Welcome to data visualization best practices in R Nick Strayer - - PowerPoint PPT Presentation

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welcome to data visualization best practices in r

Welcome to data visualization best practices in R Nick Strayer - - PowerPoint PPT Presentation

Jun 26, 2023 225 likes •467 views

DataCamp Visualization Best Practices in R VISUALIZATION BEST PRACTICES IN R Welcome to data visualization best practices in R Nick Strayer Instructor DataCamp Visualization Best Practices in R What is this course? What you will learn How

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DataCamp Visualization Best Practices in R

Welcome to data visualization best practices in R

VISUALIZATION BEST PRACTICES IN R

Nick Strayer

Instructor

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DataCamp Visualization Best Practices in R

What is this course?

What you will learn How to make better visualizations by thinking deeply about the data at hand. How you will learn it Overviews of different data types Standard visualizations Alternatives

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Course layout

Ch1 Proportions of a whole Ch2 Point data Ch3 Single distributions Ch4 Multiple(or conditional) distributions

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Warning!

Topics here are not as cut and dry as

ther programming topics

Every rule will have exceptions An emphasis on thinking through each problem is given to help you deal with these cases when you get to them

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DataCamp Visualization Best Practices in R

Tools used

R The 'Tidyverse' Ggplot2

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Data used

Comes from the World Health Organization (WHO)

> who_disease # A tibble: 43,262 x 6 region countryCode country disease year cases <chr> <chr> <chr> <chr> <int> <dbl> 1 EMR AFG Afghanistan measles 2016 638 2 EUR ALB Albania measles 2016 17.0 3 AFR DZA Algeria measles 2016 41.0 4 EUR AND Andorra measles 2016 0 5 AFR AGO Angola measles 2016 53.0 6 AMR ATG Antigua and Barbuda measles 2016 0 7 AMR ARG Argentina measles 2016 0 8 EUR ARM Armenia measles 2016 2.00 9 WPR AUS Australia measles 2016 99.0 10 EUR AUT Austria measles 2016 27.0 # ... with 43,252 more rows

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WHO disease data

# filter to AMR region. amr_region <- who_disease %>% filter(region == 'AMR') # map x to year and y to cases, color by disease. ggplot(amr_region, aes(x = year, y = cases, color = disease)) + geom_point(alpha = 0.5)

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Let's practice!

VISUALIZATION BEST PRACTICES IN R

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DataCamp Visualization Best Practices in R

Proportions of a single population

VISUALIZATION BEST PRACTICES IN R

Nick Strayer

Instructor

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DataCamp Visualization Best Practices in R

What is a proportion?

Parts making up a whole Often used to understand population

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The pie chart

Often the first technique people learn Also, the first technique people learn to dislike Dislike is not entirely warranted

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A sour pie

Pie charts are not very precise data encoded in angles Doesn't handle lots of classes well After three slices it becomes hard to compare

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A sweet pie

Intuitive and compact

who_disease %>% mutate( region = ifelse( region %in% c('EUR', 'AFR'), region, 'Other') ) %>% ggplot(aes(x = 1, fill = region)) + geom_bar(color = 'white') + coord_polar(theta = "y") + theme_void()

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The waffle chart

More precise than pie charts Encode data in area, not angles

bs_by_region <- who_disease %>%

group_by(region) %>% summarise(num_obs = n()) %>% mutate(percent = round(num_obs/sum(num_obs)*100)) # Array of rounded percentages percent_by_region <- obs_by_region$percent names(percent_by_region) <- obs_by_region$region # Send array of percentages to waffle plot function waffle::waffle(percent_by_region, rows = 5)

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Let's practice!

VISUALIZATION BEST PRACTICES IN R

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Comparing multiple populations

VISUALIZATION BEST PRACTICES IN R

Nick Strayer

Instructor

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Why not use faceting?

Almost impossible to compare

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The stacked bar chart

Allow each population to share the same y-axis Enables easier comparisons based on vertical position/size

who_disease %>% filter(region == 'SEAR') %>% ggplot(aes(x = countryCode, y = cases, fill = disease)) + geom_col(position = 'fill')

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Caveats

Worse in isolation than pie or waffle charts Accuracy degrades rapidly after 3 classes

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Chapter recap

Proportions: Pie Charts: Waffle Charts: Stacked Bars:

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Let's practice!

VISUALIZATION BEST PRACTICES IN R