Error message when I try to create an epicurve

mikhailia.mcintosh · March 4, 2024, 3:46pm

Thank you for posting! Here is an outline of an effective post:

I get the following error message when I try to create my epicurve.

Error in unsupported_date_time(time) :
Unsupported date-time class ‘character’

Please see my R code below.

# Loads packages 
pacman::p_load(
  rio,          # for importing data
  here,         # for locating files
  janitor,      # for data cleaning  
  lubridate,    # for date cleaning
  epikit,       # for easy inline code
  tsibble,      # for epiweeks and other time series analyses
  datapasta,
  reprex,
  tidyverse     # for data management and visualization
)

# data
combined <- data.frame(
  stringsAsFactors = FALSE,
  date_report = c("2020-09-09","2020-07-25",
                  "2020-07-02","2020-11-05","2020-09-26","2020-09-26",
                  "2020-07-07","2020-06-06","2020-06-06","2020-08-08",
                  "2020-07-24","2021-02-11","2020-09-15","2020-09-15",
                  "2020-11-30","2021-04-13","2021-04-13","2021-04-22",
                  "2020-07-14","2020-11-19","2020-11-19","2020-12-13",
                  "2020-12-13","2020-12-15","2020-07-13"),
  city = c("Atlanta","Union City",
           "Atlanta","Atlanta","Atlanta","East Point","Alpharetta",
           "Atlanta","East Point","Alpharetta","Atlanta","Atlanta",
           "Atlanta","College Park","Union City","Atlanta",
           "College Park","Atlanta","Roswell","Atlanta",
           "College Park","Atlanta","Hapeville","Atlanta","Atlanta"),
  population = c(498715,26830,498715,498715,
                 498715,38358,65818,498715,38358,65818,498715,
                 498715,498715,13930,26830,498715,13930,498715,92833,
                 498715,13930,498715,6553,498715,498715))
  
# Graphs  -----------------------------------------------------------------
# Create a Weekly Epidemic Curve by City 

# Define and save the vector (monthly)
covid_months <- seq.Date(from = floor_date(min(combined$date_report, na.rm=T), unit = "month"),
                        to =   ceiling_date(max(combined$date_report, na.rm=T), unit = "month"),
                        by =   "month")
#> Error in unsupported_date_time(time): Unsupported date-time class 'character'

# Weekly reported cases epicurve 
ggplot(data = combined, aes(x = date_report, fill=city)) +
  geom_histogram(
    breaks = covid_months,
    closed = "left") +
  scale_x_date(
    labels = scales::label_date_short(),
    date_breaks = "weeks") +
  labs(title = "COVID-19 epidemic",
       x = "Date of report", 
       y = "Number of cases",
       fill = "City") +
  theme_bw()
#> Error in eval(expr, envir, enclos): object 'covid_months' not found

^{Created on 2024-03-04 with reprex v2.0.2}

Session info

sessioninfo::session_info()
#> ─ Session info ───────────────────────────────────────────────────────────────
#>  setting  value
#>  version  R version 4.3.1 (2023-06-16 ucrt)
#>  os       Windows 10 x64 (build 19045)
#>  system   x86_64, mingw32
#>  ui       RTerm
#>  language (EN)
#>  collate  English_United Kingdom.utf8
#>  ctype    English_United Kingdom.utf8
#>  tz       Europe/London
#>  date     2024-03-04
#>  pandoc   3.1.1 @ C:/Program Files/RStudio/resources/app/bin/quarto/bin/tools/ (via rmarkdown)
#> 
#> ─ Packages ───────────────────────────────────────────────────────────────────
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#>  curl                5.1.0   2023-10-02 [1] CRAN (R 4.3.2)
#>  data.table          1.14.8  2023-02-17 [1] CRAN (R 4.3.2)
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#>  httpuv              1.6.12  2023-10-23 [1] CRAN (R 4.3.2)
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#>  jsonlite            1.8.7   2023-06-29 [1] CRAN (R 4.3.2)
#>  KernSmooth          2.23-21 2023-05-03 [2] CRAN (R 4.3.1)
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#>  lubridate         * 1.9.3   2023-09-27 [1] CRAN (R 4.3.2)
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#> ──────────────────────────────────────────────────────────────────────────────

Many thanks for your help.

machupovirus · March 5, 2024, 12:09am

Hello,

You need to convert date_reoprt in your data to have a date type in order for R to understand it’s a date, see below:

# loading packages
library(tidyverse)
library(janitor)
#> 
#> Attaching package: 'janitor'
#> The following objects are masked from 'package:stats':
#> 
#>     chisq.test, fisher.test

# creating the data
combined <- data.frame(
    stringsAsFactors = FALSE,
    date_report = c("2020-09-09","2020-07-25",
                                    "2020-07-02","2020-11-05","2020-09-26","2020-09-26",
                                    "2020-07-07","2020-06-06","2020-06-06","2020-08-08",
                                    "2020-07-24","2021-02-11","2020-09-15","2020-09-15",
                                    "2020-11-30","2021-04-13","2021-04-13","2021-04-22",
                                    "2020-07-14","2020-11-19","2020-11-19","2020-12-13",
                                    "2020-12-13","2020-12-15","2020-07-13"),
    city = c("Atlanta","Union City",
                     "Atlanta","Atlanta","Atlanta","East Point","Alpharetta",
                     "Atlanta","East Point","Alpharetta","Atlanta","Atlanta",
                     "Atlanta","College Park","Union City","Atlanta",
                     "College Park","Atlanta","Roswell","Atlanta",
                     "College Park","Atlanta","Hapeville","Atlanta","Atlanta"),
    population = c(498715,26830,498715,498715,
                                 498715,38358,65818,498715,38358,65818,498715,
                                 498715,498715,13930,26830,498715,13930,498715,92833,
                                 498715,13930,498715,6553,498715,498715))

# cleaning the data
clean_combined <- combined |>
    mutate(date_report = ymd(date_report))

# creating a vector of breakpoints for the histogram
covid_months <-
    seq.Date(
        from = floor_date(min(clean_combined$date_report, na.rm = T), unit = "month"),
        to = ceiling_date(max(clean_combined$date_report, na.rm = T), unit = "month"),
        by = "month"
    )

# creating the epicurve
ggplot(data = clean_combined, aes(x = date_report, fill = city)) +
    geom_histogram(breaks = covid_months,
                                 closed = "left") +
    scale_x_date(labels = scales::label_date_short(),
                             date_breaks = "weeks") +
    labs(title = "COVID-19 epidemic",
             x = "Date of report",
             y = "Number of cases",
             fill = "City") +
    theme_bw()

^{Created on 2024-03-04 with reprex v2.1.0}

Session info

sessioninfo::session_info()
#> ─ Session info ───────────────────────────────────────────────────────────────
#>  setting  value
#>  version  R version 4.3.1 (2023-06-16)
#>  os       macOS Ventura 13.6.3
#>  system   x86_64, darwin20
#>  ui       X11
#>  language (EN)
#>  collate  en_US.UTF-8
#>  ctype    en_US.UTF-8
#>  tz       America/Toronto
#>  date     2024-03-04
#>  pandoc   3.1.1 @ /Applications/RStudio.app/Contents/Resources/app/quarto/bin/tools/ (via rmarkdown)
#> 
#> ─ Packages ───────────────────────────────────────────────────────────────────
#>  package     * version date (UTC) lib source
#>  cli           3.6.2   2023-12-11 [1] CRAN (R 4.3.0)
#>  colorspace    2.1-0   2023-01-23 [1] CRAN (R 4.3.0)
#>  curl          5.2.0   2023-12-08 [1] CRAN (R 4.3.0)
#>  digest        0.6.34  2024-01-11 [1] RSPM (R 4.3.0)
#>  dplyr       * 1.1.4   2023-11-17 [1] CRAN (R 4.3.0)
#>  evaluate      0.23    2023-11-01 [1] CRAN (R 4.3.0)
#>  fansi         1.0.6   2023-12-08 [1] CRAN (R 4.3.0)
#>  farver        2.1.1   2022-07-06 [1] CRAN (R 4.3.0)
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#>  generics      0.1.3   2022-07-05 [1] CRAN (R 4.3.0)
#>  ggplot2     * 3.5.0   2024-02-23 [1] RSPM (R 4.3.0)
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#>  gtable        0.3.4   2023-08-21 [1] CRAN (R 4.3.0)
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#>  reprex        2.1.0   2024-01-11 [1] RSPM (R 4.3.0)
#>  rlang         1.1.3   2024-01-10 [1] RSPM (R 4.3.0)
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#>  yaml          2.3.8   2023-12-11 [1] CRAN (R 4.3.0)
#> 
#>  [1] /Users/timothychisamore/Library/R/x86_64/4.3/library
#>  [2] /Library/Frameworks/R.framework/Versions/4.3-x86_64/Resources/library
#> 
#> ──────────────────────────────────────────────────────────────────────────────

You may also want to adjust your breakpoints or how R labels them, as well.

All the best,

Tim