Plots.jl.jl

### A Pluto.jl notebook ###
# v0.11.12

using Markdown
using InteractiveUtils

# ╔═╡ 7b93882c-9ad8-11ea-0288-0941e163f9d5
md"""
# Plotting in Pluto

Pluto is an excellent enviroment to visualise your data. This notebook shows a few examples of using plots in Pluto using the `Plots` package.

I wrote this notebook so you can understand it even if you have never used `Plots`. However, it is not intend as a complete tutorial for the package. If you want to start making your own plots, I recommend looking at the package [documentation](https://docs.juliaplots.org/latest/) for a full tutorial as well.

Let's start by importing the `Plots` package. We do this in a special way, which guarantees that anyone who opens the notebook can use the package.
"""

# ╔═╡ d889e13e-f0ff-11ea-3306-57491904d83f
md"_First, we set up a clean package environment:_"

# ╔═╡ aefb6004-f0ff-11ea-10c9-c504c7aa9fe5
begin
	import Pkg
	Pkg.activate(mktempdir())
end

# ╔═╡ a0f0ae42-9ad8-11ea-2475-a735df64aa28
begin
	Pkg.add("Plots")
	using Plots
end

# ╔═╡ e48a0e78-f0ff-11ea-2852-2f4eee1a7d2d
md"_Next, we add the `Plots` package to our environment, and we import it._"

# ╔═╡ a9a3c640-f100-11ea-2e86-5f0e81a37ebd
md"You can just put a cell like this anywhere in your notebook, if you want to add+import more packages."

# ╔═╡ c042d3d2-f100-11ea-3833-af1f19afd400
md"(If you already had Plots installed, then this will just use the globally installed version! Neat)"

# ╔═╡ e5abaf40-f105-11ea-1494-2da858d7db5b
md"We need to choose a _backend_ for Plots.jl. We choose `plotly` because it works with no additional dependencies. You can [read more about backends](http://docs.juliaplots.org/latest/backends/#backends) in Plots.jl - it's one of its coolest features!"

# ╔═╡ 9414a092-f105-11ea-10cd-23f84e47d876
plotly()

# ╔═╡ 5ae65950-9ad9-11ea-2e14-35119d369acd
md"""
## The basics
Now we can get started. We can begin by making some X and Y values. I typed out some Y values so you can alter them and see the effect. 
"""

# ╔═╡ aaa805d4-9ad8-11ea-21c2-3b20580fea0e
years = 2001:2010

# ╔═╡ c02bc44a-9ad8-11ea-117d-3997e1f3cab0
apples = [15, 25, 80, 75, 50, 30, 35, 15, 25, 35]

# ╔═╡ a405ae4c-9ad9-11ea-0008-f763e098846d
md"""
Great, let's plot them! The basic syntax of of `Plots` is very simple.
"""

# ╔═╡ 12a8c222-9ad9-11ea-2544-355bd080367f
plot(years, apples)

# ╔═╡ 19660da0-9ada-11ea-1942-a9d4ddd7753b
md"""
You can change the properties of the plot by giving different arguments to the function call.
"""

# ╔═╡ 5410faba-9ada-11ea-2fc5-35f0bdd40d96
plot(years, apples, legend=false, title="Number of apples per year")

# ╔═╡ 90c47cae-9ada-11ea-10da-91f4dcf0f2d6
md"""
Alternatively, you can use `plot!()`. This function takes the same arguments, but alters our existing plot.
"""

# ╔═╡ b2727d2e-9ada-11ea-23d3-bddab9ec8de1
begin
	plot(years, apples)
	plot!(legend=false)
	plot!(title="Number of apples per year")
end

# ╔═╡ eb218bea-9adc-11ea-2f3a-298c41caf8a1
md"""
## More options

We can easily plot multiple series.
"""

# ╔═╡ bd30bdf4-9add-11ea-26d4-75ac3f0b8610
oranges = rand(1:100, 10)

# ╔═╡ dc50d480-9add-11ea-2821-018a98fab262
begin
	plot(years, apples, label="apples")
	plot!(years, oranges, label="oranges")
end

# ╔═╡ c9a64e98-9b67-11ea-1d6a-3b1f7548cb8d
md"""
Different plot types have their own functions.
"""

# ╔═╡ 13428812-9ade-11ea-3865-1d293993203d
scatter(apples, oranges, legend=false)

# ╔═╡ d76fd0f6-9b67-11ea-0a73-e9ddb60ca291
md"""
You can also plot a function instead of an output array!
"""

# ╔═╡ 69fa7744-9b67-11ea-26df-3b4446dfb3ea
begin
	function myfunction(x)
		return sin(x / 2)
	end
	
	plot(years, sin, label="sine")
	plot!(years, myfunction, label="my function")
end

# ╔═╡ af31a428-9adf-11ea-280a-45e2b891c4f9
md"""
## Naming plots

Plots are also just a type of variable, so you can give them a name.
"""

# ╔═╡ 5ed7c444-9adf-11ea-2925-8573f018e820
apples_plot = plot(years, apples, 
	legend=false, xlabel="year", ylabel="apples")

# ╔═╡ 932b6b3c-a64d-11ea-2aba-2bf577ce3cf8
apples_vs_oranges = scatter(apples, oranges, 
	legend=false, xlabel="apples", ylabel="oranges")

# ╔═╡ 030c1d10-9b69-11ea-11b7-ff04c60892b9
md"""
This way, you can show them again
"""

# ╔═╡ d7bdab72-9b65-11ea-18c0-5353a214749d
apples_plot

# ╔═╡ 22992cec-9adb-11ea-078e-c7c21489c053
md"""
## Combining subplots

We can combine multiple plots in a single image using the `layout` argument. One option is to provide a matrix of values and call a single `plot`.
"""

# ╔═╡ 5d723220-9ade-11ea-37db-c110dda60a15
pears = rand(1:100, 10)

# ╔═╡ 632cb26c-9ade-11ea-1bc7-39b8207190e2
bananas = rand(1:100, 10)

# ╔═╡ a01bf430-9ade-11ea-2ae4-23287ba11406
fruits = hcat(apples, oranges, pears, bananas)

# ╔═╡ 69e045b0-9ade-11ea-0c55-05fa0da5893c
plot(years, fruits, layout=(4, 1), legend=false)

# ╔═╡ 054e0c4e-9adf-11ea-3deb-4daf2b6a2548
md"""
This works when we have a nice output matrix. For more complicated options, named plots are usually a good solution. When we have created a few plots, we can put them together in a single plot.
"""

# ╔═╡ 91b4eedc-9adf-11ea-37aa-250ceec26640
plot(apples_plot, apples_vs_oranges, layout=(1, 2))

# ╔═╡ a7abf64e-9adb-11ea-2ae4-47886125fe60
md"""
## The Pluto way of plotting

For the most part, plotting in Pluto is not different from anywhere else. However, there are a few things to keep in mind.

The `plot!()` function alters an existing plot. In reactive programming, you are not supposed to alter the value of a variable you defined in a different cell. I strongly recommend that you only use `plot!()` to alter plots you initialised in the same cell. 

For the sake of demonstration, here is what happens if you use `plot!()` in its own cell. Let's start by making a new plot.
"""

# ╔═╡ 2617a7b6-9ae2-11ea-1461-d914c7cfdb09
pears_plot = plot(years, pears, label="pears")

# ╔═╡ 46388876-9ae2-11ea-2c5f-073698e45d44
md"""
The cell below adds a new series to the plot. It shows the altered plot, while our original plot still looks intact.

Maybe that's not so bad. It seems like we could use this to build a plot one step at a time. But try changing the plot below so that it plots oranges instead of bananas.
"""

# ╔═╡ 2598a29a-9ae2-11ea-02cc-21f3fa5a9472
plot!(pears_plot, years, bananas, label="bananas")

# ╔═╡ a9cdba00-9ae2-11ea-3bf9-41d07e7a785f
md"""
Did you get three series? It's because the `plot` still has the `bananas` data added to it. So the bananas are still plotted, even though you now don't have any code doing that. This is not great for coding: it means that if you close your notebook, your plots might not look the same when you open it again.

Try running the cell a few times. You keep adding series! Also not great when working on a plot.
"""

# ╔═╡ f22b6fda-9ae3-11ea-3ff2-ebcf1374f595
md"""
So what if you do want to add things to a plot one at a time, instead of using a single cell? My recommendation is to define your plot in a function.
"""

# ╔═╡ 8819edf0-9ae4-11ea-15f4-f17e9e9db8ea
function plot_pears()
	myplot = plot(years, pears, label="pears")
	return myplot
end

# ╔═╡ 9e4d1462-9ae4-11ea-3c0f-774d68a671c3
plot_pears()

# ╔═╡ a7906786-9ae4-11ea-0175-4f860c05a8a2
begin
	plot_pears()
	plot!(years, bananas, label="bananas")
end

# ╔═╡ d3cbc548-9ae4-11ea-261f-7fb956839e53
md"""
Try changing the function for the base plot, or the addition in the bottom cell. No weird effects!
"""

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