": ") ", + "delete_cmd_prefix": "rm(", + "library": "var_list.r", + "varRefreshCmd": "cat(var_dic_list()) " + } + }, + "types_to_exclude": [ + "module", + "function", + "builtin_function_or_method", + "instance", + "_Feature" + ], + "window_display": false + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} diff --git a/.ipynb_checkpoints/proposal-checkpoint.md b/.ipynb_checkpoints/proposal-checkpoint.md new file mode 100644 index 0000000..2586c0c --- /dev/null +++ b/.ipynb_checkpoints/proposal-checkpoint.md @@ -0,0 +1,39 @@ +# Project proposal + +This planning document will also form the introduction of your +argument. + +## Overarching Question + +### What central question are you interested in exploring? Why are you interested in exploring this question? + +*This should be the big picture question that you ask; use at least 5 +sentences to describe why you are interested in it.* + +### What specific research questions will you investigate? + +*List 2-4 specific research questions. Each should be answerable +using your data set.* + +## Data source + +### What data set will you use to answer your overarching question? + +*Give the title of your data set and provide a link to your data.* + +### Where is this data from? + +*Describe the source of the data set--not just where you downloaded it, but +the person or organization who gathered the data. Explain why you trust them.* + +### What is this data about? + +*Describe the nature of the data in the dataset, including the number of rows +and some of the columns which will be important to you.* + +## Methods + +### How will you use your data set to answer your quantitative questions? + +*For each research question, explain what you will do with the data set +to answer the question, and how you will present your answer (e.g. a chart or a table).* diff --git a/argument.ipynb b/argument.ipynb index 4ed27b4..b688086 100644 --- a/argument.ipynb +++ b/argument.ipynb @@ -310,7 +310,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.9.7" + "version": "3.12.3" }, "toc": { "base_numbering": 1, diff --git a/proposal.md b/proposal.md index 2586c0c..dcb62d7 100644 --- a/proposal.md +++ b/proposal.md @@ -3,6 +3,8 @@ This planning document will also form the introduction of your argument. +Nelson Mason - Date: 10/29/2025 + ## Overarching Question ### What central question are you interested in exploring? Why are you interested in exploring this question? @@ -10,10 +12,20 @@ argument. *This should be the big picture question that you ask; use at least 5 sentences to describe why you are interested in it.* +I want to know about what relationship exists, if any, between an adult (18 +) +person's age and their weight (I'll use metric). +I'm trying to find out at what age, on average, do people experience a dramatic +weight gain or loss, if at all? +I'm curious to find out if such a dramatic increase or decrease in weight can +be captured in a one-time snapshot database, where individuals are NOT tracked +over a period of time, but ONLY once. + ### What specific research questions will you investigate? *List 2-4 specific research questions. Each should be answerable using your data set.* +What number or percentage can be used to accurately indicate a +dramatic change in weight by age? How do I determine what "dramatic" is? ## Data source