Зміст курсу
Deep Dive into the seaborn Visualization
Deep Dive into the seaborn Visualization
Ecdfplot
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.
Завдання
- Create the
ecdfplot
using theseaborn
library:
- Set the
x
parameter equals thebill_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.
Дякуємо за ваш відгук!
Ecdfplot
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.
Завдання
- Create the
ecdfplot
using theseaborn
library:
- Set the
x
parameter equals thebill_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.
Дякуємо за ваш відгук!
Ecdfplot
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.
Завдання
- Create the
ecdfplot
using theseaborn
library:
- Set the
x
parameter equals thebill_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.
Дякуємо за ваш відгук!
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.
Завдання
- Create the
ecdfplot
using theseaborn
library:
- Set the
x
parameter equals thebill_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.