avallecam

``` r
if(!require("pak")) install.packages("pak")

new_packages <- c(
  "incidence2",
  "outbreaks",
  "tidyverse"
)

pak::pkg_install(new_packages)

avallecam

``` r
library(tidyverse)

# epiparameter ------------------------------------------------------------

library(epiparameter)

# get set of epidist objects
epidist_input <- epiparameter::epidist_db(
  disease = "covid",

avallecam

``` r
# packages ----------------------------------------------------------------

library(tidyverse)
library(incidence2) 

# input -------------------------------------------------------------------

onset <- tibble(
  date = seq(ymd(20200101),ymd(20200104),1),

avallecam

If I need to install python packages

```{python}
# install packages
pip install pandas
pip install matplotlib
```

I can install python (!!) and the packages in R using `{reticulate}`

avallecam

``` r
# from py to R ------------------------------------------------------------

# to convert the a python notebook to Rmd file
# with https://pkgs.rstudio.com/rmarkdown/reference/convert_ipynb.html

# for one sample ----------------------------------------------------------

set.seed(123)

avallecam

``` r
# from dplyr --------------------------------------------------------------

# https://dplyr.tidyverse.org/articles/rowwise.html#creating

library(tidyverse)

df <- tibble(
  x = 1:2, 
  y = 3:4, 

avallecam

# tidyr::complete() & tidyr::full_seq() -----------------------------------

# Turning implicit missing values into explicit missing values.
# Bonus: Filling in gaps in a date range

library(tidyr)
library(tibble)
library(dplyr)

# Making up some observations from two weather stations. 

avallecam

``` r
library(tidyverse)
#> Warning: package 'tidyverse' was built under R version 4.2.3
#> Warning: package 'ggplot2' was built under R version 4.2.3
#> Warning: package 'tibble' was built under R version 4.2.3
#> Warning: package 'forcats' was built under R version 4.2.3

# library(datapasta)
# tribble_paste()

avallecam

if (!require("pacman")) install.packages("pacman")
#> Loading required package: pacman
pacman::p_load(tidyverse)

# con missing como NA -----------------------------------------------------

f1 <- tibble(variable = c("a", "a", NA, NA, "a", "b", 
                          NA, "c", "a", "c", "b"))
f1
#> # A tibble: 11 × 1

avallecam

# https://dplyr.tidyverse.org/articles/rowwise.html 
``` r
library(tidyverse)

# how to use across() -------------------------------------------------------

# _ with summary functions ------------------------------------------------

# from cheetsheet
# summarise(mtcars, across(everything(), mean))