Saving a Plot
For saving a plot in a file on storage disk, savefig() method is used. A file can be saved in many formats like .png, .jpg, .pdf, etc.
Syntax:
pyplot.savefig(fname, dpi=None, facecolor=’w’, edgecolor=’w’, orientation=’portrait’, papertype=None, format=None, transparent=False, bbox_inches=None, pad_inches=0.1, frameon=None, metadata=None)
Example:
Python3
import matplotlib.pyplot as plt# Creating datayear = ['2010', '2002', '2004', '2006', '2008']production = [25, 15, 35, 30, 10]# Plotting barchartplt.bar(year, production)# Saving the figure.plt.savefig("output.jpg")# Saving figure by changing parameter valuesplt.savefig("output1", facecolor='y', bbox_inches="tight", pad_inches=0.3, transparent=True) |
Output:
Data Visualization using Matplotlib
Data Visualization is the process of presenting data in the form of graphs or charts. It helps to understand large and complex amounts of data very easily. It allows the decision-makers to make decisions very efficiently and also allows them in identifying new trends and patterns very easily. It is also used in high-level data analysis for Machine Learning and Exploratory Data Analysis (EDA). Data visualization can be done with various tools like Tableau, Power BI, Python.
In this article, we will discuss how to visualize data with the help of the Matplotlib library of Python.