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 / [e-mail] (example)
2. Kang, Eastern / [e-mail] (instructor)
3. Romstadt, Lisa / [e-mail]
4. Kazden, Matthew/[e-mail]
5. Yamada, Sohei / [e-mail]
6. Cho, Harrison / [e-mail]
7. Weitong Li / [e-mail]
8. Paula Jaramillo/ [e-mail]
9. Nakamura, Masaki / [e-mail]
10. Phrasavath, Bonaly / [e-mail]
11. Ilaria, Simmen/ [e-mail]
12. Hernandez, I
13. Lascano, Dayra / [e-mail]
14. Orosz, Stephanie / [e-mail]
15. Faiaz, Muhtadi / [e-mail]
16. Pykurel,Himanshu/ [e-mail],
17. Zhuohan, Fang / [e-mail]
18. Kato, Hiroaki / h
19. Nogueda,Lesley/ [e-mail]
20. Edwards, Lauryn/ [e-mail]
21. Berman-Schneider, Ray/ [e-mail]
22. Ye Yuan/ [e-mail]
23. Junyi Hua/[e-mail]
24. Cuevas, Christopher/[e-mail]
25. Tianning, Lan / [e-mail]
26. Coyle, Jackson / [e-mail]
27. Yamakawa, Daisuke / [e-mail]
28. Groper, Danielle / [e-mail]
29. Tsuru, Yutaro / [e-mail]
30. Jordan Chu / [e-mail]
31. Bo,Yutong/[e-mail]
32. Yamashita, Daichi / [e-mail]
33. Yamashita, Aoi / [e-mail]
34. Tan,Jingyi/ [e-mail]
35. Artan, Warsan / [e-mail]
36. Xuran, Wang / [e-mail]
37. Ito, Yoshi / [e-mail]
38. Chen, Wenxin / [e-mail]
39. Zhiyuan,Chi /[e-mail]
40. Yuxin Guo / [e-mail]
41. Leung, Taysia/ [e-mail] (Asynchronous Video)
42. Ahluwalia, Gurkriti / [e-mail]

Notes

You can use R as a calculator

Variables and assignments

use assignment operator <- to assign values to variables

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 / [e-mail] (example)
2. Phrasavath, Bonaly / [e-mail]
3. Hernandez, Isai / [e-mail]
4. Tianning, Lan / [e-mail]
5. Weitong Li / [e-mail]
6. Romstadt,Lisa / [e-mail]
7. Lascano, Dayra / [e-mail]
8. Yamada, Sohei / [e-mail]
9. Tsuru, Yutaro / [e-mail]
10. ilaria simmen / [e-mail]
11. Orosz, Stephanie/ [e-mail]
12. Lesley Nogueda / [e-mail]
13. Himanshu Pykurel/ [e-mail]
14. Xiangning Wu / [e-mail]
15. Nakamura, Masaki / [e-mail]
16. Cuevas, Christopher/[e-mail]
17. Yamashita, Daichi / [e-mail]
18. Tan,Jingyi /[e-mail]
19. Groper, Danielle / [e-mail]
20. Xuran, Wang / [e-mail]
21. Coyle, Jackson / [e-mail]
22. Artan, Warsan / [e-mail]
23. Yamakawa, Daisuke / [e-mail]
24. Ito, Yoshi / [e-mail]
25. Chen, Wenxin / [e-mail]
26. Tsuru, Yutaro / [e-mail]
27. Chu, Jordan / [e-mail]
28. Zhiyuan, Chi / [e-mail]
29. Yuxin Guo / [e-mail]
30. Leung, Taysia/ [e-mail] (Asynchronous Video)
31. Ahluwalia, Gurkriti / [e-mail]

Notes:

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

dir.create("data") # creating a directory

# creating a .csv file
write.csv(cats,
          file = "data/feline_data.csv", 
          row.names = FALSE)

# assigning feline_data.csv  to variable cats
cats <- write.csv(cats,
          file = "data/feline_data.csv", 
          row.names = FALSE)

cats$weight
cats$coat
cats$weight + 2

cats$weight_plus_2 <- cats$weight + 2

paste("My cat is", cats$coat)
View(cats)

cats$weight + cats$coat

5 main data types in R

• doulbe
• integer
• complex
• logical
• character

# 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:

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 / [e-mail] (example)
Nakamura, Masaki / [e-mail]
Yamada, Sohei / [e-mail]
Tianning, Lan / [e-mail]
Phrasavath, Bonaly / [e-mail]
Orosz, Stephanie / [e-mail]
Nogueda, Lesley/[e-mail]
Paula Jaramillo/[e-mail]
Pykurel, Himanshu/ [e-mail]
Cho, Harrison / [e-mail]
Artan, Warsan / [e-mail]
ilaria simmen
Lascano, Dayra / [e-mail]
Chen, Wenxin / [e-mail]
Groper, Danielle / [e-mail]
Coyle, Jackson / [e-mail]
Romstadt, Lisa / [e-mail]
Tsuru, Yutaro / [e-mail]
Cuevas, Christopher/[e-mail]
Xuran, Wang / [e-mail]
Chu, Jordan / [e-mail]
Yamakawa, Daisuke / [e-mail]
Zhiyuan, Chi / [e-mail]
Tan,Jingyi / [e-mail]
Yuxin Guo / [e-mail]
Leung, Taysia/ [e-mail] (Asynchronous Video)
Ahluwalia, Gurkriti / [e-mail]

---

Notes

importing data

# 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

str(gapminder)

class(gapminder$year)

nrow(gapminder)
ncol(gapminder)
dim(gapminder)

colnames(gapminder)
head(gapminder)

head(gapminder, n=10)

Challenge 1
answer:

# check the last few lines
tail(gapminder)
tail(gapminder, n=15)

#random rows
gapminder[sample(nrow(gapminder), 5),]

challenge 2
answer:

str(gapminder)

#selecting data by cutoff

below_average <- gapminder$lifeExp < 70.5
head(gapminder)

adding wrong length vector

below_average <- c(TRUE, TRUE, TRUE, TRUE)
head(cbind(gapminder, below_average))


below_average <- c(TRUE, FALSE, FALSE, TRUE)
head(cbind(gapminder, below_average))

#overwrite content with new data 

below_average <- as.logical(gapminder$lifeExp < 70.5)
below_average

gapminder <- cbind(gapminder, below_average)

add new row

new_row <- list('Norway', 2016, 500000, 'nordic', 80.3, 49400.0, FALSE)
new_row

factors

# makes continent a character 
gapminder$continent <- as.character(gapminder$continent)

str(gapminder)

dplyr

#installing packages:
install.packages("dplyr")

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 / [e-mail] (example)
2. Pykurel, Himanshu/ [e-mail]
3. Ilaria Simmen/ [e-mail]
4. Phrasavath, Bonaly / [e-mail]
5. Lascano, Dayra / [e-mail]
6. Nogueda, Lesley / [e-mail]
7. Tsuru, Yutaro / [e-mail]
8. Nakamura, Masaki / [e-mail]
9. Cuevas, Christopher/[e-mail]
10. Groper, Danielle / [e-mail]
11. Artan, Warsan / [e-mail]
12. Coyle, Jackson / [e-mail]
13. Xuran, Wang / [e-mail]
14. Chu, Jordan / [e-mail]
15. Zhiyuan, Chi / [e-mail]
16. Chen, Wenxin / [e-mail]
17. Tan, Jingyi / [e-mail]
18. Yuxin Guo / [e-mail]
19. Yamakawa, Daisuke / [e-mail]
20. Leung, Taysia/ [e-mail] (Asynchronous Video)
21. Ahluwalia, Gurkriti / [e-mail]

NOTES

# 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

install.packages("tidyverse", dependencies = TRUE)

library(tidyr)
library(dplyr)
library(tidyverse)

loading data

#assign data to gapminder variable
gapminder <- read.csv("data/gapminder_data.csv",
                      stringsAsFactors = FALSE)

gap_wide <- read.csv("data/gapminder_wide.csv", stringsAsFactors = FALSE)

converting wide to long format

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

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 / [e-mail] (example)
Nakamura, Masaki / [e-mail]
Phrasavath, Bonaly / [e-mail]
Lascano, Dayra / [e-mail]
Ye, Yuan / [e-mail]
Tianning , Lan / [e-mail]
Tsuru, Yutaro / [e-mail]
Chen, Wenxin / [e-mail]
Coyle, Jackson / [e-mail]
Tan, Jingyi/ [e-mail]
Groper, Danielle / [e-mail]
Artan, Warsan / [e-mail]
Cuevas, Christopher/[e-mail]
Xuran, Wang / [e-mail]
Yuxin Guo / [e-mail]
Yamakawa, Daisuke / [e-mail]
Leung, Taysia/ [e-mail] (Asynchronous Video)
Chu, Jordan / [e-mail]
Ahluwalia, Gurkriti / [e-mail]

notes

using ggplot

library("ggplot2")

ggplot(data= gapminder, aes(x= gdpPercap, y=lifeExp)) + 
  geom_point()

### challenge answer
ggplot(data= gapminder, aes(x= gdpPercap, y=lifeExp, color=continent)) + 
  geom_point()

layers

ggplot(gapminder, aes(x = year, y=lifeExp, color=continent)) +
  geom_line()

ggplot(gapminder, aes(x = year, y=lifeExp, color=continent, group = country)) +
  geom_line()

ggplot(gapminder, aes(x = year, y=lifeExp, color=continent, group = country)) +
  geom_line() + geom_point()

ggplot(gapminder, aes(x = year, y=lifeExp, group = country)) + 
  geom_line(aes(color=continent)) +
  geom_point()

# 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

ggplot(data = gapminder, aes(x= gdpPercap, y=lifeExp)) +
  geom_point(alpha=0.5) + 
  scale_x_log10()

changing alpha

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 

ggplot(data = gapminder, aes(x= gdpPercap, y=lifeExp)) +
  geom_point(aes(alpha=0.5)) + 
  scale_x_log10() +
  geom_smooth(method = "lm", size = 1.5)

#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) 

# 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

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

## 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 / [e-mail] (example)
Pykurel, Himanshu / [e-mail]
Lascano, Dayra / [e-mail]
Nogueda, Lesley /
[e-mail]
Nakamura, Masaki / [e-mail]
Phrasavath, Bonaly / [e-mail]
Tsuru, Yutaro / [e-mail]
Artan, Warsan / [e-mail]
Groper, Danielle / [e-mail]
Cuevas, Christopher/[e-mail]
Xuran, Wang / [e-mail]
Yuxin Guo / [e-mail]
Coyle, Jackson / [e-mail]
Chen, Wenxin / [e-mail]
Yamakawa, Daisuke / [e-mail]
Leung, Taysia/ [e-mail] (Asynchronous Video)
Chu, Jordan / [e-mail]
Ahluwalia, Gurkriti / [e-mail]

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 

use this google drive link to download the 'est.csv' file

https://drive.google.com/file/d/15ei1LmUURIvbJIjS9J-Y6qlyRx1jrpFB/view?usp=share_link

Notes

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

gap-to-plot <- gapminder 

est <- read_csv("data/countries_estimated.csv/")

Session 6 Questions:

Please enter any questions not answered during live session here:
1.

End Day 6