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Financial Data Manipulation in dplyr for Quant Traders – Part V

Financial Data Manipulation in dplyr for Quant Traders – Part V

Posted June 23, 2021 at 12:10 pm
Robot James
Robot Wealth

Join Robot James for a tutorial on how to use mutate() dplyr verb for financial data manipulation. See Part IPart IIPart III and Part IV to  set up and load the data.

The mutate() dplyr verb

So far we’ve just filtered selected and re-arranged existing data. Now we’re going to look at creating new data.

Mutate lets us add variables (columns) to our data. These are usually derived from existing columns.

Add new variable (column) for log volume with mutate()

Here we use mutate to add a column called logvolume to our data. It is calculated as the log of the volume variable.

prices %>%
mutate(logvolume = log(volume))

Add new variable (column) for intraday returns with mutate()

In this example, we add a column for the intraday (open to close) simple returns of the stock each day.

prices %>%
mutate(intradayreturns = close / open – 1)

Stay tuned for the next installment in which the author will demonstrate the summarise() dplyr verb.

Visit Robot Wealth website to read the full article and download code:

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