Kyle Walker
@kyle_e_walker
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Helping you use demographic and spatial data more effectively. Workshops: Book:
Fort Worth, TX
Joined May 2010
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If students tell me they want to get a PhD, I will support them and write them a letter. But I also tell them, because no one told me at age 21-22:
-- You will spend your twenties making poverty wages while your peers start getting salaries, raises, bonuses, etc.;
-- You may…
Real, non-trollish life advice:
If you're a smart young person and you really want to go to graduate school, then by all means go. But if you're on the fence, probably don't. That's not where the action is. And it's not where the action is going to be for the foreseeable future.
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The pre-print version of my book "Analyzing US Census Data: Methods, Maps, and Models in
#rstats
" is now available to read for free online: . Read on in this thread for an overview of the book's content!
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Tableau-style linked hover between a map and chart in
#rstats
- all you need is ggiraph + patchwork, no Shiny required! Here's how, with an example adapted from the tidycensus docs:
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purrr::map() is a superpower when I need to produce consistent maps in bulk for a report or presentation
In the linked example (with shapefiles previously cached), I made 51 maps in 51 seconds, each with an appropriate title
#rstats
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I've been using Quarto to create interactive tutorials for my
#rstats
workshops this year.
The ability to embed code, descriptions, and interactive content helps create fantastic learning resources.
You can check out these tutorials for yourselves:
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"Analyzing US Census Data: Methods, Maps, and Models in
#rstats
" is almost ready for you to read for free online. Just the intro chapter and conclusion left to finish up!
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An interactive map in a single tweet:
tidycensus::get_acs(
geography = "tract",
variables = "B19013_001",
state = "IL",
geometry = TRUE
) |>
mapview::mapview(
zcol = "estimate",
= "Median household income"
)
#rstats
#GIS
#demographics
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My favorite
#Python
package to use is spopt, a library for spatial optimization that integrates nicely with
@geopandas
. spopt helps you solve a wide variety of business problems, including:
📊 Facility location planning;
📊 Sales territory design;
📊 Maximizing market share;…
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Analyzing the "catchment areas" around facilities is a critical topic in spatial data science.
How you define a catchment area can matter a lot. Should you use distance, or should you use travel-times?
Read Ch7 of my book for a workflow in
#rstats
:
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I use Quarto to create interactive tutorials for my
#rstats
workshops.
The ability to embed code, descriptions, and interactive content helps create fantastic learning resources.
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My new favorite word processor is the
@rstudio
Visual Editor for R Markdown. Among many other features, automatic citation lookup by copy-pasting a DOI (citing here
@edzerpebesma
's article on {sf} in my book) is a breeze.
#rstats
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Tutorial: query the 2.35 BILLION row global buildings dataset from
@OvertureMaps
in
#rstats
and visualize in 3D w/deck.gl
Learn about the `open_dataset()` function in R's arrow 📦, which might change your life (or at least your work with big datasets)
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This article from
@R_Graph_Gallery
was exactly what I needed for class when discussing issues with pie charts this week, and it includes
#rstats
code to allow for reproduction/customization of the illustrations
#dataviz
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This week, my
#rstats
package tidycensus passed the milestone of 500,000 all-time downloads from the Posit CRAN mirror
A sincere thanks to all who have used the package over the past six and a half years!
And if you haven't used it yet - now's a great time to try it out!…
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Coming soon to
#rstats
tidycensus: a fast, automated method for dot-density mapping of
@uscensusbureau
data. Includes a dasymetric option to avoid those pesky dots-in-water issues! It debuts at this Friday's
@UMSSDAN
workshop:
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One of my absolute favorite
#rstats
packages is {leafsync} by
@TimSalabim3
and
@timelyportfolio
. They make it simple to spin up synchronized views of multiple interactive maps to help you explore your spatial data.
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I'm excited to announce pygris, a new
#Python
package to help you work with
@uscensusbureau
geographic datasets (and other resources)!
Read the docs:
Try out pygris on Colab:
Source code:
#pydata
#gischat
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Something that annoys me that I'm sure 99.9999% of people don't care about: that Google Maps uses [lat, long] instead of [long, lat]
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Geodemographic segmentation is a powerful method for understanding your target markets.
Getting started with this method is quicker than you think!
A 🧵 on building a basic geodemographic segmentation workflow in
#rstats
, including linked interactive cluster maps / charts:
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I'm excited to share with all of you that I've been promoted this week to full Professor of Geography at
@TCU
!
My promotion case centered on open-source software contributions - both the packages themselves and a book / articles written about those methods and tools.
I'm…
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Did you know that you can connect R (
#rstats
) and
#Python
to
@ArcGISPro
with far less hassle than you'd think?
Read my blog for an example, and follow here for updates on an upcoming workshop in October to help you get started!
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Writing a book... can take a long time, with years of chapter overhauls and revisions. Today is finally release day of "Analyzing US Census Data"!
You can buy a copy from Routledge () or Amazon () - I appreciate it!
#rstats
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Introducing tidycensus: get
@uscensusbureau
spatial & demographic data in
#rstats
ready for use w/sf & the tidyverse
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The easiest way to add a basemap to your
#rstats
maps is `ggspatial::annotation_map_tile()`. In one line of code, get the right context for `geom_sf()` maps!
Learn how to use basemaps with choropleth, symbol, and dot-density maps in Wednesday's workshop:
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is insanely powerful for creative visualization of big spatial datasets, and the rdeck
#rstats
package makes it very accessible to use.
Shown in the video: all 84,414 Census tracts in the United States visualized in 3D, with extruded heights corresponding…
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A US map in a tweet
#rstats
library(tmap)
tidycensus::get_acs(
geography = "county",
variables = "B01002_001",
geometry = T
) |>
tigris::shift_geometry() |>
tm_shape() +
tm_fill(col = "estimate",
title = "Median age") +
tm_layout(legend.outside = T)
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Did you miss yesterday's workshop on working with 2020 Decennial US Census Data in R (
#rstats
)?
Take a look at the slides from yesterday's presentation here:
You'll find examples of how to use lots of new datasets on block-level demographics, detailed…
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An interactive map in a single tweet:
tidycensus::get_acs(
geography = "tract",
variables = "B19013_001",
state = "OR",
geometry = TRUE
) |>
mapview::mapview(
zcol = "estimate",
= "Median household income"
)
#rstats
#GIS
#demographics
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Geographically weighted regression (GWR) is a method to assess spatial non-stationarity, where relationships b/w an outcome and predictors in a model vary from place to place.
I discuss GWR and its limitations in Ch8 of my book Analyzing US Census Data:
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Want to get started doing
#GIS
in
#Python
?
Here are the books I recommend:
Geocomputation with Python, by
@MichaelDorman84
, Anita Graser,
@jakub_nowosad
,
@robinlovelace
Geographic Data Science with Python, by
@sreyog
,
@darribas
,
@levijohnwolf
…
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In March, I'll be hosting a series of free workshops on
#tidycensus
through
@UMich
/
@UMSSDAN
. You'll learn how to wrangle, visualize, and map
@uscensusbureau
data in
#rstats
and much more. All experience levels are welcome!
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I'm publishing materials for my course on exploratory data analysis & visualization as a
@ProjectJupyter
book: It's an intro to the
@PyData
ecosystem for students new to programming. Chapters can be launched as
@mybinderteam
or
@GoogleColab
notebooks!
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We often think of commercial and open-source
#GIS
software as either / or
As it turns out, connecting
#rstats
and
@ArcGISPro
is easier than you think.
A 🧵 on getting started:
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"Hot-spot" analysis is an effective way to find patterns and areas of focus in complicated spatial datasets.
A 🧵 from Chapter 7 of my book that shows how to do this with Census data and
#rstats
:
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One of my favorite
#rstats
interactive mapping tricks: using the `|` operator in mapview to create a swipe map.
Here - showing the results of the `erase_water()` function in the Seattle area!
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Had to fire up
@rstudio
and check first thing this morning - the 2016-2020 American Community Survey data are live and working in
#rstats
tidycensus! Just use `year = 2020` in `get_acs()` and get your fresh
@uscensusbureau
data today with re-drawn 2020 geographies included!
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tidycensus version 1.0 is now released on CRAN! This major new release includes
@buddyherms
's implementation of a Migration Flows API interface with support for flow mapping: Thanks to all of you who have used tidycensus over the past four years!
#rstats
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A new version of tidycensus is up on CRAN for all you
#rstats
@uscensusbureau
data analysts; the big update is geometry support for all currently available geographies (such as school districts, shown here)
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2.3 million building footprints from
@OvertureMaps
in the Chicago area, visualized in 3D with
#rstats
, , and {rdeck}
Keep an eye out here for a blog post on how to do this...
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Five years after I published the first version, Mapping Immigrant America is now updated to the latest ACS data and
@Mapbox
GL JS:
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Analyzing spatial relationships between datasets - typical performed with dedicated GIS software - is made straightforward in
#rstats
thanks to
@edzerpebesma
's sf package and the
#rspatial
team. Read this thread for examples from Chapter 7 of my book
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Struggling with Census data in your project? There is a better way!
Read my book Analyzing US Census Data for free online (or buy a copy if you are so inclined!)
#rstats
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A new version (v1.6) of
#tidycensus
, your
#rstats
package for working with
@uscensusbureau
demographic / geographic data, is now up on CRAN!
Highlights include:
📊 Full support for the 2022 ACS data, including the 2018-2022 5-year ACS PUMS (just released today!);
📊 Support…
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After getting tenure in 2017, I was disillusioned with writing gated articles that no one reads
I focused instead on
#rstats
📦 dev and writing a book on R which have had exponentially greater impact
Going up for promotion to Full now based on my R work - we'll see how it goes!
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In February and March, I presented three 3-hour webinars on working with
@uscensusbureau
data in
#rstats
with tidycensus in collaboration with
@UMSSDAN
All the materials are free, public, and made available to you as learning resources
Check out the slide decks here:
📈…
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This year, I'm going to be blogging with tips and tricks I commonly use in my data science projects
Today's post: using iterative spatial analysis to produce 100 maps at once, and organizing your results using lists in
#rstats
!
Check it out here:
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In case you find it useful - here's some
#rstats
code to create layered interactive maps of county and tract household income. Using to teach my intro urban studies students about scale
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If I had this mindset three years ago, there would be no tigris (80k downloads from the rstudio mirror) or tidycensus (21k downloads), but maybe an extra couple publications with 15 combined citations
I wonder how many 1000s of hours of some of the brightest minds in science are being wasted creating cool
#rstats
packages that only 10 people will ever use to shave 5 minutes off the time taken to solve a problem and which will stop working with dependency issues 2 years later.
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🎉🎉 The 2021 1-year American Community Survey microdata are out today! 🎉🎉
Use them *right now* in
#rstats
tidycensus with the `get_pums()` function and the arguments `survey = "acs1"` and `year = 2021`
I'll have full 2021 PUMS support (e.g. variable recoding) up on CRAN soon
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Geodemographic segmentation is a powerful tool for understanding your target markets, helping you sift through demographic data and map clusters of similar neighborhoods.
Some applications of geodemographic segmentation include:
🗺 Identifying target neighborhoods for real…
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The
@Mapbox
Isochrone API now incorporates live and historical traffic, and these updates are available to
#rstats
users in the mapboxapi package (new version just submitted to CRAN). Also check out the new ggplot2 basemap functionality thanks to
@elipousson
's contributions!
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22
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Coming home for Game 3 of the NBA Finals, via
#rstats
, the upcoming {mapboxgl} package, and
@Mapbox
's new Standard style
You'll be able to do this yourselves, with very little code, really soon
#OneForDallas
#MavsIn7
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ICYMI: a how-to on visualizing
@OvertureMaps
building footprint data in
#3D
using
#rstats
and
Make incredible visuals like this interactive 3D building map of Manhattan, entirely in R!
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Two new
#rstats
📦 versions now on CRAN: tidycensus 1.2 with new features supporting dot-density mapping, time-series analysis, and improved PUMS access; and mapboxapi 0.3.3, with historical traffic-aware routing and improved ggplot2 basemaps. Download both today!
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One of my favorite tools for visualization of big data is tippecanoe, which converts millions of spatial features (like building footprints) into scale-sensitive vector tiles
You can use tippecanoe in
#rstats
via its wrapper in the mapboxapi package:…
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170
One of my favorite
#rstats
interactive mapping tricks: using the `|` operator in mapview to create a swipe map.
Here - showing the results of the `erase_water()` function in the Seattle area!
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You already know that
#tidycensus
gets you pre-cleaned US Census data ready to analyze and map in
#rstats
.
But did you know it includes other features to make your data science projects easier?
Let's take a tour of a few features in this 🧵:
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The 2020 decennial Census redistricting data are now available in the dev version of tidycensus! Install with `remotes::install_github("walkerke/tidycensus")`, then use `year = 2020` in `get_decennial()` to get started
#rstats
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tidycensus meets
@qgis
: a pipeline for pre-joined
@uscensusbureau
spatial & demographic data in your desktop GIS!
#rstats
#rspatial
#opensource
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New on CRAN: updates to {tidycensus} and {tigris} in
#rstats
that both default to 2018 Census and spatial data. Lots of internal improvements in tidycensus as well largely thanks to
@buddyherms
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tidycensus, my
#rstats
package for getting
@uscensusbureau
data along with simple feature geometry, is now on CRAN:
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When developing
#rstats
Shiny apps with the bslib package, try organizing elements with `card(full_screen = TRUE)`.
This allows you to pop-out elements of your dashboard to full screen, re-sizing your maps or charts if the package (like ggplot2) supports it
Here's an example:
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Thanks to all who attended my
@PennMUSA
#MUSAMasterClass
on Friday! If you couldn't make it, check out my tutorial on my new
#rstats
/
#rspatial
package for using
@Mapbox
tools in R here:
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On the blog: travel-time isochrones in
#Python
with
@Mapbox
and
@geopandas
The methodology outlined in this blog post was used in
@dallasnews
's series on health care access inequalities, "Bleeding Out":
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Many thanks to
@CARTO
for the Spatial Data Scientist of the Year award - this was a huge surprise, I am truly honored!
The Spatial Data Scientist of the Year 2022 was just announced at
#SDSC22
NY & we are very pleased to report Kyle Walker as the winner! 🏆
Kyle is an Associate Professor of Geography & Director of the Center for Urban Studies at
@TCU
! Congratulations
@kyle_e_walker
🎉
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🎉 The 2017-2021 5-year American Community Survey data are now available from
@uscensusbureau
! 🎉
Start analyzing and mapping the new data *right now* with tidycensus &
#rstats
using the argument `year = 2021`
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