Analyze in R: Heatmap your calendar! The “openair” package

The “calendarPlot” command included in this package can easily heat map your calendar.

It may be interesting to plot readily available temperature and precipitation data on a calendar.

Package version is 2.14. Checked with R version 4.2.2.

＜おすすめのRに関する書籍です＞

実践Data Scienceシリーズ RとStanではじめる ベイズ統計モデリングによるデータ分析入門 | 馬場真哉

統計・確率の基本からMCMCまでを押さえ、GLMからGLMM、動的線形モデルへと体系的に進む。brmsやbayesplotの使い方も学べる。

Install Package

Run the following command.

#Install Package
install.packages("openair")

Examples

See the command and package help for details.

#Loading the library
library("openair")

###Creating Data#####
#Install the lubridate package if it is not already present
if(!require("lubridate", quietly = TRUE)){
  install.packages("lubridate");require("lubridate")
}
#Install the tidyverse package if it is not already present
if(!require("tidyverse", quietly = TRUE)){
  install.packages("tidyverse");require("tidyverse")
}

set.seed(1234)
n <- 30
TestData <- tibble(date = seq(lubridate::ymd("2022-12-01", locale = "C",
                                             tz = "Asia/Tokyo"),
                              by = "1 day", length.out = n),
                   Data = sample(1:30, n, replace = TRUE))
########

#Convert date to Date class
TestData[, 1] <- as.Date(TestData[, 1], tz = "Japan")
#Plot
calendarPlot(TestData, pollutant = "Data",
             annotate = "date",
             day = "weekend",
             cols = c("#4b61ba", "#a87963"),
             main = "からだにいいもの")

Output Example

I hope this makes your analysis a little easier !!

＜おすすめのRに関する書籍です＞

基礎から学ぶ統計学実践編〜PCを使った計算とカテゴリカルデータ解析

PCで実際に計算しながら進める実践編。クロス集計などカテゴリカルデータの解析を扱う。

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