diff --git a/Notebook.ipynb b/Notebook.ipynb
index 6e4fbbdfc18dedca2e0bca2c9a185f47024a4210..82715d85b044e6c318736d1b694b48a3783e958b 100644
--- a/Notebook.ipynb
+++ b/Notebook.ipynb
@@ -10,19 +10,21 @@
"\n",
"In this project we decided to analyze anxiety in Gamers. We picked the dataset from kaggle because it intersected our personal interests. The data can be found [here](https://www.kaggle.com/datasets/divyansh22/online-gaming-anxiety-data)\n",
"\n",
- "The data was acquired by a survey published and shared online. This way everyone could participate. For us that also means analyzing and di"
+ "The data was acquired by a survey published and shared online. This way everyone could participate. For us that also means analyzing and di\n",
+ "\n",
+ "## Motivation - Why "
]
},
{
"cell_type": "code",
- "execution_count": 1,
+ "execution_count": 17,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
- "<src.Dataset.Dataset object at 0x000001CA32F35BD0>\n"
+ "<src.Dataset.Dataset object at 0x000001906063BDC0>\n"
]
}
],
@@ -33,6 +35,11 @@
"print(dataset)"
]
},
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": []
+ },
{
"cell_type": "markdown",
"metadata": {},
@@ -56,7 +63,7 @@
},
{
"cell_type": "code",
- "execution_count": 2,
+ "execution_count": 7,
"metadata": {},
"outputs": [],
"source": [
@@ -148,37 +155,25 @@
"metadata": {},
"source": [
"# Analysis\n",
+ "\n",
+ "## Preprocessing \n",
"Explained new columns and why we did that (\"Is_narcissist, \"Anxiety_score\")\n",
- "## Normalizing the Data \n"
+ "\n",
+ "Some columns gave the options to write individual responses. Naturally those are not useful in data analysis. In some cases we cleaned the columns and changes the unusual cases to \"Other\"/\"NA\"\n",
+ "### Cleaned Columns\n",
+ "+ \"Whyplay\" \n",
+ "+ \n",
+ "## Normalizing the Data \n",
+ "\n",
+ "+ \"Is_narcissist,\n",
+ "+ \"Anxiety_score\""
]
},
{
"cell_type": "code",
- "execution_count": 2,
+ "execution_count": null,
"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": 2,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
+ "outputs": [],
"source": [
"# Executing and showing new columns \n",
"dataset.get_combined_anxiety_score(dataset.get_dataframe())"
@@ -196,18 +191,25 @@
"\n",
"### Women vs Men \n",
"\n",
- "Explanation "
+ "Explanation \n",
+ ""
]
},
{
"cell_type": "code",
- "execution_count": 3,
+ "execution_count": 23,
"metadata": {},
"outputs": [],
"source": [
+ "\n",
"# SIDE BY SIDE PLOTS \n",
"# LEFT = LINE Graph distribution of Anxiety Score Related to Group\n",
- "# RIGHT = Stacked Bars comparing the GROUP with = 1. 2. 3. "
+ "# RIGHT = Stacked Bars comparing the GROUP with = \n",
+ "# 1.[Work] - 4 Bars\n",
+ "# 2.[Degree] - 5 Bars\n",
+ "# 3.[Whyplay ] - 4 Bars (Everything until \"All of them\")\n",
+ "\n",
+ "#"
]
},
{
@@ -220,32 +222,16 @@
},
{
"cell_type": "code",
- "execution_count": null,
- "metadata": {},
- "outputs": [],
- "source": [
- "# SIDE BY SIDE PLOTS \n",
- "# LEFT = LINE Graph distribution of Anxiety Score Related to Group\n",
- "# RIGHT = Stacked Bars comparing the GROUP with = 1. 2. 3. "
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "### High Education vs Lower Education\n",
- "Explanation"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 4,
+ "execution_count": 24,
"metadata": {},
"outputs": [],
"source": [
"# SIDE BY SIDE PLOTS \n",
"# LEFT = LINE Graph distribution of Anxiety Score Related to Group\n",
- "# RIGHT = Stacked Bars comparing the GROUP with = 1. 2. 3. "
+ "# RIGHT = Stacked Bars comparing the GROUP with = \n",
+ "# 1.[Work] - 4 Bars\n",
+ "# 2.[Degree] - 5 Bars\n",
+ "# 3.[Whyplay ] - 4 Bars (Everything until \"All of them\")"
]
},
{
@@ -257,25 +243,28 @@
},
{
"cell_type": "code",
- "execution_count": null,
+ "execution_count": 25,
"metadata": {},
"outputs": [],
"source": [
"# SIDE BY SIDE PLOTS \n",
"# LEFT = LINE Graph distribution of Anxiety Score Related to Group\n",
- "# RIGHT = Stacked Bars comparing the GROUP with = 1. 2. 3. "
+ "# RIGHT = Stacked Bars comparing the GROUP with = \n",
+ "# 1.[Work] - 4 Bars\n",
+ "# 2.[Degree] - 5 Bars\n",
+ "# 3.[Whyplay ] - 4 Bars (Everything until \"All of them\")"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
- "## Q2 - Correlations betweeet played hours and ones well being. "
+ "## Q2 - Correlations between played hours and one's well being. "
]
},
{
"cell_type": "code",
- "execution_count": null,
+ "execution_count": 26,
"metadata": {},
"outputs": [],
"source": [
@@ -291,7 +280,7 @@
},
{
"cell_type": "code",
- "execution_count": 4,
+ "execution_count": 27,
"metadata": {},
"outputs": [],
"source": [
@@ -308,7 +297,7 @@
},
{
"cell_type": "code",
- "execution_count": 5,
+ "execution_count": 28,
"metadata": {},
"outputs": [],
"source": [
@@ -335,20 +324,27 @@
"2. Is the amount of educated players similar "
]
},
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ ""
+ ]
+ },
{
"cell_type": "code",
- "execution_count": null,
+ "execution_count": 29,
"metadata": {},
"outputs": [],
"source": [
"#### Analyze the countries amounting to Top 7 or 90% of the survey. \n",
"\n",
"\n",
- "#Q4. MAP PLOT = Most played game per country (Dont do it if its League everywhere. )\n",
+ "#Q4.MAP PLOT = Most played game per country (Dont do it if its League everywhere. )\n",
"#Q4 MAP PLOT = Heat Map with redder areas for more Anxiety in the country. \n",
"#Q1.2 Grouped Bar Chart with the top game next to the \"Anxiety Score\"\n",
"\n",
- "#2 Grouped Bars with Education per Country IF POSSIBLE grouped with a bar for the anxiety "
+ "#2 Scatter PLot like in the example "
]
}
],