SemiContinuousDataAnalysis

rm(list = ls())

library(ggplot2)
library(lubridate)

## 
## Attaching package: 'lubridate'

## The following objects are masked from 'package:base':
## 
##     date, intersect, setdiff, union

df_window = read.csv("df_window.csv", sep=";")
df_window$Time = as.POSIXct(df_window$data.measurement_timestamp/1000,
                            origin = "1970-01-01 00:00:00:000")
df_window$Month = months(df_window$Time)
mnt = unique(df_window$Month)

for(i in 1:length(mnt))
{
  df = subset(df_window, Month == mnt[i] & is.na(data.heartrate) == FALSE)
  p = ggplot(df, aes(x = Time, y = data.heartrate, color=data.indicator)) +
    geom_point() + labs(title = mnt[i]) +theme_light() +
    theme(legend.position = "bottom") + 
    scale_colour_manual(values = c("warning" = "#f09034", "urgent" = "#dc324a",
                                   "normal" = "#6bacb2","Quality" = "white"))

  print(p)
}

## Warning: Removed 1 rows containing missing values (geom_point).

## Warning: Removed 222 rows containing missing values (geom_point).

## Warning: Removed 5847 rows containing missing values (geom_point).

## Warning: Removed 3364 rows containing missing values (geom_point).

## Warning: Removed 5372 rows containing missing values (geom_point).

## Warning: Removed 2 rows containing missing values (geom_point).