jsongrapherrc 2.7

A python package for creating JSONGrapher Records.

JSONGrapherRC (JSONGrapher Record Creator)

A python package for creating JSONGrapher files which can then be plotted.

To use JSONGrapherRC, first install it using pip:

pip install JSONGrapherRC[COMPLETE]

Alternatively, you can download the directory directly.

It is easiest to then follow the example file to see how to create graphable .json records and to plot them. The .json files can then be dragged into www.jsongrapher.com

1. Preparing to Create a Record

Let's create an example where we plot the height of a pear tree over several years. Assuming a pear tree grows approximately 0.40 meters per year, we'll generate sample data with some variation.

x_label_including_units = "Time (years)"
y_label_including_units = "Height (m)"
time_in_years = [0, 1, 2, 3, 4]
tree_heights = [0, 0.42, 0.86, 1.19, 1.45]

2. Creating and Populating a New JSONGrapher Record

Record = JSONRecordCreator.create_new_JSONGrapherRecord()
Record.set_comments("Tree Growth Data collected from the US National Arboretum")
Record.set_datatype("Tree_Growth_Curve")
Record.set_x_axis_label_including_units(x_label_including_units)
Record.set_y_axis_label_including_units(y_label_including_units)
Record.add_data_series(series_name="pear tree growth", x_values=time_in_years, y_values=tree_heights, plot_type="scatter_spline")
Record.set_graph_title("Pear Tree Growth Versus Time")

3. Exporting to File

We can export it to a .json file, which can then be used with JSONGrapher.

Record.export_to_json_file("ExampleFromTutorial.json")
Record.print_to_inspect()

Expected Output:

JSONGrapher Record exported to, ./ExampleFromTutorial.json
{
    "comments": "Tree Growth Data collected from the US National Arboretum",
    "datatype": "Tree_Growth_Curve",
    "data": [
        {
            "name": "pear tree growth",
            "x": [0, 1, 2, 3, 4],
            "y": [0, 0.42, 0.86, 1.19, 1.45],
            "type": "scatter",
            "line": { "shape": "spline" }
        }
    ],
    "layout": {
        "title": "Pear Tree Growth Versus Time",
        "xaxis": { "title": "Time (year)" },
        "yaxis": { "title": "Height (m)" }
    }
}

4. Plotting to Inspect

We can also plot the data using Matplotlib and export the plot as a PNG file.

Record.plot_with_matplotlib()
Record.export_to_matplotlib_png("ExampleFromTutorial_matplotlib_fig")

And we can create an interactive graph with plotly:

Record.plot_with_plotly() #Try hovering your mouse over points after this command!