58 lines
2.1 KiB
Plaintext
58 lines
2.1 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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"# Sami Almuallim"
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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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"## Research question/interests\n",
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"\n",
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"Is there a positive or a negative correlation between taxes paid and the pride of a given queer neighbourhood?\n",
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"\n",
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"- Similar again to the first research question posed, we'll need to find another data set containing geographically located tax data, which should be easy to acquire from the US government (for example, [in our cursory research, we found this data set from the IRS](https://www.irs.gov/statistics/soi-tax-stats-individual-income-tax-statistics-2018-zip-code-data-soi)).\n",
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"- This would bring the number of data sets used in this project up to three, which might present some challenges in terms of the amount of data wrangling necessary to bring it all together.\n",
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"- To measure this, we would rank the neighbourhoods presented in the gaybourhoods data set by pride (an open question which we will explore in a separate research question)\n",
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"\n",
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"\n",
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"Is there a correlation between pride flags & parades & gay bars in a given region? In other words, how are the different metrics of pride represented in this data set correlated?\n",
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"\n",
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"- This will probably be the simplest research question, requiring only the data contained in our original data set. To explore this topic, we will use different visualization methods discussed in class to develop a better understanding of the data."
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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": null,
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"outputs": [],
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"source": []
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}
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],
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"display_name": "Python 3 (ipykernel)",
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"language": "python",
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"name": "python3"
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"version": "3.10.9"
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