Plots Julia
2021年4月17日Register here: http://gg.gg/p2tul
Now you are ready to start! So, fire up a Jupyter Notebook using Julia as the kernel and get going. Julia, as with most other languages, relies on libraries of code for particular specialist purposes. The one that we are initially interested in is called Plots. This provides us with the capability to create visualizations of data.
The main plotting package in Julia is called Plots.To create a figure, you supply data in the form of arrays as arguments to the plot function (x first, then y if appropriate, then z if appropriate). All other plot information (called attributes, in Plots lingo) is supplied using keyword arguments. For example:
Note that the group keyword argument partitioned the data into two series, one for each unique value in the array supplied to group.These series are automatically shown in different colors and labeled in the legend.
These figures are made by Plots.jl Home View on GitHub Jupyter Notebook ver. This site is an unofficial Plots.jl Gallery site. It is inspired by MATLAB Plot Gallery. Figures are ploted by Plots.jl. Tested Environment. Julia 1.5.3; Plots 1.9.1; PyPlot 2.9.0; GR 0.53.0; For all plots, you should import Plots. A Computer Science portal for geeks. It contains well written, well thought and well explained computer science and programming articles, quizzes and practice/competitive programming/company interview Questions. Set of unofficial examples of Julia the high-level, high-performance dynamic programming language for technical computing. Below are a series of examples of common operations in Julia. They assume you already have Julia installed and working (the examples are currently tested with Julia v1.0.5). The simplest possible script. Plot(String.(dflong.variable),dflong.value) Note the dot., which is Julia’s dot operator that converts the entire vector of Symbols to a vector of Strings. However for this data you will probably like more a scatter plot.
You can see all the main plot types and attributes on the Plots.jl cheatsheet.
To save a plot, use the savefig function:Plots Julia Russell
ExerciseMake a graph which looks as much as possible like the one shown below. You’ll want to look at the Plots.jl cheatsheet for options.
Solution.We change the line style and width, and we add labels for the axes:Plots Julia Color
To get a quick refresher on how to perform common tasks in Julia, check out the Julia-Python-R cheatsheet, also linked from browndsi.github.io.Julia Plots Figure Size
Congratulations! You have finished the Data Gymnasia Programming with Julia course.
Register here: http://gg.gg/p2tul
https://diarynote.indered.space
Now you are ready to start! So, fire up a Jupyter Notebook using Julia as the kernel and get going. Julia, as with most other languages, relies on libraries of code for particular specialist purposes. The one that we are initially interested in is called Plots. This provides us with the capability to create visualizations of data.
The main plotting package in Julia is called Plots.To create a figure, you supply data in the form of arrays as arguments to the plot function (x first, then y if appropriate, then z if appropriate). All other plot information (called attributes, in Plots lingo) is supplied using keyword arguments. For example:
Note that the group keyword argument partitioned the data into two series, one for each unique value in the array supplied to group.These series are automatically shown in different colors and labeled in the legend.
These figures are made by Plots.jl Home View on GitHub Jupyter Notebook ver. This site is an unofficial Plots.jl Gallery site. It is inspired by MATLAB Plot Gallery. Figures are ploted by Plots.jl. Tested Environment. Julia 1.5.3; Plots 1.9.1; PyPlot 2.9.0; GR 0.53.0; For all plots, you should import Plots. A Computer Science portal for geeks. It contains well written, well thought and well explained computer science and programming articles, quizzes and practice/competitive programming/company interview Questions. Set of unofficial examples of Julia the high-level, high-performance dynamic programming language for technical computing. Below are a series of examples of common operations in Julia. They assume you already have Julia installed and working (the examples are currently tested with Julia v1.0.5). The simplest possible script. Plot(String.(dflong.variable),dflong.value) Note the dot., which is Julia’s dot operator that converts the entire vector of Symbols to a vector of Strings. However for this data you will probably like more a scatter plot.
You can see all the main plot types and attributes on the Plots.jl cheatsheet.
To save a plot, use the savefig function:Plots Julia Russell
ExerciseMake a graph which looks as much as possible like the one shown below. You’ll want to look at the Plots.jl cheatsheet for options.
Solution.We change the line style and width, and we add labels for the axes:Plots Julia Color
To get a quick refresher on how to perform common tasks in Julia, check out the Julia-Python-R cheatsheet, also linked from browndsi.github.io.Julia Plots Figure Size
Congratulations! You have finished the Data Gymnasia Programming with Julia course.
Register here: http://gg.gg/p2tul
https://diarynote.indered.space
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