I thought of ending blogs about plots last time, but I did think about Scatter and Histogram plots. I feel they are important and I felt I need them to better explain some of the blogs I kinda a plan to write in the future. So here are scatter and histogram plots.
So let’s create a simple scatter, x-values as first argument, y-values as second, I have given color as red but its completely optional:
scatter_plot = scatter([1, 2 , 3, 4], [1, 2, 3, 4], color = "red")
We have captured last output in a variable called
scatter_plot, this is much better variable name I tell you. In my previous blog I had given a names like
p which is actually blasphemy in programming world, you might be smart today and understand what
p is, but possibly 6 months later it will haunt you, or a programmer touching your code sometime later might curse you thus causing your loved ones to vomit blood and die. Anyway, we now add another scatter to
scatter_plot using the code below:
scatter!(scatter_plot, [1, 7, 8, 2, 3], [2, 6, 3, 1, 4], color = "blue")
As you can see above, this time we have not used
plot!() to modify
scatter_plot but we have used this function
scatter!() which I personally feel is much better to read. And we have put these new dots in color blue. Let’s modify
scatter_plot again this time using
plot!() function as shown below:
plot!( scatter_plot, [1, 2, 3, 4 ], [-1, -2 , -3, -4], color = "orange", seriestype = :scatter )
As you see above in the above
plot!() we have used named argument
seriestype and have set it to
:scatter for it to be a scatter plot. I am unsure why we have a colon
: before scatter, should check Julia docs about it. Okay, looks like this is a special kind of thing known as
Symbol, another data type in Julia, possibly it occupies less space compared to
"scatter" which is a string when called multiple times. I just checked this code:
julia> :a :a julia> typeof(:a) Symbol
just to check its type.
Okay, the label box int above scatter plots is overlapping a data point, lets increase the x right limit to 12 so that it would look better:
plot!(scatter_plot, xlims = (0, 12))
For some reason I like histograms, so I have plotter a histogram below:
histogram(rand(1:1000, 500), bins = 20)
I think I will be using it while writing about the Iris data set. You can get the notebook file for this blog here https://gitlab.com/data-science-with-julia/code/-/blob/master/plots.ipynb.
Learn more about Plots
This is the last blog about Plots I think unless i change my mind for some reason, if you want to learn more check the official Plots website https://docs.juliaplots.org/latest/, and this Julia Plots by Prude University https://www.math.purdue.edu/~allen450/Plotting-Tutorial.html is good too.