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Review of the second day’s material

Luke Johnston

1 / 15
Aarhus University Danish Diabetes Academy

Version control with Git

2 / 15
Aarhus University Danish Diabetes Academy

Using Git, basic workflow

  • Version control is really important, but also difficult
  • Repository is all the files in a folder tracked by Git and saved as history in .git/
  • Files that are "tracked" will have changes recorded in history (when committed)
  • Commit small changes and commit often
3 / 15
Aarhus University Danish Diabetes Academy

Using Git, basic workflow

  • Version control is really important, but also difficult
  • Repository is all the files in a folder tracked by Git and saved as history in .git/
  • Files that are "tracked" will have changes recorded in history (when committed)
  • Commit small changes and commit often
  1. Start tracking new files (git add and git commit; "Stage" then "Commit")
  2. Check "status" of repository (git status, in Git tab)
  3. Add and commit modified files (git add and git commit; "Stage" then "Commit")
  4. Check what was recently done to the repo (git log; "History" tab in Git Interface)
  5. Synch with GitHub, if set up (git push to upload, git pull to download; "Push" or "Pull")
3 / 15
Aarhus University Danish Diabetes Academy

Data visualization with ggplot2

4 / 15
Aarhus University Danish Diabetes Academy

Final exercise: Code to create first plot

NHANES %>% 
    filter(!is.na(Diabetes)) %>% 
    ggplot(aes(y = BMI, x = Poverty, 
               colour = Diabetes)) + 
    geom_point(alpha = 0.4) + 
    geom_smooth(size = 2, method = "gam") +
    facet_grid(cols = vars(SurveyYr), 
               rows = vars(Gender)) +
    scale_color_viridis_d(end = 0.8) +
    theme_classic() +
    theme(
        strip.background = element_blank(),
        panel.background = 
            element_rect(fill = "grey95"),
        axis.line = 
            element_line(colour = "grey80")
    )

5 / 15
Aarhus University Danish Diabetes Academy

Final exercise: Remove NA and set base plot

NHANES %>% 
    filter(!is.na(Diabetes)) %>%
    ggplot(aes(y = BMI, x = Poverty,
               colour = Diabetes)) +
    geom_point(alpha = 0.4) + 
    geom_smooth(size = 2, method = "gam") +
    facet_grid(cols = vars(SurveyYr), 
               rows = vars(Gender)) +
    scale_color_viridis_d(end = 0.8) +
    theme_classic() +
    theme(
        strip.background = element_blank(),
        panel.background = 
            element_rect(fill = "grey95"),
        axis.line = 
            element_line(colour = "grey80")
    )

6 / 15
Aarhus University Danish Diabetes Academy

Final exercise: Add points and smooth geoms

NHANES %>% 
    filter(!is.na(Diabetes)) %>%
    ggplot(aes(y = BMI, x = Poverty, 
               colour = Diabetes)) + 
    geom_point(alpha = 0.4) +
    geom_smooth(size = 2, method = "gam") +
    facet_grid(cols = vars(SurveyYr), 
               rows = vars(Gender)) +
    scale_color_viridis_d(end = 0.8) +
    theme_classic() +
    theme(
        strip.background = element_blank(),
        panel.background = 
            element_rect(fill = "grey95"),
        axis.line = 
            element_line(colour = "grey80")
    )

7 / 15
Aarhus University Danish Diabetes Academy

Final exercise: Add column by row facets

NHANES %>% 
    filter(!is.na(Diabetes)) %>%
    ggplot(aes(y = BMI, x = Poverty, 
               colour = Diabetes)) + 
    geom_point(alpha = 0.4) + 
    geom_smooth(size = 2, method = "gam") +
    facet_grid(cols = vars(SurveyYr),
               rows = vars(Gender)) +
    scale_color_viridis_d(end = 0.8) +
    theme_classic() +
    theme(
        strip.background = element_blank(),
        panel.background = 
            element_rect(fill = "grey95"),
        axis.line = 
            element_line(colour = "grey80")
    )

8 / 15
Aarhus University Danish Diabetes Academy

Final exercise: Add colour scheme and set theme

NHANES %>% 
    filter(!is.na(Diabetes)) %>%
    ggplot(aes(y = BMI, x = Poverty, 
               colour = Diabetes)) + 
    geom_point(alpha = 0.4) + 
    geom_smooth(size = 2, method = "gam") +
    facet_grid(cols = vars(SurveyYr), 
               rows = vars(Gender)) +
    scale_color_viridis_d(end = 0.8) +
    theme_classic() +
    theme(
        strip.background = element_blank(),
        panel.background =
            element_rect(fill = "grey95"),
        axis.line =
            element_line(colour = "grey80")
    )

9 / 15
Aarhus University Danish Diabetes Academy

Final exercise: Code to create second plot

NHANES %>%
    filter(!is.na(Diabetes), 
           !is.na(Education)) %>%
    ggplot(aes(x = Education, 
               colour = Diabetes, 
               y = TotChol)) +
    geom_boxplot(fill = "grey90", 
                 outlier.size = 0.5, 
                 size = 0.75) +
    facet_grid(cols = vars(Gender)) +
    scale_color_brewer(type = "qual") +
    theme_minimal() +
    labs(y = "Total Cholesterol") +
    coord_flip()

10 / 15
Aarhus University Danish Diabetes Academy

Final exercise: Remove NA and set base

NHANES %>%
    filter(!is.na(Diabetes),
           !is.na(Education)) %>%
    ggplot(aes(x = Education,
               colour = Diabetes,
               y = TotChol)) +
    geom_boxplot(fill = "grey90", 
                 outlier.size = 0.5, 
                 size = 0.75) +
    facet_grid(cols = vars(Gender)) +
    scale_color_brewer(type = "qual") +
    theme_minimal() +
    labs(y = "Total Cholesterol") +
    coord_flip()

11 / 15
Aarhus University Danish Diabetes Academy

Final exercise: Add boxplot geom

NHANES %>%
    filter(!is.na(Diabetes), 
           !is.na(Education)) %>%
    ggplot(aes(x = Education, 
               colour = Diabetes, 
               y = TotChol)) +
    geom_boxplot(fill = "grey90",
                 outlier.size = 0.5,
                 size = 0.75) +
    facet_grid(cols = vars(Gender)) +
    scale_color_brewer(type = "qual") +
    theme_minimal() +
    labs(y = "Total Cholesterol") +
    coord_flip()

12 / 15
Aarhus University Danish Diabetes Academy

Final exercise: Add column facets

NHANES %>%
    filter(!is.na(Diabetes), 
           !is.na(Education)) %>%
    ggplot(aes(x = Education, 
               colour = Diabetes, 
               y = TotChol)) +
    geom_boxplot(fill = "grey90", 
                 outlier.size = 0.5, 
                 size = 0.75) +
    facet_grid(cols = vars(Gender)) +
    scale_color_brewer(type = "qual") +
    theme_minimal() +
    labs(y = "Total Cholesterol") +
    coord_flip()

13 / 15
Aarhus University Danish Diabetes Academy

Final exercise: Add colour scheme and set theme

NHANES %>%
    filter(!is.na(Diabetes), 
           !is.na(Education)) %>%
    ggplot(aes(x = Education, 
               colour = Diabetes, 
               y = TotChol)) +
    geom_boxplot(fill = "grey90", 
                 outlier.size = 0.5, 
                 size = 0.75) +
    facet_grid(cols = vars(Gender)) +
    scale_color_brewer(type = "qual") +
    theme_minimal() +
    labs(y = "Total Cholesterol") +
    coord_flip()

14 / 15
Aarhus University Danish Diabetes Academy

Final exercise: Flip the x and y axes

NHANES %>%
    filter(!is.na(Diabetes), 
           !is.na(Education)) %>%
    ggplot(aes(x = Education, 
               colour = Diabetes, 
               y = TotChol)) +
    geom_boxplot(fill = "grey90", 
                 outlier.size = 0.5, 
                 size = 0.75) +
    facet_grid(cols = vars(Gender)) +
    scale_color_brewer(type = "qual") +
    theme_minimal() +
    labs(y = "Total Cholesterol") +
    coord_flip()

15 / 15
Aarhus University Danish Diabetes Academy

Version control with Git

2 / 15
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