prepare_scatter_plot
prepare_scatter_plot(df, x, y, *, color=None, size=None, loess=0, alpha=None)Scatter plot of y against x with optional aesthetics and a LOESS smoother.
Parameters
| Name | Type | Description | Default |
|---|---|---|---|
| df | pd.DataFrame | Data frame containing the variables. | required |
| x | str | Column names for the axes. | required |
| y | str | Column names for the axes. | required |
| color | str | None | Optional column mapped to marker color (numeric -> colorbar, otherwise discrete). | None |
| size | str | None | Optional numeric column mapped to marker size. | None |
| loess | Literal[0, 1, 2] | 0 no smoother, 1 unweighted LOESS, 2 LOESS weighted by size. |
0 |
| alpha | float | None | Marker opacity. If None, a sample-size-based default is used. |
None |
Returns
| Name | Type | Description |
|---|---|---|
| plotly.graph_objects.Figure | The scatter figure. |
Examples
Basic — a plain scatter of two variables (this function returns a Plotly figure directly, so there is no .fig attribute):
import expdpy as ex
from expdpy.data import load_kuznets
df = load_kuznets()
ex.prepare_scatter_plot(df, x="log_gdp_pc", y="gini_regional")Advanced — map color and marker size to other columns, add a size-weighted LOESS smoother (the N-shaped Kuznets curve) and tune opacity:
ex.prepare_scatter_plot(
df, x="log_gdp_pc", y="gini_regional",
color="continent", size="population", loess=2, alpha=0.6,
)