#   call in required packages
library(rCharts)
library(plyr)
library(knitr)
library(reshape2)
library(scales)
library(ggplot2)
library(dplyr)
library(hrbrthemes)
library(viridis)
options(RCHART_WIDTH = 900, RCHART_HEIGHT = 400)
knitr::opts_chunk$set(comment = NA, results = 'asis', tidy = F, message = F)

Processed data
to make a line plot easier to view I have aggregated the temperature records to the mean over a 3 hour period

setwd("C:/Users/roman/Documents/MawsonWeather/scripts")
source("inside_outside.R")

June only

Subsetting the data for one month

df_june <-  df_temp[which(month(df_temp$Datetime) == 6),]


df = transform(df_june, Datetime = as.character(Datetime))
m1 <- mPlot(x = "Datetime", y = c("Temperature_C.outside",  "Temperature_C.inside" ), type = "Line", data = df )
m1$set(pointSize = 0, lineWidth = 1)
m1$set(lineColors=c("skyblue","red"))
m1$print(include_assets=T)

Boxplot
Comparing Inside with outside temperature variation

dat_long <- melt(df_june, id.vars='Datetime', 
                  measure.vars=c('Temperature_C.inside', 'Temperature_C.outside' ))
names(dat_long) <- c("Datetime", "Location" , "Temperature" )
bp <- ggplot(dat_long) +
geom_boxplot(aes(x=Location, y=Temperature, color=Location))
bp

June first day 

df_24.1 <- df_temp[df_temp$Datetime >= "2023-06-01" & df_temp$Datetime < "2023-06-02", ]


df = transform(df_24.1, Datetime = as.character(Datetime))
m2 <- mPlot(x = "Datetime", y = c("Temperature_C.outside",  "Temperature_C.inside" ), type = "Line", data = df )
m2$set(pointSize = 0, lineWidth = 1)
m2$set(lineColors=c("skyblue","red"))
m2$print(include_assets=T)

June second day 

df_24.2 <- df_temp[df_temp$Datetime >= "2023-06-02" & df_temp$Datetime < "2023-06-03", ]


df = transform(df_24.2, Datetime = as.character(Datetime))
m3 <- mPlot(x = "Datetime", y = c("Temperature_C.outside",  "Temperature_C.inside" ), type = "Line", data = df )
m3$set(pointSize = 0, lineWidth = 1)
m3$set(lineColors=c("skyblue","red"))
m3$print(include_assets=T)