Población y vivienda

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This is an R Markdown document. Markdown is a simple formatting syntax for authoring HTML, PDF, and MS Word documents. For more details on using R Markdown see http://rmarkdown.rstudio.com.

When you click the Knit button a document will be generated that includes both content as well as the output of any embedded R code chunks within the document. You can embed an R code chunk like this:

#install.packages(c("tidyverse", "tidyquant", "lubridate"))

library(tidyverse)

## ── Attaching core tidyverse packages ──────────────────────── tidyverse 2.0.0 ──
## ✔ dplyr     1.2.0     ✔ readr     2.1.6
## ✔ forcats   1.0.1     ✔ stringr   1.6.0
## ✔ ggplot2   4.0.2     ✔ tibble    3.3.1
## ✔ lubridate 1.9.5     ✔ tidyr     1.3.2
## ✔ purrr     1.2.1     
## ── 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

library(tidyquant)

## Registered S3 method overwritten by 'quantmod':
##   method            from
##   as.zoo.data.frame zoo 
## ── Attaching core tidyquant packages ─────────────────────── tidyquant 1.0.11 ──
## ✔ PerformanceAnalytics 2.0.8      ✔ TTR                  0.24.4
## ✔ quantmod             0.4.28     ✔ xts                  0.14.2── Conflicts ────────────────────────────────────────── tidyquant_conflicts() ──
## ✖ zoo::as.Date()                 masks base::as.Date()
## ✖ zoo::as.Date.numeric()         masks base::as.Date.numeric()
## ✖ dplyr::filter()                masks stats::filter()
## ✖ xts::first()                   masks dplyr::first()
## ✖ dplyr::lag()                   masks stats::lag()
## ✖ xts::last()                    masks dplyr::last()
## ✖ PerformanceAnalytics::legend() masks graphics::legend()
## ✖ quantmod::summary()            masks base::summary()
## ℹ Use the conflicted package (<http://conflicted.r-lib.org/>) to force all conflicts to become errors

library(lubridate)

tickers <- c("BIMBOA.MX","CEMEXCPO.MX","MSFT","AMZN","SHELL.AS","ASML.AS")

start_date <- as.Date("2011-02-01")
end_date   <- as.Date("2024-02-01")
cut_date   <- as.Date("2020-01-01")

Including Plots

You can also embed plots, for example:

prices <- prices %>%
  mutate(period = if_else(date < cut_date, "Before 2020", "2020 onwards"))

prices %>%
  filter(period == "Before 2020") %>%
  ggplot(aes(x = symbol, y = adjusted)) +
  geom_boxplot() +
  labs(
    title = "Stock Prices (Adjusted) Before 2020",
    x = "Stock",
    y = "Adjusted Close Price"
  ) +
  theme_minimal()

prices %>%
  filter(period == "2020 onwards") %>%
  ggplot(aes(x = symbol, y = adjusted)) +
  geom_boxplot() +
  labs(
    title = "Stock Prices (Adjusted) From 2020 Onwards",
    x = "Stock",
    y = "Adjusted Close Price"
  ) +
  theme_minimal()

prices %>%
  ggplot(aes(x = symbol, y = adjusted, fill = period)) +
  geom_boxplot(position = "dodge") +
  labs(
    title = "Comparison of Stock Prices (Adjusted): Before 2020 vs 2020 Onwards",
    x = "Stock",
    y = "Adjusted Close Price",
    fill = "Period"
  ) +
  theme_minimal()

Note that the echo = FALSE parameter was added to the code chunk to prevent printing of the R code that generated the plot.