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"from IPython.display import YouTubeVideo, IFrame"
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"# Concepts\n",
"\n",
"This block is all about Geovisualisation and displaying statistical information on maps. We start with an introduction on *what* geovisualisation is; then we follow with the modifiable areal unit problem, a key concept to keep in mind when displaying statistical information spatially; and we wrap up with tips to make awesome choropleths, thematic maps. Each section contains a short clip and a set of slides, plus a few (optional) readings."
]
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{
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"source": [
"## Geovisualisation\n",
"\n",
"Geovisualisation is an area that underpins much what we will discuss in this course. Often, we will be presenting the results of more sophisticated analyses as maps. So getting the principles behind mapping right is critical. In this clip, we cover *what* is (geo)visualisation and why it is important."
]
},
{
"cell_type": "markdown",
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"source": [
"```{sidebar} Slides\n",
"\n",
"The slides used in the clip are available at:\n",
"\n",
"- `[HTML]` \n",
"- `[PDF]` \n",
"\n",
"```"
]
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"\n",
" \n",
" "
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""
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"source": [
"IFrame(\"https://liverpool.instructuremedia.com/embed/fa0ddcdd-b817-423b-a6ea-dcac4e9420e4\",\n",
" width=500,\n",
" height=300\n",
" )"
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"cell_type": "markdown",
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"source": [
"## Geographical containers for data\n",
"\n",
"This section tries to get you to think about the geographical containers we use to represent data in maps. By that, we mean the areas, delineations and aggregations we, implicitly or explicitly, incur in when mapping data. This is an important aspect, but Geographers have been aware of them for a long time, so we are standing on the shoulders of giants."
]
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{
"cell_type": "markdown",
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"```{sidebar} Slides\n",
"\n",
"The slides used in the clip are available at:\n",
"\n",
"- `[HTML]` \n",
"- `[PDF]` \n",
"\n",
"```"
]
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"IFrame(\"https://liverpool.instructuremedia.com/embed/40fcfcc8-df0f-45fb-90c5-f16604db26f5\",\n",
" width=500,\n",
" height=300\n",
" )"
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"## Choropleths\n",
"\n",
"Choropleths are thematic maps and, these days, are everywhere. From elections, to economic inequality, to the distribution of population density, there's a choropleth for everyone. Although technically, it is easy to create choropleths, it is even easier to make *bad* choropleths. Fortunately, there are a few principles that we can follow to create effective choropleths. Get them all delivered right to the conform of your happy place in the following clip and slides!"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"```{sidebar} Slides\n",
"\n",
"The slides used in the clip are available at:\n",
"\n",
"- `[HTML]` \n",
"- `[PDF]` \n",
"\n",
"```"
]
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"\n",
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" "
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"source": [
"IFrame(\"https://liverpool.instructuremedia.com/embed/20d67a48-2bbc-452d-955a-e5d61a6b33e6\",\n",
" width=500,\n",
" height=300\n",
" )"
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"source": [
"### Further readings\n",
"\n",
"The clip above contains a compressed version of the key principles behind successful choropleths. For a more comprehensive coverage, please refer to:\n",
"\n",
"```{margin}\n",
"The chapter is available for free [here](https://geographicdata.science/book/notebooks/05_choropleth.html)\n",
"```\n",
"- Choropleths chapter on the GDS book (in progress) {cite}`reyABwolf`.\n",
"- Cynthia Brewer’s \"Designing Better Maps\" {cite}`brewer2015designing` covers several core aspects of building effective geovisualisations."
]
}
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