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Lära PairGrid | Multi-Plot Grids
Deep Dive into the seaborn Visualization

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PairGrid

PairGrid is a subplot grid for plotting pairwise relationships in a dataset.

This object maps each variable in a dataset onto a column and row in a grid of multiple axes. Different axes-level plotting functions can be used to draw bivariate plots in the upper and lower triangles, and then the marginal distribution of each variable can be shown on the diagonal.

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python
import pandas as pd
import seaborn as sns
from matplotlib import pyplot as plt

df = pd.read_csv('filename.csv')

# Creating the PairGrid variable
g = sns.PairGrid(df)

# Setting diagonale plots
g.map_diag(sns.histplot)

# Setting non-diagonal plots
g.map_offdiag(sns.scatterplot)

plt.show()
Uppgift

Swipe to start coding

  1. Set the 'ticks' style with the 'lightpink' figure.facecolor.
  2. Create a PairGrid variable using g:
  • Set the data for the g;
  • Set the hue parameter equals the 'species';
  • Set the 'rocket_r' palette.

Set diagonale plots using the .map_diag() function:

  • Create a histplot using the seaborn;
  • Add the kde parameter.

Set non-diagonale plots using the .map_offdiag() function:

  • Create a scatterplot using the seaborn;
  • Set the linewidth parameter equals 0.9;
  • Set the 'purple' edgecolor parameter.

Lösning

import warnings

# Ignore all warnings
warnings.filterwarnings('ignore')


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

df = pd.read_csv('https://codefinity-content-media.s3.eu-west-1.amazonaws.com/66ba0c8e-8422-413c-b7e1-74bd24c61656/penguins_upd.csv')
# Cleaning useless columns
df = df.drop(['Unnamed: 0'], axis=1)

# Set the 'ticks' style with the 'lightpink' facecolor
sns.set_style('ticks', {'figure.facecolor' : 'lightpink'})
# Create a PairGrid variable
g = sns.PairGrid(# Set the data
df,
# Set the hue
hue = 'species',
# Set the palette
palette = 'rocket_r',
# Setting the diag_sharey
diag_sharey = False)
# Set the diagonale plot using the .map_diag() function
g.map_diag(# Create a histplot
sns.histplot,
# Set the kde
kde = True)
# Set non-diagonale plots using the .map_offdiag() function
g.map_offdiag(# Create a scatterplot
sns.scatterplot,
# Set the linewidth
linewidth = 0.9,
# Set the edgecolor

Var allt tydligt?

Hur kan vi förbättra det?

Tack för dina kommentarer!

Avsnitt 5. Kapitel 2
import warnings

# Ignore all warnings
warnings.filterwarnings('ignore')


# Importing libraries needed
import pandas as pd
import seaborn as sns
import matplotlib.pyplot as plt

# Reading the file
df = pd.read_csv('https://codefinity-content-media.s3.eu-west-1.amazonaws.com/66ba0c8e-8422-413c-b7e1-74bd24c61656/penguins_upd.csv')
# Cleaning useless columns
df = df.drop(['Unnamed: 0'], axis=1)

# Set the 'ticks' style with the 'lightpink' facecolor
sns.set_style('___', {'figure.facecolor' : '___'})
# Create a PairGrid variable
g = ___(# Set the data
___,
# Set the hue
___ = 'species',
# Set the palette
___,
# Setting the diag_sharey
diag_sharey = False)
# Set diagonale plots using the .map_diag() function
g.___(# Create a histplot
___,
# Set the kde
kde = ___)
# Set non-diagonale plots using the .map_offdiag() function
g.___(# Create a scatterplot
___,
# Set the linewidth
___ = 0.9,
# Set the edgecolor
___)

# Adding the legend
g.add_legend()
# Displaying the plot
plt.show()

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