Week 11
Penelope Pooler Eisenbies
2023-12-07
# this line specifies options for default options for all R Chunks
knitr::opts_chunk$set(echo=T,
highlight=T)
# suppress scientific notation
options(scipen=100,
getSymbols.warning4.0 = FALSE)
# install helper package (pacman), if needed
if (!require("pacman")) install.packages("pacman", repos = "http://lib.stat.cmu.edu/R/CRAN/")## Loading required package: pacman# install and load required packages
# pacman should be first package in parentheses and then list others
pacman::p_load(pacman, tidyverse, ggthemes, magrittr, lubridate, tidyquant, highcharter,
flexdashboard,knitr, RColorBrewer, dygraphs, gridExtra)
# verify packages (comment out in finished documents)
p_loaded()## [1] "gridExtra" "dygraphs" "RColorBrewer"
## [4] "knitr" "flexdashboard" "highcharter"
## [7] "tidyquant" "quantmod" "TTR"
## [10] "PerformanceAnalytics" "xts" "zoo"
## [13] "magrittr" "ggthemes" "lubridate"
## [16] "forcats" "stringr" "dplyr"
## [19] "purrr" "readr" "tidyr"
## [22] "tibble" "ggplot2" "tidyverse"
## [25] "pacman"Announcements
HW 5 - Part 2 is now posted and will be due Wednesday 12/6
This is the last HW Assignment and requires very little coding (Code is provided)
You are asked to place and format chunks correctly to expand and update your dashboard as instructed.
This assignment ALSO requires writing thoughtful responses to questions (on Blackboard) and adding text to dashboard.
- Today I will introduce HW 5 - Part 2
Plan for Thursday and Next Week
.pull-left[
Format and requirements for the project memos
Project Presentation Information
Other ways to use R/RStudio and Collaborate
Requested/Selected Topics
This week and next week are planned as short lecture days
If I receive questions that are useful to all I will incorporate topics
Goal is to provide information to all students while still keeping time open for group work.
Background for HW 5 - Part 2
Syracuse University is currently developing Six University-wide Shared Competencies
From the website:
“Undergraduate students develop competencies through their major degree courses, liberal arts requirements, and co-curricular experiences.”
BUA 455 - Information Literacy and Technology Agility
- Technology Agility skills are prevalent in every assignment and task throughout the course.
- Information literacy skills are primarily addressed in HW 5 - Part 2 and in the course project.
Essential Information Literacy Skills include
Knowing how to search for information and compare data sources.
Attributing data sources and software
Comparing and evaluating different options for presenting information to determine the right choice for a specific situation.
Intro of HW 5 - Part 2
This assignment expands the dashboard created in HW 5 - Part 1.
For some tasks, you are adding plots that are redundant with previous ones
- You will be asked to compare and contrast these data visualization options.
Review and New Skills for HW 5 and Project
Adding a panel to a dashboard
This is straightforward but it requires careful placement of the chunk, the panel header text, and the side panel text.
In-class Demo
Skills for HW 5 - Part 2 and Project
Adding linked text to Markdown Output
This same format will work in Word, Powerpoint, Html, and Pdf output files
Text to link goes in square brackets
Followed by link is in round brackets
Examples:
Skills for HW 5 - Part 2 and Project
Adding an image
This same format will work in Word, Powerpoint, Html, and Pdf output files
Similar to adding linked text:
Exclamation point followed by square brackets which can include a caption (optional)
Directly Followed by image file name in parentheses
Image file should be in
code_data_outputfolder.
NOTE: You can save and export an R data visualization, and then place that figure elsewhere in the document as .png or .jpg file separate from R code.
Example of Image with caption
Skills for HW 5 - Part 2 and Project
Citing sources
This is not an English class so I am not particular about citation formatting
If you are publishing in a journal, you will be required to use that journal’s format.
If you are consulting for a client or for a company, defer to the citation format they prefer.
In this course, all citations should be formatted consistently. Choose one format and stick with it.
Here is link with suggestions on how to cite websites
Citing R
- Type
citation()in the R Console to see the full citation which can be copy and pasted:
citation()
- To cite R:
R Core Team (2022). R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. URL https://www.R-project.org/.
Skills for HW 5 - Part 2 and Project
Citing R packages
Type citation(‘package_name’) in the R console.
Replace
package_namewith name of package or package suite, e.g.tidyversewhich is a suite of packages.
citation('tidyverse')
tidyverse suite include:
forcats stringr dplyr
purrr readr
tidyr tibble ggplot2
tidyverse
To cite tidyverse:
Wickham H, Averick M, Bryan J, Chang W, McGowan LD, François R, Grolemund G, Hayes A, Henry L, Hester J, Kuhn M, Pedersen TL, Miller E, Bache SM, Müller K, Ooms J, Robinson D, Seidel DP, SpinuV, Takahashi K, Vaughan D, Wilke C, Woo K, Yutani H (2019). “Welcome to the tidyverse.” Journal of Open Source Software, 4(43), 1686. doi:10.21105/joss.01686
Skills for HW 5 - Part 2 and Project
Citing RStudio
- type
RStudio.Version()in the R console
RStudio.Version()
To cite RStudio:
RStudio Team (2022). RStudio: Integrated Development Environment for R. RStudio, PBC, Boston, MA URL http://www.rstudio.com/.
Inline R code (Required for project, not HW 5 - Part 2)
In your projects you are asked to include inline code in the text panels
This is a good skill to know when managing and curating data in R
It allows you to include R objects, variables, and calculations in text
Inline R code will automatically update when data or R code are updated.
To use inline code:
1.Calculate and format values in an R chunk that can be hidden usingecho = F2.Write text in your dashboard or report using inline chunk format.This ‘micro-chunk’ can include a saved value, a calculation, etc..
The ‘micro-chunk’ will not appear in your output document, and it will be replaced by the output value or calculation output you specify in the chunk.
R Inline Code and Example
The small chunk that follows imports a dataset and does some of the data management tasks we have covered to a dataset about yearly movie gross.
In a dashboard or report, this chunk could be hidden by including
echo = F in the chunk header.
# import and manage data to keep top movies from each year
bom_yr <- read_csv("bom_yearly_top_gross_2023_11_28.csv", show_col_types = F, skip=12) |>
filter(!is.na(Releases)) |> # remove rows with NAs
slice(1:15) |> # keep first 15 rows
rename("yr"="Year", "tot_gross" = "Total Gross", "num1" = "#1 Release") |>
select(yr, tot_gross, num1) |>
mutate(yr = as.integer(yr),
tot_gross = gsub("$", "", tot_gross, fixed = T),
tot_gross = as.numeric(gsub(",", "", tot_gross, fixed = T))) ## Warning in grep("^[.][.](?:[.]|[1-9][0-9]*)$", names): unable to translate
## '%<b1> LY' to a wide string## Warning in grep("^[.][.](?:[.]|[1-9][0-9]*)$", names): input string 3 is
## invalid# create variables for inline code
today <- Sys.Date() # saves today's date
today_fmt <- stamp("Saturday, January 1, 1999", quiet = T)(today) # formats date
# day_updated_fmt <-
yr_to_date_gross <- round(bom_yr$tot_gross[1]/1000000000,2) # formats & saves 1st gross
pct_of_prev <- round(bom_yr$tot_gross[1]/bom_yr$tot_gross[2]*100) # creates formatted ratio
pct_of_prev_more <- pct_of_prev - 100
tenyr_pp_avg <- mean(bom_yr$tot_gross[5:14])
pct_of_tenyr_pp_avg <- round((bom_yr$tot_gross[1]/tenyr_pp_avg)*100)R Inline Code Example
In a polished document, the previous chunk could be hidden, by using the
echo=Foption in the chunk header.The document itself could have the following text which could be updated daily:
As of Thursday, December 07, 2023, the top grossing film of this year is Barbie.
So far this year, the domestic total movie gross is 8.13 billion dollars.
This is already 10% more than last year’s total domestic movie gross.
In-class Exercise
1. In the previous chunk:
Create an additional formatted date value,
day_updated_fmtto indicate when data were updated. Data were updated on 11/28/2023,today.Calculate average of total gross for the ten years before the pandemic (2010 - 2019) and save this value as an object,
tenyr_pp_avg.Calculate the ratio of the current gross for 2023 divided by the ten year average, format ratio as was done for
pct_of_prev, and save this ratio aspct_of_tenyr_pp_age
2. Add more information to the text
above, including two additional ‘micro-chunks’ of inline R code. The
full text section to be completed is shown below.
3. Knit your class notes (.Rmd) so that
you have the final output as an html file and then save (print) it as a
pdf and submit it.
As of Thursday, December 07, 2023, the top grossing film of this year
is Barbie.
So far this year, the domestic total movie gross is 8.13 billion
dollars.
This total is already 10% more than last year’s total domestic movie
gross.
It is 74% of the pre-pandemic ten-year average of domestic annual
gross.
These data were last updated on Thursday, December 07, 2023 and can be
accessed
at this link.
Here is the data link:
https://www.boxofficemojo.com/year/?ref_=bo_nb_hm_secondarytab
Key Points from Today
Introduction of HW 5 - Part 2
- Due Wednesday, 12/6/23
- Discussion of Information Literacy
- Explanation of Assignment Tasks
- Review of adding linked text and images
Citations
Required in Project: Citing data sources, R, RStudio, R Packages
Required in HW 5 - Part 2: Citing data sources
Inline R code
- Required in Project
- Ideal for updating data information efficiently
- In-class exercise to practice
You may submit an ‘Engagement Question’ about each lecture until midnight on the day of the lecture. A minimum of four submissions are required during the semester.