GPS Skills Course Series - R (2023Winter)

--- tags: gps --- # GPS Skills Course Series - R (2023Winter) **Course Details** Dates: January 30th, 2023 - February 17th, 2023 Days: Tuesday/Thursday Time: 2-3:20pm **Course Agenda:** (Github page) **Software Installation:** *Refer to Canvas course software download files. **Lesson Data (download)** *Refer to Canvas course data download files. ## NOTES: A copy of the instructor live session notes will be uploaded in canvas at the end of session lesson. ~~*(Include only for Python course)* Jupyterlab will be used for the lessons [m] Markdown cell = notes [#]also works in code cell for notes [b] = add cell below [a] is above [r]Raw cells cannot have text edits~~ https://www.markdownguide.org/getting-started/ https://www.markdownguide.org/basic-syntax/ *End* ## Session 1 ### Name (Last, First) / Email 1. Doe, John / jdoe@ucsd.edu (example) 2. Kang, Eastern / dkangsim@health.ucsd.edu (instructor) 3. Romstadt, Lisa / lromstadt@ucsd.edu 4. Kazden, Matthew/mkazden@ucsd.edu 5. Yamada, Sohei / syamada@ucsd.edu 6. Cho, Harrison / hhc002@ucsd.edu 7. Weitong Li / wel056@ucsd.edu 8. Paula Jaramillo/ pjaramillo@ucsd.edu 9. Nakamura, Masaki / m1nakamura@ucsd.edu 10. Phrasavath, Bonaly / bphrasav@ucsd.edu 11. Ilaria, Simmen/ ismmen@ucsd.edu 12. Hernandez, I 13. Lascano, Dayra / dlascano@ucsd.edu 14. Orosz, Stephanie / sorosz@ucsd.edu 15. Faiaz, Muhtadi / mfaiaz@ucsd.edu 16. Pykurel,Himanshu/ Hpykurel@ucsd.edu, 17. Zhuohan, Fang / zhf003@ucsd.edu 18. Kato, Hiroaki / h 19. Nogueda,Lesley/ lnogueda@ucsd.edu 20. Edwards, Lauryn/ ltedward@ucsd.edu 21. Berman-Schneider, Ray/ raybscneid@gmail.com 22. Ye Yuan/ yeyuan@ucsd.edu 23. Junyi Hua/juhua@ucsd.edu 24. Cuevas, Christopher/ccuevas@ucsd.edu 25. Tianning, Lan / tilan@ucsd.edu 26. Coyle, Jackson / jacoyle@ucsd.edu 27. Yamakawa, Daisuke / dayamakawa@ucsd.edu 28. Groper, Danielle / dgroper@ucsd.edu 29. Tsuru, Yutaro / ytsuru@ucsd.edu 30. Jordan Chu / j1chu@ucsd.edu 31. Bo,Yutong/yubo@ucsd.edu 32. Yamashita, Daichi / dyamashita@ucsd.edu 33. Yamashita, Aoi / aoyamashita@ucsd.edu 34. Tan,Jingyi/ j3tan@ucsd.edu 35. Artan, Warsan / wartan@ucsd.edu 36. Xuran, Wang / xuw028@ucsd.edu 37. Ito, Yoshi / yoito@ucsd.edu 38. Chen, Wenxin / wec027@ucsd.edu 39. Zhiyuan,Chi /z1chi@ucsd.edu 40. Yuxin Guo / yug041@ucsd.edu 41. Leung, Taysia/ t3leung@ucsd.edu (Asynchronous Video) 42. Ahluwalia, Gurkriti / gahluwalia@ucsd.edu ## Notes #### You can use R as a calculator #### Variables and assignments use assignment operator `<-` to assign values to variables ```r= x <- 1/40 x_2 <- x*2 # try to use unique variables names df <- x*2 rm(x) # delete variable ?rm() # use ? and function to get help in RStudio ``` ## Session 1 Questions: Please enter any questions not answered during live session here: 1. ### End Session 1 ## Session 2 ### Name (Last, First) / Email 1. Doe, John / jdoe@ucsd.edu (example) 2. Phrasavath, Bonaly / bphrasav@ucsd.edu 3. Hernandez, Isai / i4hernandez@ucsd.edu 4. Tianning, Lan / tilan@ucsd.edu 5. Weitong Li / wel056@ucsd.edu 6. Romstadt,Lisa / lromstadt@ucsd.edu 7. Lascano, Dayra / dlascano@ucsd.edu 8. Yamada, Sohei / syamada@ucsd.edu 9. Tsuru, Yutaro / ytsuru@ucs.edu 10. ilaria simmen / isimmen@oxy.edu 11. Orosz, Stephanie/ sorosz@ucsd.edu 12. Lesley Nogueda / lnogueda@ucsd.edu 13. Himanshu Pykurel/ hpykurel@ucsd.edu 14. Xiangning Wu / xiw138@ucsd.edu 15. Nakamura, Masaki / m1nakamura@ucsd.edu 16. Cuevas, Christopher/ccuevas@ucsd.edu 17. Yamashita, Daichi / dyamashita@ucsd.edu 18. Tan,Jingyi /j3tan@ucsd.edu 19. Groper, Danielle / dgroper@ucsd.edu 20. Xuran, Wang / xuw028@ucsd.edu 21. Coyle, Jackson / jacoyle@ucsd.edu 22. Artan, Warsan / wartan@ucsd.edu 23. Yamakawa, Daisuke / dayamakawa@ucsd.edu 24. Ito, Yoshi / yoito@ucsd.edu 25. Chen, Wenxin / wec027@ucsd.edu 26. Tsuru, Yutaro / ytsuru@ucsd.edu 27. Chu, Jordan / j1chu@ucsd.edu 28. Zhiyuan, Chi / z1chi@ucsd.edu 29. Yuxin Guo / yug041@ucsd.edu 30. Leung, Taysia/ t3leung@ucsd.edu (Asynchronous Video) 31. Ahluwalia, Gurkriti / gahluwalia@ucsd.edu ## Notes: ```r= coat <- ("calico", "black", "tabby") weight <- c(2.1,5.0, 3.2) likes_string <- c(1,0,1) ``` creating a csv and saving in a data folder ```r= dir.create("data") # creating a directory # creating a .csv file write.csv(cats, file = "data/feline_data.csv", row.names = FALSE) ``` ```r= # assigning feline_data.csv to variable cats cats <- write.csv(cats, file = "data/feline_data.csv", row.names = FALSE) ``` ```r= cats$weight cats$coat cats$weight + 2 ``` ```r= cats$weight_plus_2 <- cats$weight + 2 ``` ```r= paste("My cat is", cats$coat) View(cats) ``` ```r= cats$weight + cats$coat ``` ### 5 main data types in R - doulbe - integer - complex - logical - character ```r= # use typeof() to find data type Typeof("cats$weight") ``` --- ############################## ### Quick clarification for converting variable types. Suppose you have a mixed variable type recorded as presented in the class: ```r= weight<- c(2.1,5.0, 3.2, "a") ``` R is going to recognize that as `character type` because of "a". If you import the csv file with this type of mixed variable types, and if you use the option `stringAsFactors = TRUE`, then your `character type` of variable will be recognized as `factor`, which is equivalent to `integer type` of variable. We can convert the `weight` back to `numeric type` using the `as.numeric()` function, but because R recognizes the `weight` variable as factor, the converted output would be 1, 2, 3, in increasing order. For our example, 2.1 = 1, 3.2 = 2, 5.0 = 3, and "a" = 4. However, if you selected `stringAsFactros = FALSE` option, then R recognizes the weight variable as `character type`, and converting that variable to numeric would produce `NA` for mismatching type. Please see table for a brief summary: | | Original data | Converted using `as.numeric()` | | -------- | -------- | -------- | | when string is factor | (2.1, 5.0, 3.2, "a") | (1, 3, 2, 4) | | when string is character| (2.1, 5.0, 3.2, "a") | (2.1, 5.0, 3.2, NA)| --- ## Session 2 Questions: Please enter any questions not answered during live session here: 1. ### End Session 2 --- ## Session 3 ### Name (Last, First) / Email Doe, John / jdoe@ucsd.edu (example) Nakamura, Masaki / m1nakamura@ucsd.edu Yamada, Sohei / syamada@ucsd.edu Tianning, Lan / tilan@ucsd.edu Phrasavath, Bonaly / bphrasav@ucsd.edu Orosz, Stephanie / sorosz@ucsd.edu Nogueda, Lesley/lnogueda@ucsd.edu Paula Jaramillo/pjaramillo@ucsd.edu Pykurel, Himanshu/ hpykurel@ucsd.edu Cho, Harrison / hhc002@ucsd.edu Artan, Warsan / wartan@ucsd.edu ilaria simmen Lascano, Dayra / dlascano@ucsd.edu Chen, Wenxin / wec027@ucsd.edu Groper, Danielle / dgroper@ucsd.edu Coyle, Jackson / jacoyle@ucsd.edu Romstadt, Lisa / lromstadt@ucsd.edu Tsuru, Yutaro / ytsuru@ucsd.edu Cuevas, Christopher/ccuevas@ucsd.edu Xuran, Wang / xuw028@ucsd.edu Chu, Jordan / j1chu@ucsd.edu Yamakawa, Daisuke / dayamakawa@ucsd.edu Zhiyuan, Chi / z1chi@ucsd.edu Tan,Jingyi / j3tan@ucsd.edu Yuxin Guo / yug041@ucsd.edu Leung, Taysia/ t3leung@ucsd.edu (Asynchronous Video) Ahluwalia, Gurkriti / gahluwalia@ucsd.edu **** # Notes ## importing data ```r= # download data directly from a link. # download.file("https://raw.githubusercontent.com/datacarpentry/r-intro-geospatial/master/_episodes_rmd/data/gapminder_data.csv", destfile = "data/gapminder_data.csv") #make sure to have the "data" file in your Rstudio working directory ``` # exploring data ```r= str(gapminder) class(gapminder$year) nrow(gapminder) ncol(gapminder) dim(gapminder) colnames(gapminder) head(gapminder) head(gapminder, n=10) ``` Challenge 1 answer: ```r= # check the last few lines tail(gapminder) tail(gapminder, n=15) #random rows gapminder[sample(nrow(gapminder), 5),] ``` challenge 2 answer: ```r= str(gapminder) ``` #selecting data by cutoff ```r= below_average <- gapminder$lifeExp < 70.5 head(gapminder) ``` adding wrong length vector ```r= below_average <- c(TRUE, TRUE, TRUE, TRUE) head(cbind(gapminder, below_average)) below_average <- c(TRUE, FALSE, FALSE, TRUE) head(cbind(gapminder, below_average)) ``` ```r= #overwrite content with new data below_average <- as.logical(gapminder$lifeExp < 70.5) below_average gapminder <- cbind(gapminder, below_average) ``` # add new row ```r= new_row <- list('Norway', 2016, 500000, 'nordic', 80.3, 49400.0, FALSE) new_row ``` # factors ```r= # makes continent a character gapminder$continent <- as.character(gapminder$continent) str(gapminder) ``` # dplyr ```r= #installing packages: install.packages("dplyr") ``` ```r= library(dplyr) year_country_gdp <- select(gapminder, year, country, gdpPercap) head(year_country_gdp) year_country_gdp <- gapminder %>% select(year, country, gdpPercap) year_country_gdp_euro <- gapminder %>% filter(continent == "Europe") %>% select(year, country, gdpPercap) ``` ## Session 3 Questions: Please enter any questions not answered during live session here: 1. ### End Session 3 ## Session 4 ### Name (Last, First) / Email 1. Doe, John / jdoe@ucsd.edu (example) 2. Pykurel, Himanshu/ hpykurel@ucsd.edu 3. Ilaria Simmen/ isimmen@ucsd.edu 4. Phrasavath, Bonaly / bphrasav@ucsd.edu 5. Lascano, Dayra / dlascano@ucsd.edu 6. Nogueda, Lesley / lnogueda@ucsd.edu 8. Tsuru, Yutaro / ytsuru@ucsd.edu 9. Nakamura, Masaki / m1nakamura@ucsd.edu 10. Cuevas, Christopher/ccuevas@ucsd.edu 11. Groper, Danielle / dgroper@ucsd.edu 12. Artan, Warsan / wartan@ucsd.edu 13. Coyle, Jackson / jacoyle@ucsd.edu 14. Xuran, Wang / xuw028@ucsd.edu 15. Chu, Jordan / j1chu@ucsd.edu 16. Zhiyuan, Chi / z1chi@ucsd.edu 17. Chen, Wenxin / wec027@ucsd.edu 18. Tan, Jingyi / j3tan@ucsd.edu 19. Yuxin Guo / yug041@ucsd.edu 20. Yamakawa, Daisuke / dayamakawa@ucsd.edu 21. Leung, Taysia/ t3leung@ucsd.edu (Asynchronous Video) 22. Ahluwalia, Gurkriti / gahluwalia@ucsd.edu ### _NOTES_ ```r= # download data directly from a link. # download.file("https://raw.githubusercontent.com/datacarpentry/r-intro-geospatial/master/_episodes_rmd/data/gapminder_data.csv", destfile = "data/gapminder_data.csv") #make sure to have the "data" file in your Rstudio working directory # downlod `gapminder_wide` data from a link. download.file("https://raw.githubusercontent.com/swcarpentry/r-novice-gapminder/gh-pages/_episodes_rmd/data/gapminder_wide.csv", destfile = "data/gapminder_wide.csv") ``` ### loading libraries ```r= install.packages("tidyverse", dependencies = TRUE) library(tidyr) library(dplyr) library(tidyverse) ``` ### loading data ```r= #assign data to gapminder variable gapminder <- read.csv("data/gapminder_data.csv", stringsAsFactors = FALSE) ``` ```r= gap_wide <- read.csv("data/gapminder_wide.csv", stringsAsFactors = FALSE) ``` ### converting wide to long format ```r= gap_long <- gap_wide %>% pivot_longer( cols = c(starts_with('pop'), starts_with('lifeExp'), starts_with('gdpPercap')), names_to = "obstype_year", values_to = "obs_values" ) View(gap_long) #to view the data ``` ```r= gap_long$year <- as.integer(gap_long$year) gap_long <- gap_long %>% separate(obstype_year, into = c('obs_type', 'year'), sep = "_") gap_long$year <- as.integer(gap_long$year) View(gap_long) ``` ## Session 4 Questions: Please enter any questions not answered during live session here: 1. ### End Day 4 ## Session 5 ### Name (Last, First) / Email Doe, John / jdoe@ucsd.edu (example) Nakamura, Masaki / m1nakamura@ucsd.edu Phrasavath, Bonaly / bphrasav@ucsd.edu Lascano, Dayra / dlascano@ucsd.edu Ye, Yuan / yeyuan@ucsd.edu Tianning , Lan / tilan@ucsd.edu Tsuru, Yutaro / ytsuru@ucsd.edu Chen, Wenxin / wec027@ucsd.edu Coyle, Jackson / jacoyle@ucsd.edu Tan, Jingyi/ j3tan@ucsd.edu Groper, Danielle / dgroper@ucsd.edu Artan, Warsan / wartan@ucsd.edu Cuevas, Christopher/ccuevas@ucsd.edu Xuran, Wang / xuw028@ucsd.edu Yuxin Guo / yug041@ucsd.edu Yamakawa, Daisuke / dayamakawa@ucsd.edu Leung, Taysia/ t3leung@ucsd.edu (Asynchronous Video) Chu, Jordan / j1chu@ucsd.edu Ahluwalia, Gurkriti / gahluwalia@ucsd.edu # notes ## using ggplot ```r= library("ggplot2") ``` ```r= ggplot(data= gapminder, aes(x= gdpPercap, y=lifeExp)) + geom_point() ``` ```r= ### challenge answer ggplot(data= gapminder, aes(x= gdpPercap, y=lifeExp, color=continent)) + geom_point() ``` ## layers ```r= ggplot(gapminder, aes(x = year, y=lifeExp, color=continent)) + geom_line() ``` ```r= ggplot(gapminder, aes(x = year, y=lifeExp, color=continent, group = country)) + geom_line() ``` ```r= ggplot(gapminder, aes(x = year, y=lifeExp, color=continent, group = country)) + geom_line() + geom_point() ``` ```r= ggplot(gapminder, aes(x = year, y=lifeExp, group = country)) + geom_line(aes(color=continent)) + geom_point() ``` ```r= # challenge: switch geom_line() and geom_point() # challenge answer ggplot(gapminder, aes(x = year, y=lifeExp, group = country)) + geom_point() + geom_line(aes(color=continent)) ``` ## transformation and stats ```r= ggplot(data = gapminder, aes(x= gdpPercap, y=lifeExp)) + geom_point(alpha=0.5) + scale_x_log10() ``` ### changing alpha ```r= ggplot(data = gapminder, aes(x= gdpPercap, y=lifeExp)) + geom_point(aes(alpha=continent)) + scale_x_log10() # you will see a warning, but the plot still works ``` ```r= ggplot(data = gapminder, aes(x= gdpPercap, y=lifeExp)) + geom_point(aes(alpha=0.5)) + scale_x_log10() + geom_smooth(method = "lm", size = 1.5) ``` ```r= #challenge answer ggplot(data = gapminder, aes(x= gdpPercap, y=lifeExp)) + geom_point(aes(alpha=0.5, color="orange")) + scale_x_log10() + geom_smooth(method = "lm", size = 1.5) ``` ```r= # challenge answer ggplot(data = gapminder, aes(x= gdpPercap, y=lifeExp, color=continent)) + geom_point(aes(shape=continent)) + scale_x_log10() + geom_smooth(method = "lm", size = 1.5) ``` #multi-pannel figures using face-wrap ```r= americas <- gapminder[gapminder$continent == "Americas",] ggplot(americas, aes(x=year, y=lifeExp)) + geom_line() + facet_wrap(~country) + theme(axis.text.x = element_text(angle = 45, hjust =1 )) + labs(x="year", y="life Expectancy", title="figure 1", color= "continent") ``` useful ggplot cheatsheet: https://statsandr.com/blog/files/ggplot2-cheatsheet.pdf ```r= ## challenge ggplot(gapminder, aes(x=continent, y=lifeExp, fill=continent)) + geom_boxplot() + facet_wrap(~year) + ylab("life Expentancy") + theme(axis.title.x = element_blank(), axis.text.x = element_blank(), axis.ticks.x = element_blank()) ``` ## Session 5 Questions: Please enter any questions not answered during live session here: 1. ### End Day 5 ## Session 6 ### Name (Last, First) / Email Doe, John / jdoe@ucsd.edu (example) Pykurel, Himanshu / hpykurel@ucsd.edu Lascano, Dayra / dlascano@ucsd.edu Nogueda, Lesley / lnogueda@ucsd.edu Nakamura, Masaki / m1nakamura@ucsd.edu Phrasavath, Bonaly / bphrasav@ucsd.edu Tsuru, Yutaro / ytsuru@ucsd.edu Artan, Warsan / wartan@ucsd.edu Groper, Danielle / dgroper@ucsd.edu Cuevas, Christopher/ccuevas@ucsd.edu Xuran, Wang / xuw028@ucsd.edu Yuxin Guo / yug041@ucsd.edu Coyle, Jackson / jacoyle@ucsd.edu Chen, Wenxin / wec027@ucsd.edu Yamakawa, Daisuke / dayamakawa@ucsd.edu Leung, Taysia/ t3leung@ucsd.edu (Asynchronous Video) Chu, Jordan / j1chu@ucsd.edu Ahluwalia, Gurkriti / gahluwalia@ucsd.edu ### download data directly from a link. ``` r= download.file("https://raw.githubusercontent.com/datacarpentry/r-intro-geospatial/master/_episodes_rmd/data/gapminder_data.csv", destfile = "data/gapminder_data.csv") #make sure to have the "data" file in your Rstudio working directory ``` ### use this google drive link to download the 'est.csv' file ``` https://drive.google.com/file/d/15ei1LmUURIvbJIjS9J-Y6qlyRx1jrpFB/view?usp=share_link ``` ### Notes ```r= library(tidyverse) # read in gapminder data #source("filename.R") # running a group of functions stored in another .r file source("programming-with-r.R") # useful for importing data sets and creating a R pipeline ``` ### using .rmd rnotebook Create and rnotebook file: file menu/new file/r notebook #filter the country to plot ```r= gap-to-plot <- gapminder ``` ```r= est <- read_csv("data/countries_estimated.csv/") ``` ## Session 6 Questions: Please enter any questions not answered during live session here: 1. ### End Day 6

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