0️⃣Smart Plot
❓What It Can Do for You
Smart Plot is the key feature of HEARTCOUNT where typical code-heavy visualization tasks can be executed easily and come in handy. To visualize data in a way you want to examine it, all you have to do is to simply select which variable goes x-axis and which goes to y-axis and choose the type of visualizations you wish to use.
Smart Plot provides a variety of visualizations of your data, which include such below.
Data Type | Available Visualization |
---|---|
Between numeric and other numeric | Scatterplot |
Trend Line(regression line) | |
Heat Scatter | |
Between categorical and numeric | Bar (average or sum) |
Stacked Bar | |
Stacked Area | |
95% confidence interval | |
Boxplot | |
Between categorical and categorical | Ratio Bar Chart |
Stacked Count Bar | |
Between time series and numeric | Time Series Line Chart |
Stacked Area | |
Trend Line | |
Forecast |
📃How to Use
- Basics
Smart Plot consists of four key sections. You can easily create a suitable visualization of your dataset using these sections without writing a single line of code.
Area | What's It For |
---|---|
1. Main Area | This is where a plot will be displayed. You will be able to interact with plot elements such as data points in a scatterplot to further investigate the dataset to find an answer to your analytic inquiries. |
2. Side Menu | This is where you may configure Smart Plot's parameters, such as which variables to use to change the colors or sizes of data points, or to filter the data. Also, you could choose |
3. Variable Selection | This is where you can choose which variable to create a plot suitable for your analytic purpose. As with creating a data visualization in a code-heavy setting(R/Python), you must choose which variables you would place in the x and y axes and which to use for subgrouping or faceting. |
4. Visualization Type | This is where you can choose which type of visualization you would use to plot the data. Given the variables for the x and y axes, the Visualization Type tab will provide you several options you could choose from to correctly visualize your data. |
- Types of Visualizations
This section will discuss the many sorts of visualizations possible in relation to the specified x and y axes variables.
When you put numeric variables on both axes, a simple scatterplot will be displayed on Smart Plot. Also, a Pearson correlation coefficient will be given as a basic information on these two variables.
- Additional Features
Facetting
Smart Plot offers a facet feature. It allows you to divide a single plot into multiple charts based on a facet variable in order to better understand the relationship between the x and y variables. You can also use every other feature in Smart Plot within each facet plot.
Categorical variables with fewer than 11 groups can currently be used as a facet variable.
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