Contenido del Curso
First Dive into seaborn Visualization
First Dive into seaborn Visualization
I'm an Artist, that's how I See it!
We mentioned that the seaborn
is based on the matplotlib
. That is why all seaborn
styles are set using matplotlib
functions.
We can use the axes_style()
function with no arguments to see which functions are used for the current style.
And then, we have the opportunity to adjust the desired parameters manually and create our unique style!
To change individual style settings manually:
Try this code to look at the customized plot:
import seaborn as sns import numpy as np import matplotlib.pyplot as plt # Generate random data for the line plot x = np.linspace(0, 10, 100) y = np.sin(x) # Set the style of the plot using sns.set_style() sns.set_style('whitegrid', {'axes.facecolor': 'lightgrey', 'grid.color': 'white', 'grid.linewidth': 1}) # Create the line plot using sns.lineplot() sns.lineplot(x = x, y = y, color = 'blue') # Add a title and axis labels to the plot plt.title('Lineplot') plt.xlabel('X-axis') plt.ylabel('Y-axis') # Display the plot plt.show()
Tarea
- Import
seaborn
withsns
alias. - Import
matplotlib.pyplot
withplt
alias. - Import
pandas
withpd
alias. - Set
'whitegrid'
style with'xtick.color' - white
,'ytick.color' - white
,'figure.facecolor' - grey
,'font.family'- ['monospace']
. - Rotate labels along the Ox axis by 45 degrees.
- Show the plot.
¡Gracias por tus comentarios!
I'm an Artist, that's how I See it!
We mentioned that the seaborn
is based on the matplotlib
. That is why all seaborn
styles are set using matplotlib
functions.
We can use the axes_style()
function with no arguments to see which functions are used for the current style.
And then, we have the opportunity to adjust the desired parameters manually and create our unique style!
To change individual style settings manually:
Try this code to look at the customized plot:
import seaborn as sns import numpy as np import matplotlib.pyplot as plt # Generate random data for the line plot x = np.linspace(0, 10, 100) y = np.sin(x) # Set the style of the plot using sns.set_style() sns.set_style('whitegrid', {'axes.facecolor': 'lightgrey', 'grid.color': 'white', 'grid.linewidth': 1}) # Create the line plot using sns.lineplot() sns.lineplot(x = x, y = y, color = 'blue') # Add a title and axis labels to the plot plt.title('Lineplot') plt.xlabel('X-axis') plt.ylabel('Y-axis') # Display the plot plt.show()
Tarea
- Import
seaborn
withsns
alias. - Import
matplotlib.pyplot
withplt
alias. - Import
pandas
withpd
alias. - Set
'whitegrid'
style with'xtick.color' - white
,'ytick.color' - white
,'figure.facecolor' - grey
,'font.family'- ['monospace']
. - Rotate labels along the Ox axis by 45 degrees.
- Show the plot.
¡Gracias por tus comentarios!
I'm an Artist, that's how I See it!
We mentioned that the seaborn
is based on the matplotlib
. That is why all seaborn
styles are set using matplotlib
functions.
We can use the axes_style()
function with no arguments to see which functions are used for the current style.
And then, we have the opportunity to adjust the desired parameters manually and create our unique style!
To change individual style settings manually:
Try this code to look at the customized plot:
import seaborn as sns import numpy as np import matplotlib.pyplot as plt # Generate random data for the line plot x = np.linspace(0, 10, 100) y = np.sin(x) # Set the style of the plot using sns.set_style() sns.set_style('whitegrid', {'axes.facecolor': 'lightgrey', 'grid.color': 'white', 'grid.linewidth': 1}) # Create the line plot using sns.lineplot() sns.lineplot(x = x, y = y, color = 'blue') # Add a title and axis labels to the plot plt.title('Lineplot') plt.xlabel('X-axis') plt.ylabel('Y-axis') # Display the plot plt.show()
Tarea
- Import
seaborn
withsns
alias. - Import
matplotlib.pyplot
withplt
alias. - Import
pandas
withpd
alias. - Set
'whitegrid'
style with'xtick.color' - white
,'ytick.color' - white
,'figure.facecolor' - grey
,'font.family'- ['monospace']
. - Rotate labels along the Ox axis by 45 degrees.
- Show the plot.
¡Gracias por tus comentarios!
We mentioned that the seaborn
is based on the matplotlib
. That is why all seaborn
styles are set using matplotlib
functions.
We can use the axes_style()
function with no arguments to see which functions are used for the current style.
And then, we have the opportunity to adjust the desired parameters manually and create our unique style!
To change individual style settings manually:
Try this code to look at the customized plot:
import seaborn as sns import numpy as np import matplotlib.pyplot as plt # Generate random data for the line plot x = np.linspace(0, 10, 100) y = np.sin(x) # Set the style of the plot using sns.set_style() sns.set_style('whitegrid', {'axes.facecolor': 'lightgrey', 'grid.color': 'white', 'grid.linewidth': 1}) # Create the line plot using sns.lineplot() sns.lineplot(x = x, y = y, color = 'blue') # Add a title and axis labels to the plot plt.title('Lineplot') plt.xlabel('X-axis') plt.ylabel('Y-axis') # Display the plot plt.show()
Tarea
- Import
seaborn
withsns
alias. - Import
matplotlib.pyplot
withplt
alias. - Import
pandas
withpd
alias. - Set
'whitegrid'
style with'xtick.color' - white
,'ytick.color' - white
,'figure.facecolor' - grey
,'font.family'- ['monospace']
. - Rotate labels along the Ox axis by 45 degrees.
- Show the plot.