All together now!

Great! You have learned a lot about operators and subsetting. This will serve you well in future data analysis projects. Let's do one last exercise that combines a number of operators together.

A new version of the stocks data frame is available for you to use.

This exercise is part of the course

Intermediate R for Finance

Exercise instructions

First, print stocks. It contains Apple and Microsoft prices for December, 2016.
It seems like you have missing data. Let's investigate further. Use weekdays() on the date column, and assign it to stocks as the column, weekday.
View stocks now. The missing data is on weekends! This makes sense, the stock market is not open on weekends.
Remove the missing rows using subset(). Use!is.na() on apple as your condition. Assign this new data frame to stocks_no_NA.
Now, you are interested in days where apple was above 117, or when micr was above 63. Use relational operators, |, and subset() to accomplish this with stocks_no_NA.

Hands-on interactive exercise

Have a go at this exercise by completing this sample code.

# View stocks
___

# Weekday investigation
stocks$weekday <- 

# View stocks again
___

# Remove missing data
stocks_no_NA <- ___

# Apple and Microsoft joint range
___

Edit and Run Code

This exercise is part of the course

Intermediate R for Finance

BeginnerSkill Level

4.8+

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Current Exercise

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