components:
- rx.recharts.ScatterChart
- rx.recharts.Scatter
import reflex as rx
from pcweb.templates.docpage import docgraphing
data01 = [
{
"x": 100,
"y": 200,
"z": 200
},
{
"x": 120,
"y": 100,
"z": 260
},
{
"x": 170,
"y": 300,
"z": 400
},
{
"x": 170,
"y": 250,
"z": 280
},
{
"x": 150,
"y": 400,
"z": 500
},
{
"x": 110,
"y": 280,
"z": 200
}
]
data02 = [
{
"x": 200,
"y": 260,
"z": 240
},
{
"x": 240,
"y": 290,
"z": 220
},
{
"x": 190,
"y": 290,
"z": 250
},
{
"x": 198,
"y": 250,
"z": 210
},
{
"x": 180,
"y": 280,
"z": 260
},
{
"x": 210,
"y": 220,
"z": 230
}
]
scatter_chart_simple_example = """rx.recharts.scatter_chart(
rx.recharts.scatter(
data=data01,
fill="#8884d8",),
rx.recharts.x_axis(data_key="x", type_="number"),
rx.recharts.y_axis(data_key="y")
)"""
scatter_chart_simple_complex = """rx.recharts.scatter_chart(
rx.recharts.scatter(
data=data01,
fill="#8884d8",
name="A"
),
rx.recharts.scatter(
data=data02,
fill="#82ca9d",
name="B"
),
rx.recharts.cartesian_grid(stroke_dasharray="3 3"),
rx.recharts.x_axis(data_key="x", type_="number"),
rx.recharts.y_axis(data_key="y"),
rx.recharts.z_axis(data_key="z", range=[60, 400], name="score"),
rx.recharts.legend(),
rx.recharts.graphing_tooltip(),
)"""
A scatter chart always has two value axes to show one set of numerical data along a horizontal (value) axis and another set of numerical values along a vertical (value) axis. The chart displays points at the intersection of an x and y numerical value, combining these values into single data points.
For a scatter chart we must define an rx.recharts.scatter()
component for each set of values we wish to plot. Each rx.recharts.scatter()
component has a data
prop which clearly states which data source we plot. We also must define rx.recharts.x_axis()
and rx.recharts.y_axis()
so that the graph knows what data to plot on each axis.
docgraphing(scatter_chart_simple_example, comp=eval(scatter_chart_simple_example), data = "data01=" + str(data01))
We can also add two scatters on one chart by using two rx.recharts.scatter()
components, and we can define an rx.recharts.z_axis()
which represents a third column of data and is represented by the size of the dots in the scatter plot.
docgraphing(scatter_chart_simple_complex, comp=eval(scatter_chart_simple_complex), data = "data01=" + str(data01) + "&data02=" + str(data02))
Chart data tied to a State var causes the chart to automatically update when the state changes, providing a nice way to visualize data in response to user interface elements. View the "Data" tab to see the substate driving this calculation of iterations in the Collatz Conjecture for a given starting number. Enter a starting number in the box below the chart to recalculate.
class ScatterChartState(rx.State):
data: list[dict[str, int]] = []
def compute_collatz(self, form_data: dict) -> int:
n = int(form_data.get("start") or 1)
yield rx.set_value("start", "")
self.data = []
for ix in range(400):
self.data.append({"x": ix, "y": n})
if n == 1:
break
if n % 2 == 0:
n = n // 2
else:
n = 3 * n + 1
def index():
return rx.vstack(
rx.recharts.scatter_chart(
rx.recharts.scatter(
data=ScatterChartState.data,
fill="#8884d8",
),
rx.recharts.x_axis(data_key="x", type_="number"),
rx.recharts.y_axis(data_key="y", type_="number"),
),
rx.form.root(
rx.chakra.input(placeholder="Enter a number", id="start"),
rx.button("Compute", type="submit"),
on_submit=ScatterChartState.compute_collatz,
),
width="100%",
height="15em",
on_mount=ScatterChartState.compute_collatz({"start": "15"}),
)