More vapply()

The difference between vapply() and sapply() was shown in the last example to demonstrate vapply() appropriately failing, but what about when it doesn't fail? When there are no errors, vapply() returns a simplified result according to the FUN.VALUE argument.

The stock_return dataset containing daily returns for Apple, IBM, and Microsoft has been provided. The sharpe() function is also available.

Latihan ini adalah bagian dari kursus

Intermediate R for Finance

Petunjuk latihan

Calculate the sharpe ratio for each stock using vapply().
Use summary() on the apple column to get a 6 number summary.
vapply() the summary() function across stock_return to summarize each column.

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Cobalah latihan ini dengan menyelesaikan kode contoh berikut.

# Sharpe ratio for all stocks
vapply(___, ___, FUN.VALUE = numeric(___))

# Summarize Apple
___

# Summarize all stocks
vapply(___, ___, FUN.VALUE = numeric(___))

Edit dan Jalankan Kode

Latihan ini adalah bagian dari kursus

Intermediate R for Finance

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4.8+

Mulai Kursus Gratis

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Exercise 1: An introduction to dates in R Exercise 2: What day is it?Exercise 3: From char to date Exercise 4: Many dates Exercise 5: Date formats and extractor functions Exercise 6: Date formats (1)Exercise 7: Date formats (2)Exercise 8: Subtraction of dates Exercise 9: months() and weekdays() and quarters(), oh my!

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Exercise 1: Relational operators Exercise 2: Relational practice Exercise 3: Vectorized operations Exercise 4: Logical operators Exercise 5: And / Or Exercise 6: Not!Exercise 7: Logicals and subset()Exercise 8: All together now!Exercise 9: If statements Exercise 10: If this Exercise 11: If this, Else that Exercise 12: If this, Else If that, Else that other thing Exercise 13: Can you If inside an If?Exercise 14: ifelse()

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Exercise 1: Repeat loops Exercise 2: Repeat, repeat, repeat Exercise 3: When to break?Exercise 4: While loops Exercise 5: While with a print Exercise 6: While with a plot Exercise 7: Break it Exercise 8: For loops Exercise 9: Loop over a vector Exercise 10: Loop over data frame rows Exercise 11: Loop over matrix elements Exercise 12: Break and next

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Exercise 1: What are functions?Exercise 2: Function help and documentation Exercise 3: Optional arguments Exercise 4: Functions in functions Exercise 5: Writing functions Exercise 6: Your first function Exercise 7: Multiple arguments (1)Exercise 8: Multiple arguments (2)Exercise 9: Function scope (1)Exercise 10: Function scope (2)Exercise 11: Packages Exercise 12: tidyquant package

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Exercise 1: Why use apply?Exercise 2: lapply() on a list Exercise 3: lapply() on a data frame Exercise 4: FUN arguments Exercise 5: sapply() - simplify it!Exercise 6: sapply() vs. lapply()Exercise 7: Failing to simplify Exercise 8: vapply() - specify your output!Exercise 9: vapply() vs. sapply()Exercise 10: More vapply()

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Exercise 11: Anonymous functions Exercise 12: Congratulations