For required packages and data preparation scripts see the previous installments in this series here: Part I, Part II, Part III, Part IV, Part V, and Part VI.
We will use mutate to create a new column that holds our label information. I want to display the date, company and symbol on different lines, so will include line breaks with <br>.
ggplotly(
nasdaq_dividends %>%
filter(symbol != "MACK" & symbol != "FWP") %>%
left_join(nasdaq_wrangled, by = "symbol") %>%
group_by(symbol) %>%
mutate(info = paste(date,
'<br>company:', company,
'<br>symbol:', symbol,
'<br>div: $', dividends)) %>%
ggplot(aes(x = date,
y = dividends,
color = symbol,
label_tooltip = info)) +
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)),
tooltip = "label_tooltip"
)
Visit the blog to explore the interactive version of the above chart and download the R code: http://www.reproduciblefinance.com/2019/08/25/tech-dividends/
Note how we can quickly add other information, like the sector, by adding the column sector to the paste string. Indeed, we can paste any column data into that string. There might be a better way to customize the tooltip in plotly – and suggestions most definitely welcome! – but I find this to be a pretty darn good way to add data from our columns.
ggplotly(
nasdaq_dividends %>%
filter(symbol != "MACK" & symbol != "FWP") %>%
left_join(nasdaq_wrangled, by = "symbol") %>%
group_by(symbol) %>%
mutate(info = paste(date,
'<br>company:', company,
'<br>sector:', sector,
'<br>symbol:', symbol,
'<br>div: $', dividends)) %>%
ggplot(aes(x = date,
y = dividends,
color = symbol,
label_tooltip = info)) +
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)),
tooltip = "label_tooltip"
)
Visit the blog to explore the interactive version of the above chart and download the R code: http://www.reproduciblefinance.com/2019/08/25/tech-dividends/
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