8000 ci fix · plotly/plotly.r-docs@dce13a9 · GitHub
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mahdis-z
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ci fix
1 parent 9f5fbef commit dce13a9

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‎ggplot2/2019-07-30-geom_text.Rmd

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Original file line numberDiff line numberDiff line change
@@ -24,7 +24,7 @@ recent_turnout <- read.csv("https://raw.githubusercontent.com/plotly/datasets/ma
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recent_turnout$region <- factor(recent_turnout$region, levels=c("British","Northern","Western","Mediterranean","Central/Eastern"))
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library(plotly)
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fig <- recent_turnout %>%
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p <- recent_turnout %>%
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ggplot(aes(x=nat_turnout,y=euro_turnout)) +
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geom_text(aes(size=population/3.5, label=abbreviation, colour=region), alpha=1) +
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labs(title = "Recent turnout in European Union countries",
@@ -45,7 +45,7 @@ recent_turnout <- read.csv("https://raw.githubusercontent.com/plotly/datasets/ma
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recent_turnout$region <- factor(recent_turnout$region, levels=c("British","Northern","Western","Mediterranean","Central/Eastern"))
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library(plotly)
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fig <- recent_turnout %>%
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p <- recent_turnout %>%
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ggplot(aes(x=nat_turnout,y=euro_turnout)) +
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geom_point(aes(size=population, colour=region, text=paste("country:", country)), alpha=0.4) +
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geom_text(aes(size=population/3.5, label=abbreviation), colour="gray20", alpha=1) +
@@ -66,7 +66,7 @@ recent_turnout$region <- factor(recent_turnout$region, levels=c("British","North
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library(plotly)
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library(LaCroixColoR)
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fig <- recent_turnout %>%
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p <- recent_turnout %>%
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ggplot(aes(x=nat_turnout,y=euro_turnout)) +
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geom_point(aes(size=population, colour=region, text=paste("country:", country)), alpha=0.4) +
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geom_text(aes(size=population/3.5, label=abbreviation), colour="gray20", alpha=1) +
@@ -90,7 +90,7 @@ m <- lm(euro_turnout ~ nat_turnout, data = recent_turnout)
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library(plotly)
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library(LaCroixColoR)
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fig <- recent_turnout %>%
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p <- recent_turnout %>%
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ggplot(aes(x=nat_turnout,y=euro_turnout)) +
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stat_smooth(geom="line", method="lm", alpha=0.3, se=FALSE) +
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geom_point(aes(size=population, colour=region, text=paste("country:", country)), alpha=0.4) +
@@ -119,7 +119,7 @@ m <- lm(euro_turnout ~ nat_turnout, data = recent_turnout)
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library(plotly)
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library(LaCroixColoR)
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fig <- recent_turnout %>%
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p <- recent_turnout %>%
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ggplot(aes(x=nat_turnout,y=euro_turnout)) +
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stat_smooth(geom="line", method="lm", alpha=0.3, se=FALSE) +
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geom_point(aes(size=population, colour=region, text=paste("country:", country)), alpha=0.4) +

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