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{
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Anxiety in Computer-Gamers: differences, similiratires and learnings\n",
"\n",
"# Overview \n",
"\n",
"In this project we decided to analyze anxiety in Gamers. We picked the dataset from kaggle because it intersected our personal interests. \n",
"\n",
"The data was acquired by a survey published and shared online. This way everyone could "
]
},
{
"cell_type": "code",
"execution_count": 1,
"metadata": {},
"outputs": [],
"source": [
"# Plotting the \"Reference\" Column where the Data is from"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Explanation of technical terms \n",
"\n",
"### SPIN \n",
"\n",
"### GAD \n",
"s a mental and behavioral, disorder, specifally an anxiety disorder characterized by excessive, uncontrollable and often irrational worry about events or activities. There are specific questionaires you can use to evaluate the disorder. \n",
"#### Worries of concern\n",
"\n",
"The worries of concern are \n",
"1. Test \n",
"2. Test\n",
"### SWL"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"<src.Dataset.Dataset object at 0x00000285ED26C7C0>\n"
]
}
],
"source": [
"from src.Dataset import Dataset \n",
"\n",
"dataset = Dataset(\"data\\GamingStudy_data.csv\")\n",
"print(dataset)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Analysis\n",
"\n",
"## Normalizing the Data \n",
"\n"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"0 0.202288\n",
"1 0.517320\n",
"2 0.497993\n",
"3 0.272969\n",
"4 0.533567\n",
" ... \n",
"13459 0.212092\n",
"13460 0.601914\n",
"13461 0.125210\n",
"13462 0.591783\n",
"13463 0.243231\n",
"Length: 13464, dtype: float64"
]
},
"execution_count": 3,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"dataset.get_combined_anxiety_score(dataset.get_dataframe())"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Q1 - Which gamers are more anxiety prone ? \n",
"\n",
"Text .......\n",
"\n",
"We compare\n",
"\n",
"### Women vs Men \n",
"\n",
"Explanation "
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {},
"outputs": [],
"source": [
"# All of this with stacked Bars \n",
"# "
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Competetive vs Easy Going Players \n",
"Explanation "
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### High Education vs Lower Education\n",
"Explanation"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {},
"outputs": [],
"source": [
"# Plot demonstrating the differenc with stacked bars "
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Narcissist vs Non-Narcissist"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": []
}
],
"metadata": {
"kernelspec": {
"display_name": "base",
"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": "3.10.9"
},
"orig_nbformat": 4
},
"nbformat": 4,
"nbformat_minor": 2
}