Ecdf plots

Overview¶

Empirical cumulative distribution function plots are a way to visualize the distribution of a variable, and Plotly Express has a built-in function, px.ecdf() to generate such plots. Plotly Express is the easy-to-use, high-level interface to Plotly, which operates on a variety of types of data and produces easy-to-style figures.

Alternatives to ECDF plots for visualizing distributions include histograms, violin plots, box plots and strip charts.

Simple ECDF Plots¶

Providing a single column to the x variable yields a basic ECDF plot.

import plotly.express as px
df = px.data.tips()
fig = px.ecdf(df, x="total_bill")
fig.show()

Providing multiple columns leverage's Plotly Express' wide-form data support to show multiple variables on the same plot.

import plotly.express as px
df = px.data.tips()
fig = px.ecdf(df, x=["total_bill", "tip"])
fig.show()

It is also possible to map another variable to the color dimension of a plot.

import plotly.express as px
df = px.data.tips()
fig = px.ecdf(df, x="total_bill", color="sex")
fig.show()

Configuring the Y axis¶

By default, the Y axis shows probability, but it is also possible to show raw counts by setting the ecdfnorm argument to None or to show percentages by setting it to percent.

import plotly.express as px
df = px.data.tips()
fig = px.ecdf(df, x="total_bill", color="sex", ecdfnorm=None)
fig.show()

If a y value is provided, the Y axis is set to the sum of y rather than counts.

import plotly.express as px
df = px.data.tips()
fig = px.ecdf(df, x="total_bill", y="tip", color="sex", ecdfnorm=None)
fig.show()

Reversed and Complementary CDF plots¶

By default, the Y value represents the fraction of the data that is at or below the value on on the X axis. Setting ecdfmode to "reversed" reverses this, with the Y axis representing the fraction of the data at or above the X value. Setting ecdfmode to "complementary" plots 1-ECDF, meaning that the Y values represent the fraction of the data above the X value.

In standard mode (the default), the right-most point is at 1 (or the total count/sum, depending on ecdfnorm) and the right-most point is above 0.

import plotly.express as px
fig = px.ecdf(df, x=[1,2,3,4], markers=True, ecdfmode="standard",
              title="ecdfmode='standard' (Y=fraction at or below X value, this the default)")
fig.show()

In reversed mode, the right-most point is at 1 (or the total count/sum, depending on ecdfnorm) and the left-most point is above 0.

import plotly.express as px
fig = px.ecdf(df, x=[1,2,3,4], markers=True, ecdfmode="reversed",
              title="ecdfmode='reversed' (Y=fraction at or above X value)")
fig.show()

In complementary mode, the right-most point is at 0 and no points are at 1 (or the total count/sum) per the definition of the CCDF as 1-ECDF, which has no point at 0.

import plotly.express as px
fig = px.ecdf(df, x=[1,2,3,4], markers=True, ecdfmode="complementary",
              title="ecdfmode='complementary' (Y=fraction above X value)")
fig.show()

Orientation¶

By default, plots are oriented vertically (i.e. the variable is on the X axis and counted/summed upwards), but this can be overridden with the orientation argument.

import plotly.express as px
df = px.data.tips()
fig = px.ecdf(df, x="total_bill", y="tip", color="sex", ecdfnorm=None, orientation="h")
fig.show()

Markers and/or Lines¶

ECDF Plots can be configured to show lines and/or markers.

import plotly.express as px
df = px.data.tips()
fig = px.ecdf(df, x="total_bill", color="sex", markers=True)
fig.show()

import plotly.express as px
df = px.data.tips()
fig = px.ecdf(df, x="total_bill", color="sex", markers=True, lines=False)
fig.show()

Marginal Plots¶

ECDF plots also support marginal plots

import plotly.express as px
df = px.data.tips()
fig = px.ecdf(df, x="total_bill", color="sex", markers=True, lines=False, marginal="histogram")
fig.show()

import plotly.express as px
df = px.data.tips()
fig = px.ecdf(df, x="total_bill", color="sex", marginal="rug")
fig.show()

ECDF Plots also support faceting

import plotly.express as px
df = px.data.tips()
fig = px.ecdf(df, x="total_bill", color="sex", facet_row="time", facet_col="day")
fig.show()