Notice: This page requires JavaScript to function properly.
Please enable JavaScript in your browser settings or update your browser.
Ecdfplot | Distributions of Data
course content

Course Content

Deep Dive into the seaborn Visualization

Deep Dive into the seaborn Visualization

EcdfplotEcdfplot

An ecdfplot represents the proportion or count of observations falling below each unique value in a dataset. Compared to a histogram or density plot, it has the advantage that each observation is visualized directly, meaning that no binning or smoothing parameters need to be adjusted.

carousel-imgcarousel-imgcarousel-imgcarousel-imgcarousel-imgcarousel-imgcarousel-imgcarousel-img

Task

  1. Create the ecdfplot using the seaborn library:
  • Set the x parameter equals the bill_length_mm;
  • Set the hue parameter equals the 'island';
  • Add the complementary parameter;
  • Set the stat parameter equals the 'count';
  • Set the palette equals the 'mako';
  • Set the data.

Everything was clear?

Section 2. Chapter 4
toggle bottom row
course content

Course Content

Deep Dive into the seaborn Visualization

Deep Dive into the seaborn Visualization

EcdfplotEcdfplot

An ecdfplot represents the proportion or count of observations falling below each unique value in a dataset. Compared to a histogram or density plot, it has the advantage that each observation is visualized directly, meaning that no binning or smoothing parameters need to be adjusted.

carousel-imgcarousel-imgcarousel-imgcarousel-imgcarousel-imgcarousel-imgcarousel-imgcarousel-img

Task

  1. Create the ecdfplot using the seaborn library:
  • Set the x parameter equals the bill_length_mm;
  • Set the hue parameter equals the 'island';
  • Add the complementary parameter;
  • Set the stat parameter equals the 'count';
  • Set the palette equals the 'mako';
  • Set the data.

Everything was clear?

Section 2. Chapter 4
toggle bottom row
some-alt