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Impara I'm an Artist, that's how I See it! | Plot Customization
First Dive into seaborn Visualization

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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:

python
import seaborn as sns
# Setting the unique style
sns.set_style('style_name', {'axes.facecolor': 'red', 'grid.color': 'black',...})

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()
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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()
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Compito

Swipe to start coding

  1. Import seaborn with sns alias.
  2. Import matplotlib.pyplot with plt alias.
  3. Import pandas with pd alias.
  4. Set 'whitegrid' style with 'xtick.color' - white, 'ytick.color' - white, 'figure.facecolor' - grey, 'font.family'- ['monospace'].
  5. Rotate labels along the Ox axis by 45 degrees.
  6. Show the plot.

Soluzione

import seaborn as sns
import matplotlib.pyplot as plt
import pandas as pd

df = pd.read_csv('https://codefinity-content-media.s3.eu-west-1.amazonaws.com/c5b4ea8f-8a30-439f-9625-ddf2effbd9ac/bamboo.csv')

sns.set_style('whitegrid', {'xtick.color':'white', 'ytick.color':'white', 'figure.facecolor':'grey', 'font.family':['monospace']})

sns.countplot(x = 'Bamboo', data = df)

plt.xticks(rotation = 45)

plt.show()

Tutto è chiaro?

Come possiamo migliorarlo?

Grazie per i tuoi commenti!

Sezione 3. Capitolo 5
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# Import libraries needed
___
___
___

# Reading the file
df = pd.read_csv('https://codefinity-content-media.s3.eu-west-1.amazonaws.com/c5b4ea8f-8a30-439f-9625-ddf2effbd9ac/bamboo.csv')

# Set the unique style
sns.set_style('___', {'___' : '___', '___' : '___', '___' : '___', 'font.family' : ['___']})

# Creating the countplot
sns.countplot(x = 'Bamboo', data = df)

# Rotate
plt.___(___)

# Show the plot
___

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