Help for package corona

Title:

Coronavirus ('Rona') Data Exploration

Version:

0.3.0

Depends:

R (≥ 3.5.0), plyr

Imports:

gganimate, ggplot2, gridExtra, qicharts2, reshape2

Maintainer:

Jo van Schalkwyk <jvanschalkwyk@gmail.com>

Description:

Manipulate and view coronavirus data and other societally relevant data at a basic level.

License:

GPL-3

Encoding:

UTF-8

LazyData:

true

RoxygenNote:

7.1.0

NeedsCompilation:

Packaged:

2020-09-17 01:16:56 UTC; jo

Author:

Jo van Schalkwyk

[aut, cre]

Repository:

CRAN

Date/Publication:

2020-09-23 09:30:03 UTC

Allometric scaling data.

Description

Used to introduce power laws.

Usage

allo

Format

A data frame with 455 rows.

Species
Mass
Temperature
MR: Metabolic rate
AvgMass
Q10SMR
Reference

Source

https://royalsocietypublishing.org/doi/suppl/10.1098/rsbl.2005.0378

Citymapper data.

Description

These are a bit unusual in that each country has a column.

Usage

citymap

Format

A data frame with 108 rows.

Date
Australia
Austria
Belgium
Brazil
Canada
Denmark
France
Germany
Italy
Japan
Mexico
Netherlands
Portugal
Russia
Singapore
South.Korea
Spain
Sweden
Turkey
United.Kingdom
United.States

Source

https://citymapper.com/cmi/about

Country data from Our World In Data.

Description

Country data from Our World In Data.

Usage

cntry

Format

A data frame with 17,013 rows (current)

iso_code: ISO 3-letter country code
location: Text name of country
population
continent
population_density
median_age
aged_65_older
aged_70_older
gdp_per_capita
extreme_poverty
cvd_death_rate
diabetes_prevalence
female_smokers
male_smokers
handwashing_facilities
hospital_beds_per_thousand
life_expectancy
alias: Alias country name, shorter
lowstart: Start of 'summer' viral respiratory low
lowend: End of respiratory low. Sketchy at present.

Source

https://github.com/owid/covid-19-data/tree/master/public/data and https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4847850/

Basic setup of corona (Nanny Rona) R program

Description

Try ?corona for help. For most functions, saying pdf=TRUE will write a PDF to images/. If you wish to print to PDF, you need to setwd() to a directory that contains an images/ directory that can be written to, or this will fail. Individual examples are also available. Try e.g. ?corona_rabbits or ?corona_country The results of corona_life() will depend on how your system handles animated GIF files.

Usage

corona()

Examples


    corona_rabbits ( )
    corona_monty ( )
    corona_country ('France') 
    corona_vienna ( ) 
    corona_totals ( ) 
    country_dead ( ) 
    corona_converge ( )
    corona_metabolism ( ) 
    corona_citymap ( ) 
    corona_dowjones ( )

Generate all Figures

Description

For the book 'Rona' (printing to PDF) work through and generate PDFs for all examples.

Usage

corona_all()

Plot citymapper data against COVID-19 diagnoses, over time

Description

Requires ggplot2, plyr and the data frames lock, owid, citymap. Multiple, select frames are plotted.

Usage

corona_citymap(pdf = FALSE, FewCities = NULL, cols = 4)

Arguments

pdf

= TRUE writes to PDF, default FALSE

FewCities

a c() list of city names from the city options. Default is all.

cols

Number of columns in output, default is 4

Examples

corona_citymap(cols=4);

Create various statistical distributions

Description

Build a normal or log-normal distribution from simple components. Large numbers e.g. n=1e6 will take some time to run.

Usage

corona_converge(
  n = 1e+05,
  method = "add",
  runs = 7,
  pdf = FALSE,
  xscale = 1,
  bins = 64,
  log = FALSE
)

Arguments

n

is the number of samples

method

is either 'multiply' or 'add'

runs

number of iterations (default 7)

pdf

defaults to FALSE

xscale

a scaling factor, can use values < 1.0 to magnify (x) e.g. 0.4

bins

defaults to 64

log

take logarithm of values (for 'multiply')

Examples

corona_converge( n=10000, method='multiply', xscale=0.4, bins=128, runs=5 )

Plot time course of coronavirus case incidence and deaths for one country

Description

The daily case rate is also shown as a smoothed curve. The smoothed death incidence is MULTIPLIED x5 to highlight its relationship to the incidence curve. See grown-up documentation (LyX)

Usage

corona_country(country, pdf = FALSE, smooth = TRUE, deaths = TRUE)

Arguments

country

: no default

pdf

: defaults to FALSE. If TRUE, writes to country_name_new.pdf i.e. 'new.pdf' is appended to formal country name. If the country name contains spaces ' ' they are changed to underscores ''

smooth

: default TRUE show smoothed (red) curve

deaths

: default TRUE show deaths

Examples

corona_country('United States'); 
corona_country('Taiwan');

Plot Dow-Jones Closing data

Description

Assumes the existence of the data frame djia, part of corona data.

Usage

corona_dowjones(pdf = FALSE)

Arguments

pdf

: will not print to PDF

Examples

corona_dowjones ( )

Animate Conway's Game of Life

Description

The canvas (arena) wraps around vertically and horizontally! Execution will take some time. Results will be viewed differently depending on your system's default viewer for animated GIF files.

Usage

corona_life(
  pattern = "soup",
  side = 50,
  steps = 100,
  density = 0.3,
  filename = NULL,
  wrap = TRUE,
  fps = 20,
  pause = 10
)

Arguments

pattern

Defaults to 'soup' but there are many other well-known options: blinker ttetromino rpentomino toad beehive beacon clock pulsar pentadecathlon galaxy spaceship glidergun piheptomino switchengine conway acorn rabbits boring static patterns: block snake eater

side

The number of elements on the area's side (width or height)

steps

The number of frames

density

0.0–1 The density of the initial, random items ('soup')

filename

writes to this file name e.g. foo.gif (NULL for current GIF device)

wrap

Wrap around

fps

Frames per second

pause

Initial pause

Examples

## Not run: 
corona_life( filename='animation.gif', side=50, steps=500, density=0.2 ) 
corona_life( side=100, steps=1000, pattern='rpentomino', wrap=FALSE ) 
corona_life( side=30, steps=120, pattern='spaceship' ) 
corona_life( side=100, steps=400, pattern='switchengine' ) 
corona_life( side=20, steps=30, pattern='clock' ) 
corona_life( side=20, steps=30, pattern='galaxy' ) 
corona_life( side=100, steps=200, pattern='glidergun' ) 
corona_life( side=45, steps=130, pattern='conway', fps=8, pause=40)

## End(Not run)

Draw multiple smoothed graphs of new daily cases, with lockdown date, if present

Description

By default limited to countries with population > 4M, and over 200 cases. This may take over 5s to run, depending on your hardware.

Usage

corona_lockdown(
  pdf = FALSE,
  minpeople = 4e+06,
  mincases = 200,
  cols = 7,
  striptextsize = 10,
  textsize = 10,
  legendx = 0.94,
  legendy = 0.02
)

Arguments

pdf

print to PDF

minpeople

Minimum population for the country

mincases

Minimum number of COVID-19 cases

cols

Number of columns to display, default = 7

striptextsize

size of text in country names

textsize

Size of text header

legendx

X position of legend

legendy

Y position of legend

Examples

## Not run: 
corona_lockdown( cols=14 )  

## End(Not run)

Allometric scaling of metabolic rates

Description

Log-log plot of mammalian weights (grams) against metabolic rates. The PDF file is allometry.pdf.

Usage

corona_metabolism(pdf = FALSE, base = 10)

Arguments

pdf

will not print to PDF

base

base for logarithms, default 10

Examples

corona_metabolism ( )

A Monte Carlo simulation of the Monty Hall problem

Description

A Monte Carlo simulation of the Monty Hall problem

Usage

corona_monty(runs = 100)

Arguments

runs

specifies the number of parallel simulations, default=100.

Examples

corona_monty ( runs=10000 )

Demonstrate (graph) exponential growth of rabbit population:

Description

For finer details, see the LyX/PDF documentation.

Usage

corona_rabbits(topyear = 6, pdf = FALSE)

Arguments

topyear

is last year, defaults to 6

pdf

Will not print to PDF if FALSE (the default)

Examples

corona_rabbits( topyear=10)

Plot total cases over time for a selected country.

Description

Defaults to Italy, as this was our demonstration. Add a linear regression by specifying smooth=TRUE.

Usage

corona_totals(
  country = "Italy",
  daystart = 60,
  dayend = 76,
  pdf = FALSE,
  log = FALSE,
  smooth = FALSE,
  prefix = ""
)

Arguments

country

Text name of country (in owid frame)

daystart

first day

dayend

last day to plot

pdf

TRUE will print value

log

TRUE will take base 10 logarithm of y-axis values

smooth

TRUE will try to fit linear model (use with logarithm)

prefix

defaults to ”; a text value will be prefixed to PDF name after country_ name.

Examples

corona_totals( country='Italy', daystart=60, dayend=76, log=TRUE, smooth=TRUE ) 
corona_totals(country='United Kingdom', log=TRUE, smooth=TRUE)

Plot Google Trends data for searches involving the word 'coronavirus'.

Description

Just plot the lines.

Usage

corona_trends(pdf = FALSE)

Arguments

pdf

default FALSE will not print the PDF file

Examples

corona_trends ( )

Plot Semmelweis' original data from Vienna.

Description

First simply 'plots the dots'; subsequently draws a run chart with a transition at the point where he instituted hand-washing.

Usage

corona_vienna(pdf = FALSE)

Arguments

pdf

default FALSE will not print the two PDF files: semmelweis_plot.pdf semmelweis_run.pdf

Examples

corona_vienna ( )

Plot country deaths by week, with various adjustments:

Description

Assumes the existence of the data frame stmf containing relevant iso_codes for countries. The unusual codes GBRTENW and GBR_SCO represent England+Wales and Scotland. You can obtain a list of countries by country_dead('?'), forcing a diagnostic error!

Usage

country_dead(country = "England+Wales", pdf = FALSE, save = FALSE)

Arguments

country

Country name

pdf

default FALSE will not print to PDF

save

Do we save the data as a CSV

Details

The columns in the frame stmf are just 'iso_code', 'Year', 'Week', and 'Deaths'.

Draws three graphs:

Raw data with a linear regression line, over n years;
Data with secular adjustment;
Data adjusted for a 'summer baseline' using the "other n years of data" after secular adjustment.

Examples

country_dead( 'New Zealand' )

Historical Dow Jones Industrial Average prices.

Description

Historical Dow Jones Industrial Average prices.

Usage

djia

Format

A data frame with 110 rows (current)

Date: Date of transaction—excludes weekends etc
Open: Opening average
High: Maximum over the day
Low: Minimum
Close: Closing price

Source

https://www.wsj.com/market-data/quotes/index/DJIA/historical-prices

Google trends search for 'coronavirus'.

Description

Google trends search for 'coronavirus'.

Usage

gt

Format

A data frame with 155 rows (current)

Date: Date in format YYYY-MM-DD
Day
coronavirus: Coronavirus 'interest' as percentage of maximum count

Source

https://trends.google.com/trends/

The game of life.

Description

This specifies initial conditions, using a clumsy storage format as below.

Usage

life

Format

A data frame with 213 rows.

x: x co-ordinate of an active cell
y: y co-ordinate
pattern: A name like 'blinker' — will be common to several rows, specifying a Game of Life pattern

Source

(internal generation)

Approximate dates of full lockdown in various countries.

Description

Approximate dates of full lockdown in various countries.

Usage

lock

Format

A data frame with 110 rows (current)

iso_code: Country
Lockdown: Date of lockdown YYYY-MM-DD
nature: Text description: national | partial | advice | empty(none)

Source

Various data sources.

Wide-ranging data from Our World In Data. I only use a tiny part.

Description

Wide-ranging data from Our World In Data. I only use a tiny part.

Usage

owid

Format

A data frame with 17,013 rows (current)

iso_code: ISO 3-letter country code
date: Date for this row of data
total_cases: total cases to date
new_cases: new cases
total_deaths: eponymous
new_deaths
total_tests: Recorded tests in toto
new_tests: Eponymous
tests_units
stringency_index: How severe the lockdown was

Source

https://github.com/owid/covid-19-data/tree/master/public/data

Deaths, by week, for various countries.

Description

Deaths, by week, for various countries.

Usage

stmf

Format

A data frame with 22678 rows.

iso_code: Normally a 3-character country code e.g. NZL, AUT. England+Wales=GBRTENW, Scotland=GBR_SCO
Year: YYYY
Week: Week within that year, 1=1st
Deaths: Number of deaths in that week
X

Source

https://www.ons.gov.uk/peoplepopulationandcommunity/birthsdeathsandmarriages/deaths/datasets/weeklyprovisionalfiguresondeathsregisteredinenglandandwales https://www.stats.govt.nz/experimental/covid-19-data-portal https://www.scb.se/en/finding-statistics/statistics-by-subject-area/population/population-composition/population-statistics/#_Tablesandgraphs and also (registration now required) https://www.mortality.org/

Semmelweis' data on Deaths of parturients in Vienna

Description

Semmelweis' data on Deaths of parturients in Vienna

Usage

vienna

Format

A data frame with 98 rows

date: Date of the start of each month YYYY-MM-01
births: Number of births during that month
deaths: Number of maternal deaths during that month

Source

https://en.wikipedia.org/wiki/Historical_mortality_rates_of_puerperal_fever