JointGrid
JointGrid
is a figure-level function, when the function is called a JointGrid object is instantiated. The function creates a JointGrid object consisting of three axes objects but does not plot anything on it.






import pandas as pd
import seaborn as sns
from matplotlib import pyplot as plt
df = pd.read_csv('filename.csv')
# Creating the JointGrid variable
g = sns.JointGrid(x = 'column_name', y = 'column_name', data = df)
# Creating the inside plot
g.plot_joint(sns.scatterplot)
# Creating the outside plot
g.plot_marginals(sns.histplot)
plt.show()
Swipe to start coding
- Set the
'ticks'
style with the'lightcyan'
figure.facecolor
. - Create a
JointGrid
variableg
:
- Set the
x
parameter equals the'bill_length_mm'
; - Set the
y
parameter equals the'bill_depth_mm'
; - Set the
hue
parameter equals the'species'
; - Set the
'viridis'
palette; - Set the data.
Set the inside plot using the .plot_joint()
function using the g
variable:
- Create a
scatterplot
using theseaborn
; - Set the
alpha
parameter equals0.5
; - Set the
'pink'
edgecolor
parameter; - Set the
linewidth
parameter equals1
.
Set the outside plot using the .plot_marginals()
function:
- Create the
histplot
using theseaborn
; - Add the
kde
parameter.
Lösung
Danke für Ihr Feedback!
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JointGrid
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JointGrid
is a figure-level function, when the function is called a JointGrid object is instantiated. The function creates a JointGrid object consisting of three axes objects but does not plot anything on it.






import pandas as pd
import seaborn as sns
from matplotlib import pyplot as plt
df = pd.read_csv('filename.csv')
# Creating the JointGrid variable
g = sns.JointGrid(x = 'column_name', y = 'column_name', data = df)
# Creating the inside plot
g.plot_joint(sns.scatterplot)
# Creating the outside plot
g.plot_marginals(sns.histplot)
plt.show()
Swipe to start coding
- Set the
'ticks'
style with the'lightcyan'
figure.facecolor
. - Create a
JointGrid
variableg
:
- Set the
x
parameter equals the'bill_length_mm'
; - Set the
y
parameter equals the'bill_depth_mm'
; - Set the
hue
parameter equals the'species'
; - Set the
'viridis'
palette; - Set the data.
Set the inside plot using the .plot_joint()
function using the g
variable:
- Create a
scatterplot
using theseaborn
; - Set the
alpha
parameter equals0.5
; - Set the
'pink'
edgecolor
parameter; - Set the
linewidth
parameter equals1
.
Set the outside plot using the .plot_marginals()
function:
- Create the
histplot
using theseaborn
; - Add the
kde
parameter.
Lösung
Danke für Ihr Feedback!
Awesome!
Completion rate improved to 4.35single