In NanisTe/tsheatmap: Plot a calendaric heatmap of data frame with a POSIXct column and a Data cloumn

knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>",
  fig.path = "man/figures/README-",
  out.width = "100%"
)

tsheatmap

The goal of tsheatmap is to create an easy visualisations of timeseries as a heatmap with respect to the nature of repetitive patterns in calendaric phases like week, days, and hours. Most of our behaviour is related to the date, day of the week and hour. The type of visualisation respects that and will make repetitice patterns over the course of a year visible.

Installation

You can install the development version of tsheatmap from Github by

library(devtools)
devtools::install_github("NanisTe/tsheatmap",ref = "dev")

Example

This is a basic example which shows you how to plot a dataset:

library(tsheatmap)
## basic example code

df <- 
  data.frame(
    Datetime = seq.POSIXt(from = as.POSIXct("2019-01-01",tz = "Europe/Zurich")
                          ,to = as.POSIXct("2019-12-31 23:00",tz = "Europe/Zurich")
                          ,by = "1 hour"),
    Data = c(1,2,3,4,5,6,5,4,3,2,1,0,1,3,5,7,9,7,5,4,3,2,1,0))

tsheatmap(data = df
          , datetime_colname = "Datetime"
          , data_colname = "Data")

tsheatmap(data = df[1:8713,]
          , data_colname = "Data")

What is special about using README.Rmd instead of just README.md? You can include R chunks like so:

summary(cars)

You'll still need to render README.Rmd regularly, to keep README.md up-to-date.

You can also embed plots, for example:

plot(pressure)

In that case, don't forget to commit and push the resulting figure files, so they display on GitHub!

NanisTe/tsheatmap documentation built on Jan. 29, 2020, 8:02 p.m.