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AMOUNTS
MPA 635: Data Visualization September 25, 2018
AMOUNTS MPA 635: Data Visualization September 25, 2018 P L A N F - - PowerPoint PPT Presentation
AMOUNTS MPA 635: Data Visualization September 25, 2018 P L A N F - - PowerPoint PPT Presentation
AMOUNTS MPA 635: Data Visualization September 25, 2018 P L A N F O R T O D A Y More on truth Amounts Verbs Live example M O R E O N T R U T H D A T A A N D W H I T E L I E S I secretly wonder if I'm a righteous dude, is it OK
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M O R E O N T R U T H
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D A T A A N D W H I T E L I E S “I secretly wonder if I'm a righteous dude, is it OK for me to sort of maybe possibly mislead people so they pursue a more righteous policy?”
Anonymous MPA 635 student
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I S N U D G I N G O K A Y ?
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W H O D E F I N E S “ G O O D ” ?
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D O N ’ T M E S S W I T H D A T A
You can push people towards policy outcomes, but don't distort data to do it. “Lies, damned lies, and statistics”
↑ Don’t perpetuate this ↑
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A M O U N T S
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P R O B L E M S W I T H B A R P L O T S
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# b a r b a r p l o t s
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B A R P L O T S A N D S U M M A R Y S T A T S
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G E N E R A L R U L E S
More data = better Show actual points Don’t use bars for summary stats The end of the bar is
- ften all that matters
Lollipops, points, heatmaps Counts okay, but there are better solutions Always start at zero!
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V E R B S
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M O S T C O M M O N V E R B S filter()
Choose rows based on conditions
select()
Choose (and rename) columns
mutate()
Add column (or change existing column)
group_by()
Make subgroups based on a column
summarize()
Calculate summary statistics for groups
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F I LT E R
gapminder %>% filter(year == 1967)
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F I LT E R
gapminder %>% filter(lifeExp < 40)
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F I LT E R
gapminder %>% filter(continent == "Asia", lifeExp < 40)
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S E L E C T
gapminder %>% select(country, year, pop)
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M U T A T E
gapminder %>% mutate(something_new = 5)
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M U T A T E
gapminder %>% mutate(pop_million = pop / 1000000)
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M U T A T E
gapminder %>% mutate(lifeExp_binary = ifelse(lifeExp < 40, "Very low", "Not very low"))
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G R O U P _ B Y + S U M M A R I Z E
gapminder %>% group_by(continent) %>% summarize(avg_lifeexp = mean(lifeExp), median_lifeexmp = median(lifeExp), num_countries = n())
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G R O U P _ B Y + S U M M A R I Z E
gapminder %>% group_by(continent, year) %>% summarize(avg_lifeexp = mean(lifeExp), median_lifeexmp = median(lifeExp), num_countries = n())
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O T H E R H E L P F U L V E R B S arrange()
Sort a data frame by a column
left_join()
Merge two data frames by column(s)
count()
group_by() %>% summarize(n = n())
gather()
Make a data frame long
spread()
Make a data frame wide
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