In Part IV Jonathan created a chart. In today’s installment of this series, he shows us how to wrap that chart in a call to
ggplotly() and get part of that functionality out of the box.
We will need to add the legend back to the plot by removing
legend.position = "none".
library(plotly) ggplotly( nasdaq_dividends %>% filter(symbol != "MACK" & symbol != "FWP") %>% group_by(symbol) %>% ggplot(aes(x = date, y = dividends, color = symbol)) + geom_point() + scale_y_continuous(labels = scales::dollar) + scale_x_date(breaks = scales::pretty_breaks(n = 10)) + labs(x = "", y = "div/share", title = "Nasdaq dividends") + theme(plot.title = element_text(hjust = 0.5)) )
Visit the blog to download the R code or to explore the interactive version of the above chart: http://www.reproduciblefinance.com/2019/08/25/tech-dividends/ Hover on that orange-red dot between $5 and $7 and notice it’s the symbol ATAI. If you double click on ATAI in the legend, it will isolate just those dots on the chart. And we can see that this was probably a special dividend.
Now, it might be nice to have the name of the company and the sector displayed when we mouse hover, instead of just the symbol.
In the next installment of this series, Jonathan will add back the name and sector data by
left_join()ing our wrangled data object.
The required packages and data preparation scripts are available in Part I, and Part II of this series. In Part III Jonathan worked with data for MACK and FWP dividends.
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