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Price goes up

Line plots are highly effective at displaying the evolution of a variable over time. In this exercise, you will continue to work with data describing the prices of different funds over time. The goal is to plot the evolution of the daily high price for the iShares Russell 1000 Growth ETF fund (IWF) as a function of time, displaying the overall trend and patterns.

The CSV and DataFrames packages have been imported for you.

This exercise is part of the course

Introduction to Data Visualization with Julia

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Exercise instructions

  • Import the Plots.jl package.
  • Load the data in the .csv file into the iwf DataFrame.
  • Call the relevant function to create a line plot.
  • Pass the price_date and high columns of the iwf DataFrame in that order as arguments to the function.

Hands-on interactive exercise

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

# Import Plots.jl
____ ____

# Load dataset
iwf = ____(CSV.File("iwf.csv"))

# Create a line plot
____(
	# Pass the columns
	____.____,
	____.____
)
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