{"id":94533,"date":"2021-07-09T11:30:00","date_gmt":"2021-07-09T15:30:00","guid":{"rendered":"https:\/\/ibkrcampus.com\/?p=94533"},"modified":"2022-11-21T09:47:43","modified_gmt":"2022-11-21T14:47:43","slug":"financial-data-manipulation-in-dplyr-for-quant-traders-part-vii","status":"publish","type":"post","link":"https:\/\/www.interactivebrokers.com\/campus\/ibkr-quant-news\/financial-data-manipulation-in-dplyr-for-quant-traders-part-vii\/","title":{"rendered":"Financial Data Manipulation in dplyr for Quant Traders \u2013 Part VII"},"content":{"rendered":"\n

Join Robot James for a tutorial on how to use group_by()<\/code><\/em> dplyr verb for financial data manipulation. See Part I<\/a>, Part II<\/a>, Part III<\/a>, Part IV<\/a>,  Part V<\/a> and Part VI<\/a> for instructions on other dplyr verb<\/em>s.<\/p>\n\n\n\n

The group_by()<\/code> dplyr verb<\/h3>\n\n\n\n
\"\"<\/figure><\/div>\n\n\n\n

Summarising the entire data set isn\u2019t always very useful.<\/p>\n\n\n\n

Usually, we want to group by a variable, and then summarise that grouped data.<\/p>\n\n\n\n

The group_by()<\/code> function tells the dplyr<\/code> verbs to operate on each group one at a time.<\/p>\n\n\n\n

Use summarise()<\/code> with group_by()<\/code> to calculate mean traded volume for each stock<\/h4>\n\n\n\n

If we group by ticker, then call summarise, then dplyr<\/code> will preform the summary calculations separately for each ticker. We will get a row for each ticker.<\/p>\n\n\n\n

\nprices %>%
\n group_by(ticker) %>%
\n summarise(meanvolume = mean(volume))\n<\/p>\n\n\n\n

\"\"<\/figure><\/div>\n\n\n\n

Use summarise()<\/code> with multiple group_by<\/code> variables, to calculate the mean traded volume for each stock for each year<\/h4>\n\n\n\n

In this example we:<\/p>\n\n\n\n