Category-wise distributions
Compare a numeric measurement across categories while retaining every observation.
Plotly · Function
px.strip
px.strip creates an interactive strip chart that displays individual observations across categories or numeric values. It is useful when the points themselves matter more than a summarized box or violin shape.
How it works
px.strip creates a strip chart from a data frame, displaying individual observations along categorical or continuous axes. It supports long-form data and, as a 2D Cartesian function, can also process wide-form and mixed-form inputs; the returned figure can then be displayed or further customized.
Syntax
plotly.express.strip(data_frame=None, x=None, y=None, color=None, ...)Parameters
| Name | Type | Description |
|---|---|---|
data_frame | DataFrame or array-like | Input data frame containing the columns used by the chart. |
x | str or array-like | Column or data values mapped to the horizontal axis. |
y | str or array-like | Column or data values mapped to the vertical axis. |
color | str or array-like | Column or data values used to assign point colors. |
Returns
A Plotly figure containing the generated strip chart.
Key points
- The chart emphasizes every observation rather than summarizing the distribution with a visible box.
- Long-form data is directly supported, with columns mapped to the chart through named arguments.
- Because it is a 2D Cartesian function,
px.stripalso accepts wide-form and mixed-form inputs. px.stripbelongs to Plotly Express's group of functions with wide-form and mixed-form support.
Common mistakes
- Pass the data frame first, then refer to its columns by name in arguments such as
x,y, andcolor.
Example: Basic strip chart
import plotly.express as px
df = px.data.tips()
fig = px.strip(df, x="day", y="tip", color="smoker")
fig.show()Creates an interactive strip chart of tip values by day, with points colored by smoking status.
When to use it
Point-level distribution inspection
Show how observations are distributed without hiding outliers behind summary statistics.
Wide-form data exploration
Use several columns as separate distributions when the source data is wide-form.
Interview questions
QWhat does px.strip visualize?
px.strip produces a strip chart: individual points are shown without the box or violin body. It is useful for displaying the distribution of observations across categories.
Follow-up: How can it accept multiple data layouts? It accepts long-form data and also supports wide-form and mixed-form input as a 2D Cartesian Plotly Express function.
QHow are data and columns supplied to px.strip?
The first positional argument is data_frame. Columns can then be supplied by name through arguments such as x, y, and color.
Follow-up: What is a wide-form call? Pass a list of data-frame column names, such as y=["a", "b"], to trigger wide-form processing.
QWhat does the function return?
It returns a Plotly figure generated from the supplied data and encoding options. The figure can be displayed with fig.show() and further configured with Plotly figure methods.
Follow-up: How would you add grouping? Supply a grouping encoding such as color, then customize the returned figure or traces as needed.
Related
px.boxpx.violinpx.scatterplotly.express