Draw strip plot using jitter parameter
jitter can be used to provide displacements along the horizontal axis, which is useful when there are large clusters of data points. You can specify the amount of jitter (half the width of the uniform random variable support), or just use True for a good default.
Syntax:
seaborn.stripplot(x, y, data, jitter)
Code:
Python3
# Python program to illustrate # Stripplot using inbuilt data-set # given in seaborn # importing the required module import seaborn import matplotlib.pyplot as plt # use to set style of background of plot seaborn. set (style = 'whitegrid' ) # loading data-set tips = seaborn.load_dataset( "tips" ) seaborn.stripplot(x = "day" , y = "total_bill" , data = tips, jitter = 0.1 ) |
Output:
Stripplot using Seaborn in Python
Seaborn is an amazing visualization library for statistical graphics plotting in Python. It provides beautiful default styles and color palettes to make statistical plots more attractive. It is built on top of the matplotlib library and also closely integrated into the data structures from pandas.
Strip plot
A strip plot is drawn on its own. It is a good complement to a boxplot or violinplot in cases where all observations are shown along with some representation of the underlying distribution. It is used to draw a scatter plot based on the category.
Syntax: seaborn.stripplot(*, x=None, y=None, hue=None, data=None, order=None, hue_order=None, jitter=True, dodge=False, orient=None, color=None, palette=None, size=5, edgecolor=’gray’, linewidth=0, ax=None, **kwargs)
Parameters:
- x, y, hue: Inputs for plotting long-form data.
- data: Dataset for plotting.
- order: It is the order to plot the categorical levels in.
- color: It is the color for all of the elements, or seed for a gradient palette
Returns: This method returns the Axes object with the plot drawn onto it.
Example: Basic visualization of “tips” dataset using stripplot()
Python3
import seaborn import matplotlib.pyplot as plt seaborn. set (style = 'whitegrid' ) tip = seaborn.load_dataset( "tips" ) seaborn.stripplot(x = "day" , y = "total_bill" , data = tip) plt.show() |
Output: