The Plotly Python graphics library creates interactive graphs with online publishing quality. this plot is mainly used when we want to create line plots, scatter plots, area plots, bar charts, error bars, box plots, bar charts, heat maps, helper charts, multi-axis charts, polar charts, and bubble charts.
Seaborn &is a library for generating statistical graphics in Python. It is built on top of matplotlib and integrated with pandas data structures.
1. We are importing seaborn, the only library needed for this simple example.
import seaborn as sns
2. We use the standard default theme, scaling and color palette.
3. We are loading one of the sample datasets.
tips = sns.load_dataset ("tips")
4. We are drawing a polyhedral scatter plot with several semantic variables.
# This Python program will illustrate scatter plot with Seaborn # importing modules import matplotlib.pyplot as plt import seaborn as sns # values for x-axis x = [`Sunday`,` Monday`, `Tuesday`,` Wednesday`, `Thursday`,` Friday`, `Saturday` ] # valueds for y-axis y = [10.5, 12.5, 11.4, 11.2, 9.2, 14.5, 10.1] # plotting with seaborn my_plot = sns.stripplot (x, y); # assigning x-axis and y-axis labels my_plot.set (xlabel = `Day Names`, ylabel =` Turn Over (In Million Dollars) `) # assigning plot title plt.title (` Scatter Plot`); # function to show plot plt.show ()