| Type: | Package |
| Title: | Load and Analyze Live Data from the COVID-19 Pandemic |
| Version: | 2.1.3.3 |
| Date: | 2023-10-14 |
| Author: | Marcelo Ponce [aut, cre], Amit Sandhel [ctb] |
| Maintainer: | Marcelo Ponce <m.ponce@utoronto.ca> |
| Description: | Load and analyze updated time series worldwide data of reported cases for the Novel Coronavirus Disease (COVID-19) from different sources, including the Johns Hopkins University Center for Systems Science and Engineering (JHU CSSE) data repository https://github.com/CSSEGISandData/COVID-19, "Our World in Data" https://github.com/owid/ among several others. The datasets reporting the COVID-19 cases are available in two main modalities, as a time series sequences and aggregated data for the last day with greater spatial resolution. Several analysis, visualization and modelling functions are available in the package that will allow the user to compute and visualize total number of cases, total number of changes and growth rate globally or for an specific geographical location, while at the same time generating models using these trends; generate interactive visualizations and generate Susceptible-Infected-Recovered (SIR) model for the disease spread. |
| Imports: | readxl, ape, rentrez, curl, plotly, htmlwidgets, deSolve, gplots, pheatmap, shiny, shinydashboard, shinycssloaders, DT, dplyr, collapsibleTree |
| Suggests: | knitr, devtools, roxygen2, markdown, rmarkdown, testthat |
| License: | GPL-2 | GPL-3 [expanded from: GPL (≥ 2)] |
| URL: | https://mponce0.github.io/covid19.analytics/ |
| BugReports: | https://github.com/mponce0/covid19.analytics/issues |
| RoxygenNote: | 7.1.0 |
| VignetteBuilder: | knitr |
| NeedsCompilation: | no |
| Packaged: | 2023-10-15 05:36:02 UTC; marcelo |
| Repository: | CRAN |
| Date/Publication: | 2023-10-15 21:50:11 UTC |
function to define the OWID repos URLs
Description
function to define the OWID repos URLs
Usage
OWID.repos(tgt)
Arguments
tgt |
target case: 'VAC.global','VAC.us','VAC.country','VAC.locations', 'testing', 'testing.details' |
Value
URL
function to obtain sequencing data grom NCBI Reference: https://www.ncbi.nlm.nih.gov/nuccore/NC_045512.2
Description
function to obtain sequencing data grom NCBI Reference: https://www.ncbi.nlm.nih.gov/nuccore/NC_045512.2
Usage
X.covid19.genomic.data(graphics.ON = TRUE)
Arguments
graphics.ON |
flag to activate/deactivate graphical output |
Examples
# obtain covid19's genomic data
covid19.gen.seq <- covid19.genomic.data()
# display the actual RNA seq
covid19.gen.seq$NC_045512.2
function to query NCBI database servers using the "rentrex" library
Description
function to query NCBI database servers using the "rentrex" library
Usage
avecRentrez(
DB = "nucleotide",
max.nr.recs = 20000,
chunkSize = 100,
accOnly = TRUE
)
Arguments
DB |
database |
max.nr.recs |
maximun number of records to retrieve, there are limitations in the fns and server sides |
chunkSize |
number of records to retrieve at once |
accOnly |
boolean indicator for getting only accession codes or whole records |
bad argument error handling function
Description
bad argument error handling function
Usage
badOption(arg)
Arguments
arg |
argument choosen |
function to obtain FASTA seqs for nucleotides or proteins from SARS-CoV-2
Description
function to obtain FASTA seqs for nucleotides or proteins from SARS-CoV-2
Usage
c19.NP_fasta.data(src = "repo", target = "nucleotide")
Arguments
src |
origin for the data source: "livedata" OR "repo" |
target |
"nucleotide", "protein" or "codingRegion" |
function to obtain data for nucleotides or proteins from SARS-CoV-2
Description
function to obtain data for nucleotides or proteins from SARS-CoV-2
Usage
c19.NPs.data(
src = "livedata",
DB = "nucleotide",
max.nr.recs = NULL,
accOnly = TRUE
)
Arguments
src |
origin for the data source: "livedata", "repo", "local" |
DB |
database |
max.nr.recs |
maximun number of records to retrieve, there are limitations in the fns and server sides |
accOnly |
boolean indicator for getting only accession codes or whole records |
function to read data from OWID repos
Description
function to read data from OWID repos
Usage
c19.OWID.data(repo, disclaimer = TRUE)
Arguments
repo |
URL for reading the data |
disclaimer |
indicate whether the information about the source of the data is disclosed |
Value
datafram object
function to obtain FASTA sequence of the SARS-CoV-2 virus
Description
function to obtain FASTA sequence of the SARS-CoV-2 virus
Usage
c19.fasta.data(src = "livedata")
Arguments
src |
argument to indicate where the data is being retrieved from |
function to obtain genomic data from SARS-CoV-2019
Description
function to obtain genomic data from SARS-CoV-2019
Usage
c19.genomic.data(src = "livedata", accOnly = TRUE)
Arguments
src |
argument to indicate what sources are going to be used for retrieving the data: "livedata", "repo" or "local" 'livedata' will access NCBI servers to acquire the latest possible data, this may incur in significant longer times 'repo' will access an updated replica of the data from a github repository (faster but not necessarily upto the latest udpates) 'local' will access previously archived records within teh package (fastest but not updated) |
accOnly |
boolean indicator for getting only accession codes or whole records |
Value
a list containing reference genome, annotation data, nucleotides, proteins and list of SRA runs
function to obtain "Tree of complete SARS-CoV-2 Sequences as obtained from NCBI"
Description
function to obtain "Tree of complete SARS-CoV-2 Sequences as obtained from NCBI"
Usage
c19.ptree.data(src = "livedata")
Arguments
src |
argument to indicate where the data is being retrieved from |
function to obtain sequencing data grom NCBI Reference: https://www.ncbi.nlm.nih.gov/nuccore/NC_045512.2
Description
function to obtain sequencing data grom NCBI Reference: https://www.ncbi.nlm.nih.gov/nuccore/NC_045512.2
Usage
c19.refGenome.data(src = "livedata", graphics.ON = TRUE)
Arguments
src |
data origin source: 'livedata', 'repo', 'local' |
graphics.ON |
flag to activate/deactivate graphical output |
Examples
## Not run:
# obtain covid19's genomic data
covid19.gen.seq <- c19.refGenome.data()
# display the actual RNA seq
covid19.gen.seq$NC_045512.2
## End(Not run)
function to check the geographical location
Description
function to check the geographical location
Usage
checkGeoLoc(data, geo.loc = NULL)
Arguments
data |
data.frame with data from covid19 |
geo.loc |
list of locations |
Value
list of capitalized locations within the data
auxiliary function to check whether a dataset is composed of time series data
Description
auxiliary function to check whether a dataset is composed of time series data
Usage
chk.TS.data(data, xtp = FALSE)
Arguments
data |
data set to consider |
xtp |
indicator whether to stop the program if data is not time series |
Value
a boolean indicator whether the data contains time series values or not
function to draw confidence bands, using generalized moving averages/sds
Description
importFrom grDevices rgb importFrom graphics lines polygon importFrom stats sd
Usage
confBand(
x,
y,
x0,
x1,
y0,
y1,
windowsNbr = 10,
period = ceiling(length(y)/windowsNbr),
lcolour = "gray",
ltype = 4,
lwidth = 2,
filling = TRUE
)
function that determines whether there are consistency issues within the data, such as, anomalies in the cumulative quantities of the data as reported by JHU/CCSEGIS
Description
function that determines whether there are consistency issues within the data, such as, anomalies in the cumulative quantities of the data as reported by JHU/CCSEGIS
Usage
consistency.check(
data,
n0 = 5,
nf = ncol(data),
datasetName = "",
disclose = FALSE,
details = TRUE
)
Arguments
data |
dataset to analyze |
n0 |
column where the cumulative data begins |
nf |
column where the cumulative data ends |
datasetName |
optional argument to display the name of the dataset |
disclose |
boolean flag to indicate whether index of problematic entries are returned |
details |
optional argument to specify whether to show details about the records where inconsistencies were detected |
function to import data for Canada as reported by Health Canada https://health-infobase.canada.ca/src/data/covidLive/covid19.csv
Description
function to import data for Canada as reported by Health Canada https://health-infobase.canada.ca/src/data/covidLive/covid19.csv
Usage
covid19.Canada.data(
data.fmt = "TS",
local.data = FALSE,
debrief = FALSE,
acknowledge = FALSE
)
Arguments
data.fmt |
"TS" for TimeSeries of cumulative cases or "original" for the data as original reported |
local.data |
boolean flag to indicate whether the data will be read from the local repo, in case of connectivity issues or data integrity |
debrief |
boolean specifying whether information about the read data is going to be displayed in screen |
acknowledge |
boolean flag to indicate that the user acknowledges where the data is coming from. If FALSE, display data acquisition messages. |
Value
a dataframe with the latest data reported by "OpenData Toronto" for the city of Toronto, ON - Canada
function to read "live" data as reported by JHU's CCSE repository
Description
function to read "live" data as reported by JHU's CCSE repository
Usage
covid19.JHU.data(
case = "aggregated",
local.data = FALSE,
debrief = FALSE,
acknowledge = FALSE
)
Arguments
case |
a string indicating the category of the data, possible values are: "aggregated" : latest number of cases *aggregated* by country, "ts-confirmed" : time data of confirmed cases, "ts-deaths" : time series data of fatal cases, "ts-recovered" : time series data of recovered cases, "ts-ALL" : all time series data combined, "ts-confirmed-US" : time series data of confirmed cases for the United States, "ts-deaths-US" : time series data of fatal cases for the United States, "ts-dep-confirmed" : time series data of confirmed cases as originally reported (depricated), "ts-dep-deaths" : time series data of deaths as originally reported (depricated), "ts-dep-recovered" : time series data of recovered cases as originally reported (depricated), "ALL": all of the above "Toronto" : data for the City of Toronto, ON - Canada |
local.data |
boolean flag to indicate whether the data will be read from the local repo, in case of connectivity issues or data integrity |
debrief |
boolean specifying whether information about the read data is going to be displayed in screen |
acknowledge |
boolean flag to indicate that the user acknowledges where the data is coming from. If FALSE, display data acquisition messages. |
Value
a dataframe (or a list in the case of "ALL") with the daily worlwide indicated type of data per country/region/city
Examples
# reads all possible datastest, returnin a list
covid19.all.datasets <- covid19.data("ALL")
# reads the latest aggregated data
covid19.ALL.agg.cases <- covid19.data("aggregated")
# reads time series data for casualities
covid19.TS.deaths <- covid19.data("ts-deaths")
function to import data from the city of Toronto, ON - Canada as reported by the City of Toronto OR Open Data Toronto
Description
function to import data from the city of Toronto, ON - Canada as reported by the City of Toronto OR Open Data Toronto
Usage
covid19.Toronto.data(
origin = "OD",
data.fmt = "TS",
local.data = FALSE,
debrief = FALSE,
OLD.fmt = FALSE,
acknowledge = FALSE
)
Arguments
origin |
select between the "City of Toronto" ('city') OR "Open Data Toronto" ('OD') |
data.fmt |
"TS" for TimeSeries of cumulative cases or "original" for the data as reported in the google-document with multiple sheets |
local.data |
boolean flag to indicate whether the data will be read from the local repo, in case of connectivity issues or data integrity |
debrief |
boolean specifying whether information about the read data is going to be displayed in screen |
OLD.fmt |
boolean flag to specify if the data is being read in an old format |
acknowledge |
boolean flag to indicate that the user acknowledges where the data is coming from. If FALSE, display data acquisition messages. |
Value
a dataframe (or a list in the case of "original") with the latest data reported for the city of Toronto, ON - Canada
function to import data from the city of Toronto, ON - Canada as reported by Open Data Toronto https://open.toronto.ca/dataset/covid-19-cases-in-toronto/ This dataset is updated WEEKLY.
Description
function to import data from the city of Toronto, ON - Canada as reported by Open Data Toronto https://open.toronto.ca/dataset/covid-19-cases-in-toronto/ This dataset is updated WEEKLY.
Usage
covid19.Toronto_OD.data(
data.fmt = "TS",
local.data = FALSE,
debrief = FALSE,
acknowledge = FALSE
)
Arguments
data.fmt |
"TS" for TimeSeries of cumulative cases or "original" for the data as original reported |
local.data |
boolean flag to indicate whether the data will be read from the local repo, in case of connectivity issues or data integrity |
debrief |
boolean specifying whether information about the read data is going to be displayed in screen |
acknowledge |
boolean flag to indicate that the user acknowledges where the data is coming from. If FALSE, display data acquisition messages. |
Value
a dataframe with the latest data reported by "OpenData Toronto" for the city of Toronto, ON - Canada
function to import data from the city of Toronto, ON - Canada as reported by the City of Toronto https://www.toronto.ca/home/covid-19/covid-19-pandemic-data/
Description
function to import data from the city of Toronto, ON - Canada as reported by the City of Toronto https://www.toronto.ca/home/covid-19/covid-19-pandemic-data/
Usage
covid19.Toronto_city.data(
data.fmt = "TS",
local.data = FALSE,
debrief = FALSE,
OLD.fmt = FALSE,
acknowledge = FALSE
)
Arguments
data.fmt |
"TS" for TimeSeries of cumulative cases or "original" for the data as reported in the google-document with multiple sheets |
local.data |
boolean flag to indicate whether the data will be read from the local repo, in case of connectivity issues or data integrity |
debrief |
boolean specifying whether information about the read data is going to be displayed in screen |
OLD.fmt |
boolean flag to specify if the data is being read in an old format |
acknowledge |
boolean flag to indicate that the user acknowledges where the data is coming from. If FALSE, display data acquisition messages. |
Value
a dataframe (or a list in the case of "original") with the latest data reported for the city of Toronto, ON - Canada
function to read CSV from URLs or local replicas
Description
function to read CSV from URLs or local replicas
Usage
covid19.URL_csv.data(
local.data = FALSE,
acknowledge = FALSE,
srcURL = "",
srcName = "",
locFileName = NA,
locVarName = NA
)
Arguments
local.data |
boolean flag to indicate whether the data will be read from the local repo, in case of connectivity issues or data integrity |
acknowledge |
boolean flag to indicate that the user acknowledges where the data is coming from. If FALSE, display data acquisition messages. |
srcURL |
URL from where to obtain the data |
srcName |
name of the source |
locFileName |
name of the file to read from local repo |
locVarName |
name of the variable loaded from local file |
Value
data as oriignally obtained from the URL src
function to read the TimeSeries US detailed data
Description
function to read the TimeSeries US detailed data
Usage
covid19.US.data(local.data = FALSE, debrief = FALSE, acknowledge = FALSE)
Arguments
local.data |
boolean flag to indicate whether the data will be read from the local repo, in case of connectivity issues or data integrity |
debrief |
boolean specifying whether information about the read data is going to be displayed in screen |
acknowledge |
boolean flag to indicate that the user acknowledges where the data is coming from. If FALSE, display data acquisition messages. |
Value
TimeSeries dataframe with data for the US
function to read "live" data from reported covid19 cases
Description
function to read "live" data from reported covid19 cases
Usage
covid19.data(
case = "aggregated",
local.data = FALSE,
debrief = FALSE,
acknowledge = FALSE
)
Arguments
case |
a string indicating the category of the data, possible values are: "aggregated" : latest number of cases *aggregated* by country, "ts-confirmed" : time data of confirmed cases, "ts-deaths" : time series data of fatal cases, "ts-recovered" : time series data of recovered cases, "ts-ALL" : all time series data combined, "ts-confirmed-US" : time series data of confirmed cases for the United States, "ts-deaths-US" : time series data of fatal cases for the United States, "ts-dep-confirmed" : time series data of confirmed cases as originally reported (depricated), "ts-dep-deaths" : time series data of deaths as originally reported (depricated), "ts-dep-recovered" : time series data of recovered cases as originally reported (depricated), "ALL": all of the above "ts-Toronto" : data for the City of Toronto, ON - Canada |
local.data |
boolean flag to indicate whether the data will be read from the local repo, in case of connectivity issues or data integrity |
debrief |
boolean specifying whether information about the read data is going to be displayed in screen |
acknowledge |
boolean flag to indicate that the user acknowledges where the data is coming from. If FALSE, display data acquisition messages. |
Value
a dataframe (or a list in the case of "ALL") with the daily worlwide indicated type of data per country/region/city
Examples
# reads all possible datastest, returnin a list
covid19.all.datasets <- covid19.data("ALL")
# reads the latest aggregated data
covid19.ALL.agg.cases <- covid19.data("aggregated")
# reads time series data for casualities
covid19.TS.deaths <- covid19.data("ts-deaths")
main master (wrapper) function to obtain different types of genomic data for the SARS-CoV-2 virus
Description
main master (wrapper) function to obtain different types of genomic data for the SARS-CoV-2 virus
Usage
covid19.genomic.data(
type = "genome",
src = "livedata",
graphics.ON = TRUE,
accOnly = TRUE
)
Arguments
type |
type of data to retrieve, options are: 'genome', 'genomic', 'fasta', 'nucleotide', 'protein', 'ptree' |
src |
source of the data: "livedata", "repo" or "local" |
graphics.ON |
boolean option for display associated graphics |
accOnly |
boolean indicator for getting only accession codes or whole records |
function to read data related to covid19 Testing from OWID repo
Description
function to read data related to covid19 Testing from OWID repo
Usage
covid19.testing.data(tgt = "testing", disclaimer = TRUE)
Arguments
tgt |
selects between time series data ('testing') and details and overall view of the data ("testing.details") |
disclaimer |
indicates whether the information about the source of the data is disclosed |
Value
dataframe containing list of countries (Entity) and testing data
function to read data related to covid19 vaccinations
Description
function to read data related to covid19 vaccinations
Usage
covid19.vaccination(tgt = "global", data.fmt = "orig", disclaimer = TRUE)
Arguments
tgt |
selects data type: 'global','us','country','locations' |
data.fmt |
selects the format of the data, options are: 'orig' (original as reported by the OWID repo) |
disclaimer |
indicates whether the information about the source of the data is disclosed |
covid19.analytics explorer dashboard
Description
covid19.analytics explorer dashboard
Usage
covid19Explorer(locn = NULL)
Arguments
locn |
geographical location to use as default |
covid19.analytics explorer dashboard
Description
covid19.analytics explorer dashboard
Usage
covid19dashboard(locn = NULL)
Arguments
locn |
geographical location to use as default |
Value
list with shinyApp UI and server
function to check for data integrity and data consistency
Description
function to check for data integrity and data consistency
Usage
data.checks(
data,
n0 = 5,
nf = ncol(data),
datasetName = "",
details = TRUE,
disclose = FALSE
)
Arguments
data |
dataset to analyze |
n0 |
column where the cumulative data begins |
nf |
column where the cumulative data ends |
datasetName |
optional argument to display the name of the dataset |
details |
optional argument to specify whether to show details about the records where inconsistencies were detected |
disclose |
boolean flag to indicate whether index of problematic entries are returned |
estimate rolling rates for a given geographical location for an specific TS data
Description
estimate rolling rates for a given geographical location for an specific TS data
Usage
estimateRRs(
data = NULL,
geo.loc = NULL,
period = NULL,
graphics.ON = TRUE,
splitG = TRUE
)
Arguments
data |
time series dataset to consider |
geo.loc |
country/region to analyze |
period |
length of window |
graphics.ON |
boolean flag to activate/deactivate graphical output |
splitG |
boolean flag for having the graphical output separated or not |
Examples
# the following examples take longer than 10 sec, and triggers CRAN checks
## Not run:
estimateRRs(covid19.data("TS-all"), geo.loc='Peru', period=7)
estimateRRs(covid19.data("TS-all"),
geo.loc=c('Peru','Argentina','Uruguay','US','Spain','Japan'), period=7)
## End(Not run)
function to generate models using GLM
Description
function to generate models using GLM
Usage
gen.glm.model(y, family = Gamma(link = "log"))
Arguments
y |
vector containing the data to fit |
family |
family to use in the GLM method |
function to generate models using Linear Regression "LM"
Description
function to generate models using Linear Regression "LM"
Usage
genModel(y, deg = 1)
Arguments
y |
vector containing the data to fit |
deg |
degree of the polynomial fit |
function to generate a simple SIR (Susceptible-Infected-Recovered) model based on the actual data of the coivd19 cases
Description
function to generate a simple SIR (Susceptible-Infected-Recovered) model based on the actual data of the coivd19 cases
Usage
generate.SIR.model(
data = NULL,
geo.loc = "Hubei",
t0 = NULL,
t1 = NULL,
deltaT = NULL,
tfinal = 90,
fatality.rate = 0.02,
tot.population = 1.4e+09,
staticPlt = TRUE,
interactiveFig = FALSE,
add.extras = FALSE
)
Arguments
data |
time series dataset to consider |
geo.loc |
country/region to analyze |
t0 |
initial period of time for data consideration |
t1 |
final period of time for data consideration |
deltaT |
interval period of time from t0, ie. number of days to consider since t0 |
tfinal |
total number of days |
fatality.rate |
rate of causality, deafault value of 2 percent |
tot.population |
total population of the country/region |
staticPlt |
optional flag to activate/deactive plotting of the data and the SIR model generated |
interactiveFig |
optional flag to activate/deactive the generation of an interactive plot of the data and the SIR model generated |
add.extras |
boolean flag to add extra indicators, such as, the "force of infection" and time derivatives |
Examples
data <- covid19.data("ts-confirmed")
generate.SIR.model(data,"Hubei", t0=1,t1=15)
generate.SIR.model(data,"Germany",tot.population=83149300)
generate.SIR.model(data,"Uruguay", tot.population=3500000)
generate.SIR.model(data,"Canada", tot.population=37590000, add.extras=TRUE)
function to define continents and its constituent countries
Description
function to define continents and its constituent countries
Usage
geographicalRegions(cont = NULL)
Arguments
cont |
optional argumetn, to specify a particular continent; if no argument is given then it returns all the continents and countries for each |
Value
list with the composition of continents
auxiliary function to download files in a protected fashion, i.e. against errors in the downloading procedure
Description
auxiliary function to download files in a protected fashion, i.e. against errors in the downloading procedure
Usage
getFile(url = NULL, fileName = NULL)
Arguments
url |
resource's URL on the web |
fileName |
name of the resource (file) to download keywords internal |
function to compute daily changes and "Growth Rates" per location; "Growth Rates" defined as the ratio between changes in consecutive days
Description
function to compute daily changes and "Growth Rates" per location; "Growth Rates" defined as the ratio between changes in consecutive days
Usage
growth.rate(
data0,
geo.loc = NULL,
stride = 1,
info = "",
staticPlt = TRUE,
interactiveFig = FALSE,
interactive.display = TRUE
)
Arguments
data0 |
data.frame with *time series* data from covid19 |
geo.loc |
list of locations |
stride |
how frequently to compute the growth rate in units of days |
info |
additional information to include in plots' title |
staticPlt |
boolean flag to indicate whether static plots would be generated or not |
interactiveFig |
boolean flag to indicate whether interactice figures would be generated or not |
interactive.display |
boolean flag to indicate whether the interactive plot will be displayed (pushed) to your browser |
Value
a list containing two dataframes: one reporting changes on daily baisis and a second one reporting growth rates, for the indicated regions
Examples
###\donttest{
# read data for confirmed cases
data <- covid19.data("ts-confirmed")
# compute changes and growth rates per location for all the countries
# growth.rate(data)
# compute changes and growth rates per location for 'Italy'
growth.rate(data,geo.loc="Italy")
# compute changes and growth rates per location for 'Italy' and 'Germany'
growth.rate(data,geo.loc=c("Italy","Germany"))
###}
auxiliary fn to print "headers" adn 'titles'
Description
auxiliary fn to print "headers" adn 'titles'
Usage
header(x = "-", title = "", total.len = 80, eol = "\n")
Arguments
x |
character to use as lines |
title |
title to dispo |
total.len |
length of the line |
eol |
end of line character |
auxiliary fn to print "headers" adn 'titles'
Description
auxiliary fn to print "headers" adn 'titles'
Usage
header0(x = "-", title = "", total.len = 80, eol = "\n")
Arguments
x |
character to use as lines |
title |
title to dispo |
total.len |
length of the line |
eol |
end of line character |
function that determines whether there are integrity issues within the datasets or changes to the structure of the data as reported by JHU/CCSEGIS
Description
function that determines whether there are integrity issues within the datasets or changes to the structure of the data as reported by JHU/CCSEGIS
Usage
integrity.check(data, datasetName = "", disclose = FALSE, recommend = TRUE)
Arguments
data |
dataset to analyze |
datasetName |
optional argument to display the name of the dataset |
disclose |
boolean flag to indicate whether index of problematic entries are returned |
recommend |
optional flag to recommend further actions |
function to visualize trends in daily changes in time series data interactively
Description
function to visualize trends in daily changes in time series data interactively
Usage
itrends(
ts.data = NULL,
geo.loc = NULL,
with.totals = FALSE,
fileName = NULL,
interactive.display = TRUE
)
Arguments
ts.data |
time series dataset to process |
geo.loc |
geographical location, country/region or province/state to restrict the analysis to |
with.totals |
a boolean flag to indicate whether the global totals should be displayed with the records for the specific location |
fileName |
file where to save the HTML version of the interactive figure |
interactive.display |
boolean flag to indicate whether the interactive plot will be displayed (pushed) to your browser |
function to map cases in an interactive map
Description
function to map cases in an interactive map
Usage
live.map(
data = covid19.data(),
select.projctn = TRUE,
projctn = "orthographic",
title = "",
no.legend = FALSE,
szRef = 0.2,
fileName = NULL,
interactive.display = TRUE
)
Arguments
data |
data to be used |
select.projctn |
argument to activate or deactivate the pulldown menu for selecting the type of projection |
projctn |
initial type of map-projection to use, possible values are: "equirectangular" | "mercator" | "orthographic" | "natural earth" | "kavrayskiy7" | "miller" | "robinson" | "eckert4" | "azimuthal equal area" | "azimuthal equidistant" | "conic equal area" | "conic conformal" | "conic equidistant" | "gnomonic" | "stereographic" | "mollweide" | "hammer" | "transverse mercator" | "albers usa" | "winkel tripel" | "aitoff" | "sinusoidal" |
title |
a string with a title to add to the plot |
no.legend |
parameter to turn off or on the legend on the right with the list of countries |
szRef |
numerical value to use as reference, to scale up the size of the bubbles in the map, from 0 to 1 (smmaller value –> larger bubbles) |
fileName |
file where to save the HTML version of the interactive figure |
interactive.display |
boolean argument for enabling or not displaying the figure |
Examples
## Not run:
# retrieve aggregated data
data <- covid19.data("aggregated")
# interactive map of aggregated cases -- with more spatial resolution
live.map(data)
# interactive map of the time series data of the confirmed cases
# with less spatial resolution, ie. aggregated by country
live.map(covid19.data("ts-confirmed"))
## End(Not run)
auxiliary function to check and load an specific set of libraries
Description
auxiliary function to check and load an specific set of libraries
Usage
loadLibrary(lib)
Arguments
lib |
is a list of packages to be loaded |
aux fn to create a log-scale pulldown option in plotly plots
Description
aux fn to create a log-scale pulldown option in plotly plots
Usage
## S3 method for class 'sc.setup'
log(nbr.traces, tot.traces)
Arguments
nbr.traces |
number of traces in order to set Ts/Fs |
generic fn that computes the "fn" on a moving window
Description
generic fn that computes the "fn" on a moving window
Usage
movingFn(x, fn = mean, period = length(x), direction = "forward")
Arguments
x |
a numeric vector |
fn |
a function to be applied/computed, default is set to mean() |
period |
size of the "moving window", default set to the lenght of the vector |
direction |
type of moving avergage to consider: "forward", "centered", "backward"; ie. whether the window computation is ( "centered" / "forward" / "backward" ) wrt the data series |
Value
a vector with the 'moving operation' applied to the x vector
function to compute a rolling fn (rate) of multiple quantities from TS data, eg. fatality and recovery rate
Description
function to compute a rolling fn (rate) of multiple quantities from TS data, eg. fatality and recovery rate
Usage
mrollingRates(data = NULL, geo.loc = NULL, fn = mean, period)
Arguments
data |
time series dataset to consider |
geo.loc |
country/region to analyze |
fn |
function to compute rolling |
period |
length of window |
function to visualize different indicators for trends in daily changes of cases reported as time series data, for mutliple (or single) locations
Description
function to visualize different indicators for trends in daily changes of cases reported as time series data, for mutliple (or single) locations
Usage
mtrends(data, geo.loc = NULL, confBnd = TRUE, info = "")
Arguments
data |
data.frame with *time series* data from covid19 |
geo.loc |
list of locations |
confBnd |
flag to activate/deactivate drawing of confidence bands base on a moving average window |
info |
additional info to display in the plot |
Examples
# triggers CRAN checks for timing
## Not run:
ts.data <- covid19.data("ts-confirmed")
mtrends(ts.data, geo.loc=c("Canada","Ontario","Uruguay","Italy"))
## End(Not run)
remove inconsistencies from data by removing 'suspicious' entries
Description
remove inconsistencies from data by removing 'suspicious' entries
Usage
nullify.data(data, stringent = FALSE)
Arguments
data |
dataset to process |
stringent |
only return records with "complete cases" |
function to retrieve historical pandemics data
Description
function to retrieve historical pandemics data
Usage
pandemics.data(acknowledge = TRUE, show = FALSE, tgt = "pandemics")
Arguments
acknowledge |
displays details on the data sources |
show |
displays data |
tgt |
which data set to read – options are 'pandemics' OR 'pandemics_vaccines' |
Value
data.frame
internal function to retrieve historical data on pandemics
Description
internal function to retrieve historical data on pandemics
Usage
pandemics.loaddata(
tgt.file = "pandemics.RDS",
acknowledge = TRUE,
show = FALSE,
src.descr = ""
)
Arguments
tgt.file |
which data set to read |
acknowledge |
displays details on the data sources |
show |
displays data |
src.descr |
description of the source of the data |
Value
data.frame
function to plot the results from the SIR model fn
Description
function to plot the results from the SIR model fn
Usage
plt.SIR.model(
SIR.model,
geo.loc = "",
interactiveFig = FALSE,
fileName = NULL,
interactive.display = TRUE,
add.extras = TRUE
)
Arguments
SIR.model |
model resulting from the generate.SIR.model() fn |
geo.loc |
optional string to specify geographical location |
interactiveFig |
optional flag to activate interactive plot |
fileName |
file where to save the HTML version of the interactive figure |
interactive.display |
boolean flag to indicate whether the interactive plot will be displayed (pushed) to your browser |
add.extras |
boolean flag to add extra indicators, such as, the "force of infection" and time derivatives |
auxiliary function to pre-process data per geographical location
Description
auxiliary function to pre-process data per geographical location
Usage
preProcessingData(data0, geo.loc)
Arguments
data0 |
data set |
geo.loc |
geopgraphical location, can be a country, region, province or city #@keywords internal |
method associated with 'report' objects
Description
method associated with 'report' objects
Usage
print(report.obj)
Arguments
report.obj |
'report' object |
function associated to the 'report' object method
Description
function associated to the 'report' object method
Usage
## S3 method for class 'report'
print(report.obj)
Arguments
report.obj |
'report' object |
function to redirect users to install devel version from github
Description
function to redirect users to install devel version from github
Usage
red.devel.ver(fileRDS, force = TRUE)
Arguments
fileRDS |
missing data file |
force |
boolean flag to force stoping the code |
function to obtain main indicators from Toronto data
Description
function to obtain main indicators from Toronto data
Usage
report.Tor(
colTgts = c("Source.of.Infection", "Age.Group", "Client.Gender", "Outcome",
"Neighbourhood.Name"),
report = TRUE,
staticPlt = TRUE,
horiz.plts = 4,
vert.plts = 3,
same.Yaxis = TRUE,
interactiveFig = FALSE,
interactive.display = TRUE
)
Arguments
colTgts |
optional argument to indicate which columns from the Toronto data to process |
report |
optional argument indicating whether a report will be printed to the screen |
staticPlt |
optional argument to indicate whether the 'static' graphical output is wanted or not |
horiz.plts |
number of plots in the horizontal direction |
vert.plts |
number of plots in the vertical direction |
same.Yaxis |
graphical argument to indicate if plots will use same y-axis |
interactiveFig |
boolean flag to indicate whether interactice figures would be generated or not |
interactive.display |
boolean flag to indicate whether the interactive plot will be displayed (pushed) to your browser |
Value
list with statistics by selected as indicated in colTgts
#@export
function to summarize the current situation, will download the latest data and summarize the top provinces/cities per case
Description
function to summarize the current situation, will download the latest data and summarize the top provinces/cities per case
Usage
report.summary(
cases.to.process = "ALL",
Nentries = 10,
geo.loc = NULL,
graphical.output = TRUE,
saveReport = FALSE
)
Arguments
cases.to.process |
which data to process: "TS" –time series–, "AGG" –aggregated– or "ALL" –time series and aggregated– |
Nentries |
number of top cases to display |
geo.loc |
geographical location to process |
graphical.output |
flag to deactivate graphical output |
saveReport |
flag to indicate whether the report should be saved in a file |
Examples
# triggers CRAN checks for timing
## Not run:
# displaying top 10s
report.summary()
# get the top 20
report.summary(Nentries=20,graphical.output=FALSE)
# specify a location
report.summary(geo.loc="NorthAmerica")
## End(Not run)
function to compute a rolling fn of a TS data
Description
function to compute a rolling fn of a TS data
Usage
rollingRate(data, fn = mean, period = NULL)
Arguments
data |
TS data |
fn |
function to compute rolling |
period |
length of window |
Value
a vector with rolling values
auxiliary function to select data based on geographical location
Description
auxiliary function to select data based on geographical location
Usage
select.per.loc(data, geo.loc)
Arguments
data |
data set to process |
geo.loc |
geographical location, can be a country, region, province or city |
auxiliary function to set the graphical layout
Description
auxiliary function to set the graphical layout
Usage
set.plt.canvas(geo.loc, ylayers = 1, minBreaks = 5)
Arguments
geo.loc |
list of locations so that the fn can determine how many plots would be |
ylayers |
parameter to set a multiplier times the nbr of initial plots |
minBreaks |
cut-off to set the minimum nbr of plots |
Define an ODE system for a simple SIR model
Description
Define an ODE system for a simple SIR model
Usage
simple.SIR.ODE(time, state, parameters)
Arguments
time |
time variable |
state |
state variable |
parameters |
parameters of the ODE |
function to visualize different indicators for trends in daily changes of cases reported as time series data
Description
function to visualize different indicators for trends in daily changes of cases reported as time series data
Usage
single.trend(ts.data, confBnd = TRUE, info = "")
Arguments
ts.data |
time series data |
confBnd |
optional argument to remove the drawing of a confidence band |
info |
addtional information to display in plots |
Examples
tor.data <- covid19.Toronto.data()
single.trend(tor.data[tor.data$status=="Active Cases",])
ts.data <- covid19.data("ts-confirmed")
ont.data <- ts.data[ ts.data$Province.State == "Ontario",]
single.trend(ont.data)
single.trend(ts.data[ ts.data$Country.Region=="Italy",])
function to perform a sweep of models and generate values of R0
Description
function to perform a sweep of models and generate values of R0
Usage
sweep.SIR.models(
data = NULL,
geo.loc = "Hubei",
t0_range = 15:20,
t1 = NULL,
deltaT = NULL,
tfinal = 90,
fatality.rate = 0.02,
tot.population = 1.4e+09
)
Arguments
data |
time series dataset to consider |
geo.loc |
country/region to analyze |
t0_range |
range of initial date for data consideration |
t1 |
final period of time for data consideration |
deltaT |
interval period of time from t0, ie. number of days to consider since t0 |
tfinal |
total number of days |
fatality.rate |
rate of causality, deafault value of 2 percent |
tot.population |
total population of the country/region |
Examples
# read TimeSeries data
TS.data <- covid19.data("TS-confirmed")
# select a location of interest, eg. France
# France has many entries, just pick "la France"
France.data <- TS.data[ (TS.data$Country.Region == "France") & (TS.data$Province.State == ""),]
# sweep values of R0 based on range of dates to consider for the model
ranges <- 15:20
deltaT <- 20
params_sweep <- sweep.SIR.models(data=France.data,geo.loc="France", t0_range=ranges, deltaT=deltaT)
# obtain the R0 values from the parameters
R0s <- unlist(params_sweep["R0",])
# nbr of infected cases
FR.infs<- preProcessingData(France.data,"France")
# average per range
# define ranges
lst.ranges <- lapply(ranges, function(x) x:(x+deltaT))
# compute averages
avg.FR.infs <- lapply(lst.ranges, function(x) mean(FR.infs[x]))
# plots
plot(R0s, type='b')
# plot vs average number of infected cases
plot(avg.FR.infs, R0s, type='b')
function to plot total number of cases per day for different groups
Description
function to plot total number of cases per day for different groups
Usage
totals.plt(
data0 = NULL,
geo.loc0 = NULL,
one.plt.per.page = FALSE,
log.plt = TRUE,
with.totals = FALSE,
interactive.fig = TRUE,
fileName = NULL,
interactive.display = TRUE
)
Arguments
data0 |
time series dataset to process, default all the possible cases: 'confirmed' and 'deaths' for all countries/regions |
geo.loc0 |
geographical location, country/region or province/state to restrict the analysis to |
one.plt.per.page |
boolean flag to have one plot per figure |
log.plt |
include a log scale plot in the static plot |
with.totals |
a boolean flag to indicate whether the totals should be displayed with the records for the specific location |
interactive.fig |
switch to turn off/on an interactive plot |
fileName |
file where to save the HTML version of the interactive figure |
interactive.display |
boolean argument for enabling or not displaying the interactive figure |
Examples
# retrieve time series data
TS.data <- covid19.data("ts-ALL")
# static and interactive plot
totals.plt(TS.data)
function to compute totals per location
Description
function to compute totals per location
Usage
tots.per.location(
data,
geo.loc = NULL,
confBnd = FALSE,
nbr.plts = 1,
info = ""
)
Arguments
data |
data.frame with *time series* data from covid19 |
geo.loc |
list of locations |
confBnd |
flag to activate/deactivate drawing of confidence bands base on a moving average window |
nbr.plts |
parameter to control the number of plots to display per figure |
info |
additional info to display in plots' titles |
Value
a list or dataframe with totals per specified locations and type of case
Examples
# read data for confirmed cases
data <- covid19.data("ts-confirmed")
# compute totals per location for all the countries
tots.per.location(data)
# compute totals per location for 'Italy'
tots.per.location(data,geo.loc="Italy")
# compute totals per location for 'Italy' and 'Germany'
tots.per.location(data,geo.loc=c("Italy","Germany"))