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---
title: "💻 <i>R</i> Workshop 💻"
subtitle: "GIS DAY 2020<br> Mapping Covid-19 in England using R and Leaflet"
author: "Luca Valnegri"
output:
xaringan::moon_reader:
css: ["default", "metropolis", "metropolis-fonts", "https://datamaps.uk/assets/datamaps/xari.css"]
lib_dir: libs
nature:
highlightStyle: github
highlightLanguage: ["r"]
highlightLines: true
countIncrementalSlides: false
ratio: "16:10"
---
layout: true
<div class="datamaps-header">
<img class="logo" src="https://datamaps.uk/assets/datamaps/logo_white.png"/>
</div>
<div class="datamaps-footer">
<span> ©2020 datamaps.uk <br>
<a href = "https://github.com/lvalnegri/workshop-gis_day_2020"> GitHub Repository </a>
</span>
</div>
---
# Learning outcomes
- be able to use *R* and *RStudio* to collect, read, manipulate, subsetting and save spatial and non-spatial data
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- join spatial data to attribute data
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- customize classification methods, and choosing the right colour *palette*
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- some basic spatial operations, like reprojection, simplifying, dissolving, and point in polygon analysis
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- know how to design and create both *dotmaps* and *choropleths*
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- be able to add labels, popups, and modals in Shiny apps that can also show tables and graphs
---
# Packages [1] Data Collection and Wrangling
- [data.table](https://rdatatable.gitlab.io/data.table/)
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- [openxlsx](https://ycphs.github.io/openxlsx/index.html) to easily read *Excel* files
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- the [*tidyverse*](https://www.tidyverse.org/) collection:
- [readr](https://readr.tidyverse.org/) read *csv* files
- [readxl](https://readr.tidyverse.org/) read *Excel* files
- [dplyr](https://dplyr.tidyverse.org/) data manipulation
- [tidyr](https://tidyr.tidyverse.org/) data reshaping
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- [magrittr](https://cran.r-project.org/web/packages/magrittr/) for the *pipe* operator `%>%`: `f(x,y) => x %>% f(y)`
---
# Packages [2] Spatial Tools
- [rgdal](https://cloud.r-project.org/web/packages/rgdal/) read/save vector-based spatial data (*boundaries*) in various format (*shapefile*, *GeoJSON*, *kml*, *MapInfo*)
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- [sp](https://cloud.r-project.org/web/packages/sp/) to store the spatial objects as a specific *R* class
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# Packages [3] Data Display
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# Packages [4] Data Visualization: Static
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# Packages [5] Data Visualization: Interactive
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# Packages [6] Data Presentation and Deployment
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# Workflow
- Install packages
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- Data Collection and Wrangling
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- Data Display and Visualization
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- Dotmaps for Trusts (daily deaths)
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- Choropleths for LTLA (daily cases) and MSOA (weekly cases)
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- Bivariate Choropleths by syncing or by ternary color (total cases by MSOA + IMD / income / ...)
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- Shiny app [add time series on mouse click for any of the above]
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- Automating data collection
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# UK Geographies
- *PCU* Postcode Units
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- *OA*, *LSOA*, and *MSOA* Small Areas from the Census Hierarchy
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- *LTLA*, *UTLA* and *RGN* Administrative Hierarchy
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- *CCG* and *STP* NHS Hierarchy
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# Data Collection: Ancillary Data
- [MSOA House of Commons *intelligible* Names](https://visual.parliament.uk/msoanames)
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- [MSOA => LTLA => UTLA => RGN APR-2020](https://coronavirus.data.gov.uk/details/about-data#cases-by-middle-super-output-area-msoa)
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- [OA => LSOA => MSOA 2011](https://geoportal.statistics.gov.uk/datasets/output-area-to-lower-layer-super-output-area-to-middle-layer-super-output-area-to-local-authority-district-december-2011-lookup-in-england-and-wales)
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- [LSOA => CCG => STP => CAL APR-2020](https://geoportal.statistics.gov.uk/datasets/lsoa-2011-to-clinical-commissioning-groups-to-sustainability-and-transformation-partnerships-april-2020-lookup-in-england)
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- [ONS Postcode Directory AUG-2020](https://geoportal.statistics.gov.uk/datasets/ons-postcode-directory-august-2020)
---
# Data Collection: GeoDemographics
- [Population by LSOA + MSOA and Sex + Age](https://www.ons.gov.uk/peoplepopulationandcommunity/populationandmigration/populationestimates/datasets/middlesuperoutputareamidyearpopulationestimates)
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- [Index of Multiple Deprivation by LSOA](https://www.gov.uk/government/statistics/english-indices-of-deprivation-2019)
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- [Food Shops Locations by PCU](https://ratings.food.gov.uk/open-data/en-GB) See [my other github repository] to learn how to collect data related to food shops
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- [Household Disposable Income by MSOA](https://www.ons.gov.uk/employmentandlabourmarket/peopleinwork/earningsandworkinghours/datasets/smallareaincomeestimatesformiddlelayersuperoutputareasenglandandwales)
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- [Median House Prices by MSOA](https://www.ons.gov.uk/peoplepopulationandcommunity/housing/datasets/hpssadataset2medianhousepricebymsoaquarterlyrollingyear)
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- [Electricity and Gas Consumption](https://www.gov.uk/government/statistics/lower-and-middle-super-output-areas-gas-consumption)
---
# Data Collection: Covid-19 Data
- [Covid Cases by LTLA](https://coronavirus.data.gov.uk/details/about-data#legacy-csv-downloads)
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- [Covid Cases by Age Class](https://coronavirus.data.gov.uk/details/about-data#cases-by-age)
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- [Covid Cases by MSOA](https://coronavirus.data.gov.uk/details/about-data#cases-by-middle-super-output-area-msoa)
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- [Covid Deaths by NHS Trust](https://www.england.nhs.uk/statistics/statistical-work-areas/covid-19-daily-deaths/)
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- [Hospital Admissions and Bed Occupancy by NHS Trust](https://www.england.nhs.uk/statistics/statistical-work-areas/covid-19-hospital-activity/)
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- [Covid Symptoms (NHS Pathways Calls and Online) by CCG and Sex + Age](https://digital.nhs.uk/data-and-information/publications/statistical/mi-potential-covid-19-symptoms-reported-through-nhs-pathways-and-111-online/latest/)
---
# Spatial Data Representation
- In general, there are two main family of spatial data, each dealt in its own way
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- Vector: point, lines, polygons
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- Raster: regular grids
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In the current session, we are going to deal only with vector data: Points and Polygons
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- Normally, in spatial data analysis each spatial object has a dataset attached to it, storing data related to each of its components
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# R as a GIS
- Using the *sp* packages, Points and Polygons are represented by the classes:
- `SpatialPointsDataFrame`
- `SpatialPolygonsDataFrame`
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- Both objects are partitioned in *slots*, accessed using the `@` operator
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- *Points* contains a `coords` slot that stores the coordinates of each point,
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- *Polygons* contains a `polygons` slot that stores, among other information, the coordinates related to each polygon
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# R as a GIS
Other slots common to both classes are:
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- `data` a dataframe that stores the data connected to each entity
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- `bbox` the coordinates for the *bounding box*, the minimum square box that can include all the entities.
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- `proj4string` a string that define the *projection* and *coordinate reference system* (CRS)
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It can be written in the form `+init=epsg:x` where `x` is a code that define
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# R as a GIS
- When using web application, it is customary to use the so called *WGS84*, [World Geodetic System 1984](https://epsg.io/4326), identified by `epsg:4326`.
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- Its unit is the *degree*, so it can't be used to measure areas or lengths.
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- Great Britan: [British National Grid, OSGB_1936](https://epsg.io/27700) with `epsg:27700`
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- Ireland: [Irish Grid, GCS_TM65](https://epsg.io/29902) with `epsg:29902`
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# How to read points
- Various UK geographies can be downloaded from the GeoPortal
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- You can also find additional
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# Summary
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# Credits
- [Gis Day website](https://www.gisday.com/en-us/overview)
- Contains Public Health England data © Crown copyright and database right 2020
- Contains Ordnance Survey data © Crown copyright and database right 2020
- Office for National Statistics licensed under the Open Government Licence v.3.0
- Contains MSOA names © Open Parliament copyright and database right 2020
- Contains Royal Mail data © Royal Mail copyright and database right 2020
---
# Resources
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- [Cheat Sheet]()
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- [Reference]()
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- [RStudio Tutorials]()
---
# Thank You!
- [`r icon::fa("github")` lvalnegri](https://github.com/lvalnegri)
- [`r icon::fa("twitter")` @datamaps](https://twitter.com/datamaps)
- [`r icon::fa("linkedin")` Luca Valnegri](https://www.linkedin.com/in/lucavalnegri)