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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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()

Tehtävä

Swipe to start coding

Set the 'ticks' style with the 'lightpink' figure.facecolor.
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.

Ratkaisu

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

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Osio 5. Luku 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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