ggplot with a highcharts taste
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At work I use ggplot2 almost for everything. I really like the mid term between high level (highcharts) and low-level (like d3 for example). The deafult theme for ggplot it’s good, and really good if you compare with the old looking R base graphics, and there is more: the ggthemes package which have some themes for ggplot objects. However, I miss the elegant and modern touch, for example in highcharts.
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So I decide to play around the theme function to replicate the look and feel of highcharts. The main tasks were:
- Change the font to a more modern one.
- Remove grid lines (minor ones).
- Use a more plain color palette.
- Reduce the width of bars.
- Put a white background.
In the next images we can see some samples of this theme.
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As you can see, the plot look more clean without the gridlines and the background. This cause less confusion (and maybe less detail) because generate more space.
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Finally,
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In my humble option, it look great. What do you think? Here the R code to do the magic ;). The first part defines the theme and colors, the second one we make the plots.
data(diamonds) data <- subset(diamonds, color %in% c("E", "F", "G") & cut %in% c("Ideal", "Premium", "Good")) data$indicator <- ifelse(data$color %in% c("G" ), 1, 0) colors_hc <- c("#7CB5EC", "#313131", "#F7A35C", "#90EE7E", "#7798BF", "#AAEEEE", "#FF0066", "#EEAAEE", "#55BF3B", "#DF5353", "#7798BF", "#AAEEEE") font_import(paths="~/Downloads/open-sans/") loadfonts() fonts() theme_hc <- function(){ theme( text = element_text(family="Open Sans", size = 10), title = element_text(hjust=0), axis.title.x = element_text(hjust=.5), axis.title.y = element_text(hjust=.5), panel.grid.major.y = element_line(color='gray', size = .3), panel.grid.minor.y = element_blank(), panel.grid.major.x = element_blank(), panel.grid.minor.x = element_blank(), panel.border = element_blank(), panel.background = element_blank(), legend.position = "bottom", legend.title = element_blank() ) } p1 <- ggplot(data) + geom_bar(aes(cut), width =.4, fill = colors_hc[1]) + ggtitle("An interesting title for a bar plot") + xlab("Cut") + ylab("Amount") + scale_y_continuous(labels = comma) + theme_hc() p1 p2 <- ggplot(data) + geom_bar(aes(color, fill=cut), position="dodge", width=.4) + ggtitle("Another interesting title") + xlab("Cut") + ylab("Amount") + scale_y_continuous(labels = comma) + scale_fill_manual(values=colors_hc) + theme_hc() p2 p3 <- ggplot(data) + geom_density(aes(x, fill=cut, color=cut), alpha=I(0.5)) + ggtitle("Density plot") + xlab("x") + ylab("Density") + scale_y_continuous(labels = percent) + scale_fill_manual(values=colors_hc) + xlim(4, 8) + theme_hc() p3Bonustrack: More is less! This is a good lesson from Darkhorse Analytics.
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