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library(readxl)
library(tidyverse)
## ── Attaching core tidyverse packages ──────────────────────── tidyverse 2.0.0 ──
## ✔ dplyr     1.1.4     ✔ readr     2.1.5
## ✔ forcats   1.0.0     ✔ stringr   1.5.1
## ✔ ggplot2   3.5.1     ✔ tibble    3.2.1
## ✔ lubridate 1.9.3     ✔ tidyr     1.3.1
## ✔ purrr     1.0.2     
## ── Conflicts ────────────────────────────────────────── tidyverse_conflicts() ──
## ✖ dplyr::filter() masks stats::filter()
## ✖ dplyr::lag()    masks stats::lag()
## ℹ Use the conflicted package (<http://conflicted.r-lib.org/>) to force all conflicts to become errors
Energy<-read_excel("Energy.xlsx")

###1: SUMMARY OF TWO VARIABLES THAT I WOULD LIKE TO EXPLORE AND SEE IF THERE IS A CORRELATION BETWEEN THE TWO

summary(Energy$`Total people in household / Número total...`)
##    Min. 1st Qu.  Median    Mean 3rd Qu.    Max. 
##   0.000   1.000   2.000   2.341   3.000  13.000
summary(Energy$`Usage Consumption`)
##    Min. 1st Qu.  Median    Mean 3rd Qu.    Max. 
##     0.0     0.0   112.0   610.1  1039.5 10902.0

###2: HISTROGRAM FOR BOTH VARIABLES

ggplot(Energy, aes(x=`Total people in household / Número total...`)) + geom_histogram()
## `stat_bin()` using `bins = 30`. Pick better value with `binwidth`.

ggplot(Energy, aes(x=`Usage Consumption`)) + geom_histogram()
## `stat_bin()` using `bins = 30`. Pick better value with `binwidth`.

###3: PLOT THAT COMPARES BOTH VARIABLES

ggplot(Energy,aes(x=`Total people in household / Número total...`,y=`Usage Consumption`)) + geom_point()

###4: CORRELATION

cor(Energy$`Usage Consumption`, Energy$`Total people in household / Número total...`)
## [1] 0.1437128

###THERE IS A WEAK POSITIVE CORRELATION BETWEEN TOTAL PEOPLE IN HOUSEHOLD AND USAGE CONSUMPTION