Matplotlib Course Objectives

This Python Matplotlib course focuses on providing knowledge on various plots and their respective methods available as a part of the library that can be applied to the graphs. It lets you dig deep into the Matplotlib library for data visualization using different plots. Starting from basic plots like line and scatter plots, this Matplotlib course also covers other plots including histogram, Bar, Pie, and Box plots.

Matplotlib is a popular, fast, and easy to use Python library used for visualizing data using various plots and analyzing information from the obtained graphs. Built as an extension of NumPy, various visual data plots can be generated using Matplotlib.

In addition, this Matplotlib course consists of 2-D histograms, Violin plots, Bubble Charts, and Donut Charts. As a part of this Matplotlib course, customization of the plots is also taught which includes modifying axis, changing color and line styles, adding titles, labels, and legend, changing font sizes and axis limits, etc. Finally, it covers the basics of 3-dimensional plots.

This Python library comes with various static, animated, and interactive plots including box plots, bar graphs, histograms, etc. It also comes with respective methods to customize plots, plot multiple graphs, and export the obtained graphs.

Converting both theoretical and coding examples, including quizzes, this Matplotlib course lets you have complete knowledge on data visualization and related concepts with python. In addition it also comes with some real time projects to let you complete grasp on matplotlib.

Designed for both beginners and professionals, this matplotlib course allows users to grasp respective concepts with ease. The topics covered in this Matplotlib course help the learners to comprehend the Python programming fundamentals for data visualization.

With easy to code and understandable Python syntax, makes it easy for everyone to learn it. Also the simple and handy built in functions available as a part of matplotlib library adds to it making it easy for the learner to code for visualizing the data.

To conclude, this Matplotlib course is the place for learning the Python library matplotlib and grabbing the visualization concepts under one roof.

This course comes covers the matolptlib basic plots to 3D plots including

1. Simple plots like line and scatter plots
2. Modifying the graphs like changing line style, adding text and legends to graphs, etc.
3. Customizing axis with respect to ticks and axis limits
4. Other plots such as bar graphs, pie charts, box plots and many more
5. Stacking multiple plots and 3D plots

This Matplotlib course also includes coding examples and quizzes to give practical knowledge. And also real time projects are discussed to give hands on experience for the participants. With the increasing opportunities in the industry involving data, the knowledge of Matplotlib and data visualization skills will help you get a job of interest.

Designed to cover all the fundamental topics related to visualization with matplotlib, this Matplotlib course aims to help the students get one’s hands on the library, expertise themselves with coding and landing in a good job.

Why should you learn Matplotlib?

• The global data visualization market is growing at a CAGR of 9.69% over the forecast period.
• Matplotlib is the oldest Python plotting library, and it’s still the most popular
• Matplotlib is fundamental to other libraries built on top of it including pandas and Seaborn
• Top companies including Walmart, Apple, and Tesla use Matplotlib
• Employees who knows Data Visualization earn an average of ₹20.1lakhs, mostly ranging from ₹15.0lakhs to ₹46.2lakhs.
• Studies predict that the data visualization market is going to grow at a CAGR of 9.69% over the forecast period globally.
• Data visualization job has a growth rate of 36%, which is much faster than the average for other jobs
• Research says that about 15% of arXiv papers use the Matplotlib library

What is Matplotlib?

Data visualization is a complex field that transforms raw data into a graphical dimension, including descriptive statistics, quantitative analysis, and storytelling. It is becoming more and more applied in many different domains with an increase in the use of data. Matplotlib is an open source and cross-platform Python library used for Data visualization. It is a complete package with a wide range of graphical tools and is simple to use. It is a library useful for any Python and NumPy user. It can also be used with graphics toolkits available in Python like Tkinter, PyQt, and wxPython. Most of its utilities are under the pyplot submodule which allows for creating various quality plots for data and making interactive figures that can be zoomed, updated, and also customizing can be done with respect to visual style and layout. Multiple plots can be plotted using this library including bar, line, scatter, histogram, etc. to better represent the data through the graph. In addition, 3D charting is also possible with this library. This allows us to easily analyze the data more efficiently and make specific decisions according to data analysis. Also, Matplotlib is an exceptionally fast library with a variety of built in operations. In addition, it also allows to export the visualizations many image formats, including PDF, SVG, JPG, PNG, BMP, and GIF. Also, a large number of third party Python packages extend and build on Matplotlib functionality, including seaborn and Pandas. Thus, it acts as one of the foundation libraries to learn for obtaining data visualization and data analytics skills. It is used by many companies in various domains to analyze data, build machine learning models, create websites, and program software. Many popular and massive companies including Walmart, Tesla, Apple, Lockheed Martin, etc. use Matplotlib for exploratory data analysis and publishing relevant information from the data. It is also used for other applications such as web application servers, shells, and Python scripts.

What to do before you begin?

Matplotlib is one of the popular Python libraries used for data visualization. So, it is suggested that the learner has a basic understanding of the Python Programming language and its syntax to easily code. It is also suggested that the learner has a PC or laptop with a minimum of an i3 processor, a 20GB disk, and 4 GB RAM with a Python compiler installed in the system for doing the coding examples and implementing projects.

Who should go for this free Matplotlib course?

This course is designed for anyone interested in increasing their skills in Matplotlib and Python and for those looking for any courses to land a job in the field of data science. Design from scratch this course covers all the topics for you to master the skills of data visualization and data analysis. Thus, this matplotlib course is for both freshers and professionals having knee to learn python matplotlib. This Matplotlib course consists of concepts that can help you in landing the respective job. It is best suited for:

1. Freshers looking for Python job
2. IT Developers looking for migrating to job involving Data handling
3. Data analysts looking for coding skills in Python
4. Machine Learning engineers searching for pre processing skills
5. Python engineers looking for data visualizations jobs

By enrolling in our Matplotlib course, you can expect the following benefits:

This matplotlib training comes with many benefits starting from basics to mastering the matplotlib library. Being a cross-platform library with simple syntax requiring a lesser number of lines of code for MATLAB, this library is easy to learn for any user. Developed as an alternative to MATLAB, it is an open source library used for data visualization and graphical plotting of data with Python. This course contains concepts that help you learn fundamentals of matplotlib library and its features. It also helps you understand the different plot types available including line plots, scatter plots, bar graphs, pie plots, and many more. In addition, customizing the plots with changing axis, adding texts, legends, and many more are discussed. Finally, stacking multiple plots using subplots and 3D plots such as Line and Scatter Plots and viewing them from different angles are covered. This Matplotlib course will guide you through all the possible techniques required for plotting appropriate graphs from the given data. And also analyzing the obtained plots for getting the information from the data, making you build your confidence in using the latest tools and technologies related to data visualization. Thus, making you communicate relevant information and presenting relevant insights from the data, is an important requirement for any data scientist. In addition to this, this Matplotlib course includes coding examples, quizzes, and real time projects that give hands on experience with respect to the library and lets you explore the main functionalities of Matplotlib. Also, the course material is downloadable for availing the concepts both online and offline for the learner. This Matplotlib course is inclusive of certification on completion of the course. Helping you expand your expertise with the concepts of data visualization by coding to plot various customizable plots with matplotlib, this Matplotlib course will help you grab a job in respective field. Also, placement guidance is given as a part of this course to help you land in job of your choice. Throughout this Matplotlib course, you will learn: On getting trained with out Matplotlib couse, the participants will get to learn skills to visualize data using Python. You will also learn different plots and related methods to customize the graphs. Through the coding examples and projects, the training will provide hands on experience to the trainers. The complete course is organized to make the trainer master data visualization and analysis skills. During the course, you will learn

1. Line and Scatter Plots
2. Other plots bar, pie charts, histograms, box plots, bubble charts, etc.
3. Customize the plots with respect to axis, color, and line styles
4. Add titles, labels, and legends
5. Adjust the size of the plots
6. Using figures and subplots
7. Understand basic 3D plotting

Jobs after Learning this Matplotlib Course

Matplotlib is an open source, powerful, and fast Python library built as an extension to Numpy library that allows users easy data visualization. It consists of various methods for different plots and charts. Also, it allows you to customize the graphs including scatter plot, box plot, histograms, etc. and also multiple plots using subplots. It also consists of methods to draw 3-dimensional plots. In addition, it allows exporting of the graphs obtained in various popular image formats. This is not only an amazing visualization library, but also a foundation for other various Python libraries including Seaborn and Pandas. It is used widely in the industries of various domains involving data analysis. It is a complete plotting package useful for making graphical plotting of data. This library is being used not only within the data science industry but also in other domains dealing with data to communicate the findings of data and make important statistical conclusions. Matplotlibs is one of the popular Python libraries used for data visualization. It provides different options for people looking for a job in the data visualization and analysis domain. The increasing use and growth of the Python programming language in various industries has raised the number of job opportunities. Also the tremendous increase in the use of data and the information obtained from the data in various industrial domains, led to increase in the number of job positions. Different industries including medical, business, education, etc. are providing multiple jobs. With increasing use of data in various sectors, the importance and utilization of this library and the need for people with respective skills has increased. Some of the job opportunities available for people with Matplotlib knowledge and respective coding skills are as follows:

1. Data Analyst
2. Machine Learning Engineers
3. Data Enginners
4. Python Developer, AI/ML
5. Automated Software Engineer
6. Visualization Engineer
7. Research analyst
8. Data scientist
9. Test engineer

Our students are working in leading organizations