{"id":25865,"date":"2019-11-26T09:53:00","date_gmt":"2019-11-26T14:53:00","guid":{"rendered":"https:\/\/ibkrcampus.com\/?p=25865"},"modified":"2024-05-14T11:30:03","modified_gmt":"2024-05-14T15:30:03","slug":"tech-dividends-part-vi","status":"publish","type":"post","link":"https:\/\/www.interactivebrokers.com\/campus\/ibkr-quant-news\/tech-dividends-part-vi\/","title":{"rendered":"Tech Dividends \u2013 Part VI"},"content":{"rendered":"\n<p class=\"wp-block-paragraph\"><em>In&nbsp;<\/em><a href=\"\/campus\/ibkr-quant-news\/tech-dividends-part-iv\/\"><em>Part IV<\/em><\/a><em>&nbsp;and <\/em><a href=\"\/campus\/ibkr-quant-news\/tech-dividends-part-v\/\"><em>Part V<\/em><\/a><em> Jonathan created a chart and showed how to wrap that chart in a call to&nbsp;<\/em><code><em>ggplotly()<\/em><\/code><em> .<\/em>&nbsp; <em>The required packages and data preparation scripts are available in&nbsp;<a href=\"\/campus\/ibkr-quant-news\/tech-dividends-part-i\/\">Part I<\/a>,&nbsp;and&nbsp;<a href=\"\/campus\/ibkr-quant-news\/tech-dividends-part-ii\/\">Part II<\/a>&nbsp;of this series.<\/em>&nbsp;<em>In&nbsp;<a href=\"\/campus\/ibkr-quant-news\/tech-dividends-part-iii\/\">Part III<\/a>&nbsp;Jonathan worked with data for MACK and FWP dividends<\/em>. <\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Let\u2019s add back the name and sector data by&nbsp;<code>left_join()<\/code>ing our wrangled data object.<\/p>\n\n\n\n<pre class=\"wp-block-code\"><code>nasdaq_dividends %>% \n  left_join(nasdaq_wrangled, by = \"symbol\") %>% \n  head()<\/code><\/pre>\n\n\n\n<pre class=\"wp-block-code\"><code># A tibble: 6 x 9\n  symbol date       dividends company last_sale_price market_cap ipo_year\n  &lt;chr>  &lt;date>         &lt;dbl> &lt;chr>             &lt;dbl>      &lt;dbl>    &lt;dbl>\n1 AVGO   2010-12-13      0.07 Broadc\u2026            272.     108330     2009\n2 AVGO   2011-03-16      0.08 Broadc\u2026            272.     108330     2009\n3 AVGO   2011-06-15      0.09 Broadc\u2026            272.     108330     2009\n4 AVGO   2011-09-15      0.11 Broadc\u2026            272.     108330     2009\n5 AVGO   2011-12-15      0.12 Broadc\u2026            272.     108330     2009\n6 AVGO   2012-03-15      0.13 Broadc\u2026            272.     108330     2009\n# \u2026 with 2 more variables: sector &lt;chr>, industry &lt;chr><\/code><\/pre>\n\n\n\n<p class=\"wp-block-paragraph\">Once the company name data is joined, we can incorporate into the plot by adding&nbsp;<code>label_tooltip = company<\/code>&nbsp;to&nbsp;<code>ggplot(aes(...))<\/code>&nbsp;and then setting&nbsp;<code>tooltip = \"label_tooltip\"<\/code>, to alert&nbsp;<code>plotly<\/code>&nbsp;about the new tooltip data.<\/p>\n\n\n\n<figure class=\"wp-block-image\"><img decoding=\"async\" width=\"765\" height=\"463\" data-src=\"\/campus\/wp-content\/uploads\/sites\/2\/2019\/11\/Tech-Dividends-R-1.png\" alt=\"R Programming Tech Dividends\" class=\"wp-image-25874 lazyload\" data-srcset=\"https:\/\/ibkrcampus.com\/campus\/wp-content\/uploads\/sites\/2\/2019\/11\/Tech-Dividends-R-1.png 765w, https:\/\/ibkrcampus.com\/campus\/wp-content\/uploads\/sites\/2\/2019\/11\/Tech-Dividends-R-1-300x182.png 300w, https:\/\/ibkrcampus.com\/campus\/wp-content\/uploads\/sites\/2\/2019\/11\/Tech-Dividends-R-1-700x424.png 700w\" data-sizes=\"(max-width: 765px) 100vw, 765px\" src=\"data:image\/svg+xml;base64,PHN2ZyB3aWR0aD0iMSIgaGVpZ2h0PSIxIiB4bWxucz0iaHR0cDovL3d3dy53My5vcmcvMjAwMC9zdmciPjwvc3ZnPg==\" style=\"--smush-placeholder-width: 765px; aspect-ratio: 765\/463;\" \/><figcaption> <\/figcaption><\/figure>\n\n\n\n<p class=\"wp-block-paragraph\"> <em>Visit the blog to download the R code or to explore the interactive version of the above chart:&nbsp;<\/em><a href=\"https:\/\/www.reproduciblefinance.com\/2019\/08\/25\/tech-dividends\/\"><em>https:\/\/www.reproduciblefinance.com\/2019\/08\/25\/tech-dividends\/<\/em><\/a>   <\/p>\n\n\n\n<pre class=\"wp-block-code\"><code>ggplotly(\nnasdaq_dividends %>%\n  filter(symbol != \"MACK\" &amp; symbol != \"FWP\") %>% \n  left_join(nasdaq_wrangled, by = \"symbol\") %>% \n  group_by(symbol) %>% \n  ggplot(aes(x = date, y = dividends, color = symbol, label_tooltip = company)) + \n  geom_point() + \n  scale_y_continuous(labels = scales::dollar)  +\n  scale_x_date(breaks = scales::pretty_breaks(n = 10)) +\n  labs(x = \"\", y = \"div\/share\", title = \"Nasdaq dividends\") +\n  theme(plot.title = element_text(hjust = 0.5)),\ntooltip = \"label_tooltip\"\n)<\/code><\/pre>\n\n\n\n<p class=\"wp-block-paragraph\"><em>In the next installment of this series, Jonathan<\/em> <em>use<\/em>&nbsp;<code>mutate<\/code>&nbsp;<em>to create a new column that holds our label information.<\/em><\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Any stock, options or futures symbols displayed are for illustrative purposes only and are not intended to portray recommendations.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Jonathan Regenstein reproducible finance scripts teach novice quants how to gather, clean and chart the data using 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