Getting Started
You can utilize Kandy both in Kotlin projects and in interactive editors. For detailed instructions, refer to the respective pages:
Getting Kandy
How to Install Kotlin Notebook?
You can find detailed instructions here.
Install IntelliJ IDEA Ultimate if you don't already have it.
Open your IDE and press Cmd+comma to open the IDE settings.
Select Kotlin Notebook plugin.
from the menu and install theClick
to apply the changes and restart your IDE if prompted.Create a new Kotlin Notebook file.
Run this cell:
%use kandy // If you are using dataframe as data %use dataframe
Congratulations, you now have access to the Kandy library in Kotlin Notebook.
How to Use Datalore?
You can find detailed instructions here.
Open Datalore.
Register if you don't have an account.
Create a new notebook.
Select the Kotlin Kernel.
Run this cell:
%use kandy // If you are using dataframe as data %use dataframe
Congratulations, you now have access to the Kandy library in Datalore.
How to Install Jupyter with Kotlin?
You can find detailed instructions here.
Install Jupyter.
Install the Kotlin Kernel using one of the following methods:
pip install kotlin-jupyter-kernelconda install -c jetbrains kotlin-jupyter-kernelRun Jupyter by executing the following command in the terminal:
jupyter notebookCreate a new notebook by selecting the Kotlin kernel.
Run this cell in the notebook:
%use kandy // If you are using dataframe as data %use dataframe
Congratulations, you now have access to the Kandy library in Jupyter Notebook.
Gradle Configuration
You can find detailed instructions here.
Create a JVM project with Kotlin in your IDE.
Add the Kandy dependency to your build.gradle.kts file:
dependencies { implementation("org.jetbrains.kotlinx:kandy-lets-plot:0.7.0") }
Congratulations, you now have access to the Kandy library in your Kotlin project.
Plotting a Simple Example
Let's create data that will be used to construct the plot. This data will represent the average annual temperatures in various cities. When working in interactive notebooks, it is advisable to divide the data creation and plot construction into two separate cells. This approach ensures that extension properties are generated for our columns in the DataFrame, allowing us to reference them easily.
First, create a DataFrame containing data on the average temperatures in different cities as follows:
Next, construct a simple plot using the data from the DataFrame:
This supplementary schema outlines the key elements of Kandy's DSL, providing a quick reference to assist you in building your visualizations.
plot
For more examples, please see the Examples section.