Lets visualize our data with Strip Plot which is present in Seaborn library. We can also use Strip Plot in conjunction with Box Plot and Violin Plot.
We can pass various parameters to stripplot like jitter, hue, dodge, order, palette, color, edgecolor, alpha, linewidth, marker, size etc.
Lets explore Strip Plot using Tips dataset.
Step 1: Import required libraries
import numpy as np
import pandas as pd
import seaborn as sns
import matplotlib.pyplot as plt
%matplotlib inline
Step 2: Load Tips dataset
tips=sns.load_dataset('tips')
tips.head()
Step 3: Explore data using Strip Plot
Strip Plot is both univariate and bivariate. Lets analyze it first by using one variable and then we will use two variables.
Visualizing one variable using Strip Plot
sns.stripplot(x=tips['tip'])
sns.stripplot(x=tips['total_bill'])
sns.stripplot(x='total_bill', data=tips)
sns.stripplot(x='total_bill', data=tips, color='green')
Visualizing two variables using Strip Plot
sns.stripplot(x='day', y='total_bill', data=tips)
sns.stripplot(x='total_bill', y='day', data=tips)
Add jitter parameter
sns.stripplot(x='day', y='total_bill', data=tips, jitter=False)
sns.stripplot(x='day', y='total_bill', data=tips, jitter=0.3)
sns.stripplot(x='day', y='total_bill', data=tips, jitter=0.3, linewidth=1.2)
Add hue and dodge parameter
sns.stripplot(x='day', y='total_bill', data=tips, hue='sex')
sns.stripplot(x='day', y='total_bill', data=tips, hue='sex', jitter=False)
sns.stripplot(x='day', y='total_bill', data=tips, hue='sex', dodge=True)
sns.stripplot(x='day', y='total_bill', data=tips, hue='sex', dodge=True, palette='winter_r')
sns.stripplot(x='day', y='total_bill', data=tips, hue='sex', dodge=True, palette='winter_r', order=['Sat', 'Sun', 'Thur', 'Fri'])
sns.stripplot(x='day', y='total_bill', data=tips, hue='sex', dodge=True, marker='D')
sns.stripplot(x='day', y='total_bill', data=tips, hue='sex', dodge=True, marker='D', size=10)
sns.stripplot(x='day', y='total_bill', data=tips, hue='sex', dodge=True, marker='D', size=10, edgecolor='gray', alpha=0.3)
Combining Strip Plot and Box Plot
sns.stripplot(x='day', y='total_bill', data=tips)
sns.boxplot(x='day', y='total_bill', data=tips)
sns.stripplot(x='day', y='total_bill', data=tips, jitter=False, palette='husl', color=0.1)
sns.boxplot(x='day', y='total_bill', data=tips)
Combining Strip Plot and Violin Plot
sns.stripplot(x='day', y='total_bill', data=tips, jitter=False, palette='husl', color=0.1)
sns.violinplot(x='day', y='total_bill', data=tips)
sns.stripplot(x='day', y='total_bill', data=tips, jitter=False, palette='husl', color=0.1)
sns.violinplot(x='day', y='total_bill', data=tips, color='grey')
You can download my Jupyter notebook from here. I recommend to also try above code with Iris dataset.
We can pass various parameters to stripplot like jitter, hue, dodge, order, palette, color, edgecolor, alpha, linewidth, marker, size etc.
Lets explore Strip Plot using Tips dataset.
import numpy as np
import pandas as pd
import seaborn as sns
import matplotlib.pyplot as plt
%matplotlib inline
Step 2: Load Tips dataset
tips=sns.load_dataset('tips')
tips.head()
Step 3: Explore data using Strip Plot
Strip Plot is both univariate and bivariate. Lets analyze it first by using one variable and then we will use two variables.
Visualizing one variable using Strip Plot
sns.stripplot(x=tips['tip'])
sns.stripplot(x=tips['total_bill'])
sns.stripplot(x='total_bill', data=tips)
sns.stripplot(x='total_bill', data=tips, color='green')
Visualizing two variables using Strip Plot
sns.stripplot(x='day', y='total_bill', data=tips)
sns.stripplot(x='total_bill', y='day', data=tips)
Add jitter parameter
sns.stripplot(x='day', y='total_bill', data=tips, jitter=False)
sns.stripplot(x='day', y='total_bill', data=tips, jitter=0.3)
sns.stripplot(x='day', y='total_bill', data=tips, jitter=0.3, linewidth=1.2)
Add hue and dodge parameter
sns.stripplot(x='day', y='total_bill', data=tips, hue='sex')
sns.stripplot(x='day', y='total_bill', data=tips, hue='sex', jitter=False)
sns.stripplot(x='day', y='total_bill', data=tips, hue='sex', dodge=True)
sns.stripplot(x='day', y='total_bill', data=tips, hue='sex', dodge=True, palette='winter_r')
sns.stripplot(x='day', y='total_bill', data=tips, hue='sex', dodge=True, palette='winter_r', order=['Sat', 'Sun', 'Thur', 'Fri'])
sns.stripplot(x='day', y='total_bill', data=tips, hue='sex', dodge=True, marker='D')
sns.stripplot(x='day', y='total_bill', data=tips, hue='sex', dodge=True, marker='D', size=10)
sns.stripplot(x='day', y='total_bill', data=tips, hue='sex', dodge=True, marker='D', size=10, edgecolor='gray', alpha=0.3)
Combining Strip Plot and Box Plot
sns.stripplot(x='day', y='total_bill', data=tips)
sns.boxplot(x='day', y='total_bill', data=tips)
sns.stripplot(x='day', y='total_bill', data=tips, jitter=False, palette='husl', color=0.1)
sns.boxplot(x='day', y='total_bill', data=tips)
Combining Strip Plot and Violin Plot
sns.stripplot(x='day', y='total_bill', data=tips, jitter=False, palette='husl', color=0.1)
sns.violinplot(x='day', y='total_bill', data=tips)
sns.stripplot(x='day', y='total_bill', data=tips, jitter=False, palette='husl', color=0.1)
sns.violinplot(x='day', y='total_bill', data=tips, color='grey')
You can download my Jupyter notebook from here. I recommend to also try above code with Iris dataset.
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