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Omnya Khaled

By the end of this project, you will be able to add the data in the CSV file to Pandas data frame, plot the graph, and set marker type and color. You will also be able to apply labels, change font size, add grid lines and legends. Finally, you will be able to create the boxplot and save the graph as an image using the matplotlib and seaborn libraries, which are the most important libraries in python that are used for Data Visualization. You can create bar-plots, scatter-plots, histograms, and a lot more with them.

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By the end of this project, you will be able to add the data in the CSV file to Pandas data frame, plot the graph, and set marker type and color. You will also be able to apply labels, change font size, add grid lines and legends. Finally, you will be able to create the boxplot and save the graph as an image using the matplotlib and seaborn libraries, which are the most important libraries in python that are used for Data Visualization. You can create bar-plots, scatter-plots, histograms, and a lot more with them.

This guided project is for people in the field of data and data analysis. people who want to learn python and Pandas library. It provides you with the important steps to be a data analyst. Moreover, it equips you with the knowledge of python's native data structures

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What's inside

Syllabus

Project Overview
By the end of this project, you will be able to add the data in the csv file to Pandas data frame, plot the graph and set marker type and color. You will also be able to apply labels, change font size, add grid lines and legends. Finally, you will be able to create the boxplot and save the graph as an image using the matplotlib and seaborn libraries, which are the most important libraries in python that are used for Data Visualization. You can create bar-plots, scatter-plots, histograms and a lot more with them.

Good to know

Know what's good
, what to watch for
, and possible dealbreakers
Suitable for those in the data visualization and analysis fields
Helps learners gain practical skills in using Python's Pandas library for data manipulation and visualization
Builds upon learners' knowledge of Python's native data structures
Provides hands-on experience in creating visualizations using the Matplotlib and Seaborn libraries
Covers essential topics in data visualization, including bar plots, scatter plots, and histograms

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Reviews summary

Matplotlib for beginners

According to students, this course is a good introduction to Matplotlib. Beginners may find this course is a good place to start, but more could have been done to cover the material.
Course is a good introduction.
"It is an average course."
"Good for beginners."
Beginners might like this course.
"It is an average course."
"Good for beginners."
Felt like more could have been done.
"I wanted an introduction to Matplotlib."
"I just have a feeling that more could have been done during this time."

Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in Plots Creation using Matplotlib Python with these activities:
Review Linear Algebra Concepts
Strengthen your understanding of linear algebra to better grasp the mathematical foundations of data visualization and analysis.
Browse courses on Matrix Operations
Show steps
  • Review matrix operations, such as addition, subtraction, and multiplication.
  • Practice solving systems of linear equations.
Participate in Online Discussion Forums
Engage with fellow students and industry professionals in online discussion forums to exchange knowledge, clarify doubts, and expand your perspectives on data visualization techniques.
Show steps
  • Join online discussion forums relevant to data visualization.
  • Participate in discussions by asking questions and sharing insights.
  • Connect with other members to build a network of professionals in the field.
Data Cleaning Practice
Practice data cleaning to reinforce the concepts covered in the course and improve your data handling skills.
Browse courses on Data Cleaning
Show steps
  • Download a sample dataset
  • Clean the dataset using Pandas
  • Export the cleaned dataset
Two other activities
Expand to see all activities and additional details
Show all five activities
Learn about Seaborn for Data Visualization
Enhance your data visualization skills by exploring Seaborn tutorials to learn advanced techniques for creating visually appealing and informative plots.
Show steps
  • Install the Seaborn library.
  • Follow a Seaborn tutorial to create a scatter plot.
  • Customize your Seaborn plot by adding color palettes and modifying axes.
  • Explore additional Seaborn features for creating histograms and boxplots.
Create a custom data visualization
Creating a custom data visualization will help you apply the theory discussed in the course to a real-world scenario.
Browse courses on Data Visualization
Show steps
  • Choose a visualization type
  • Gather and clean your data
  • Create your visualization
  • Write a summary of your findings

Career center

Learners who complete Plots Creation using Matplotlib Python will develop knowledge and skills that may be useful to these careers:
Data Visualization Engineer
Data Visualization Engineers design and develop interactive data visualizations. This course in Plots Creation using Matplotlib Python provides a solid foundation in data visualization, which is the core skill required for Data Visualization Engineers. The course covers topics such as creating interactive plots, customizing plot appearance, and exporting plots to various formats. Additionally, the course provides hands-on experience in using the matplotlib and seaborn libraries, which are industry-standard tools for data visualization.
Data Scientist
Data Scientists are highly skilled professionals who use their knowledge of statistics, mathematics, and programming to extract insights from large datasets. This course in Plots Creation using Matplotlib Python provides a solid foundation in data visualization, which is a critical component of data science. The course covers topics such as creating bar-plots, scatter-plots, histograms, and boxplots, which are commonly used in data science projects. Additionally, the course provides hands-on experience in using the matplotlib and seaborn libraries, which are industry-standard tools for data visualization.
Data Journalist
Data Journalists use data to tell stories and communicate insights to the public. This course in Plots Creation using Matplotlib Python can provide you with valuable skills in data visualization, which is essential for effectively communicating data-driven stories. The course covers topics such as creating clear and concise graphs, adding labels and legends, and customizing the appearance of plots. Additionally, the course provides hands-on experience in using the matplotlib and seaborn libraries, which are widely used in the field of data journalism.
Data Analyst
Data Analysts are data science professionals who combine mathematical and coding skills to analyze and interpret large datasets. This course in Plots Creation using Matplotlib Python can help you build a strong foundation in data visualization, a crucial skill for Data Analysts. The course covers topics such as adding data to Pandas data frames, plotting graphs, and creating boxplots, which are all essential for effective data analysis. Additionally, the course provides hands-on experience in using the matplotlib and seaborn libraries, which are widely used in the field of data science.
Statistician
Statisticians are experts in the collection, analysis, interpretation, and presentation of data. This course in Plots Creation using Matplotlib Python can help you develop strong skills in data visualization, a key aspect of statistical analysis. The course covers topics such as creating histograms, scatterplots, and boxplots, which are commonly used in statistical analyses. Additionally, the course provides hands-on experience in using the matplotlib and seaborn libraries, which are widely used in the field of statistics.
Business Analyst
Business Analysts use data to help businesses make informed decisions. This course in Plots Creation using Matplotlib Python can provide you with valuable skills in data visualization, which is essential for effectively communicating insights to stakeholders. The course covers topics such as creating clear and concise graphs, adding labels and legends, and customizing the appearance of plots. Additionally, the course provides hands-on experience in using the matplotlib and seaborn libraries, which are widely used in the business world.
Data Architect
Data Architects design and manage data systems. This course in Plots Creation using Matplotlib Python can provide you with valuable skills in data visualization, which is essential for effectively communicating data architecture concepts to stakeholders. The course covers topics such as creating clear and concise graphs, adding labels and legends, and customizing the appearance of plots. Additionally, the course provides hands-on experience in using the matplotlib and seaborn libraries, which are widely used in the field of data architecture.
Data Engineer
Data Engineers are responsible for building and maintaining the infrastructure and processes that support data analysis and data science. This course in Plots Creation using Matplotlib Python can help you develop strong skills in data visualization, which is essential for effectively communicating data engineering concepts to stakeholders. The course covers topics such as creating clear and concise graphs, adding labels and legends, and customizing the appearance of plots. Additionally, the course provides hands-on experience in using the matplotlib and seaborn libraries, which are widely used in the field of data engineering.
Market Researcher
Market Researchers collect and analyze data to understand consumer behavior and market trends. This course in Plots Creation using Matplotlib Python can provide you with valuable skills in data visualization, which is essential for effectively communicating market research insights to stakeholders. The course covers topics such as creating clear and concise graphs, adding labels and legends, and customizing the appearance of plots. Additionally, the course provides hands-on experience in using the matplotlib and seaborn libraries, which are widely used in the field of market research.
Machine Learning Engineer
Machine Learning Engineers build and maintain machine learning models. This course in Plots Creation using Matplotlib Python can provide you with valuable skills in data visualization, which is crucial for understanding and debugging machine learning models. The course covers topics such as creating scatterplots, histograms, and ROC curves, which are commonly used in machine learning. Additionally, the course provides hands-on experience in using the matplotlib and seaborn libraries, which are widely used in the field of machine learning.
Quantitative Analyst
Quantitative Analysts use mathematical and statistical models to analyze financial data. This course in Plots Creation using Matplotlib Python can provide you with valuable skills in data visualization, which is essential for effectively communicating financial insights to stakeholders. The course covers topics such as creating clear and concise graphs, adding labels and legends, and customizing the appearance of plots. Additionally, the course provides hands-on experience in using the matplotlib and seaborn libraries, which are widely used in the financial industry.
UX Researcher
UX Researchers study how users interact with products and services. This course in Plots Creation using Matplotlib Python can provide you with valuable skills in data visualization, which is increasingly important for UX Researchers. The course covers topics such as creating clear and concise graphs, adding labels and legends, and customizing the appearance of plots. Additionally, the course provides hands-on experience in using the matplotlib and seaborn libraries, which are widely used in the field of UX research.
Database Administrator
Database Administrators manage and maintain databases. This course in Plots Creation using Matplotlib Python can provide you with valuable skills in data visualization, which is increasingly important for Database Administrators. The course covers topics such as creating clear and concise graphs, adding labels and legends, and customizing the appearance of plots. Additionally, the course provides hands-on experience in using the matplotlib and seaborn libraries, which are widely used in the field of database administration.
Product Manager
Product Managers are responsible for the development and launch of new products. This course in Plots Creation using Matplotlib Python can provide you with valuable skills in data visualization, which is increasingly important for Product Managers. The course covers topics such as creating clear and concise graphs, adding labels and legends, and customizing the appearance of plots. Additionally, the course provides hands-on experience in using the matplotlib and seaborn libraries, which are widely used in the field of product management.
Software Engineer
Software Engineers design, develop, and maintain software applications. This course in Plots Creation using Matplotlib Python can provide you with valuable skills in data visualization, which is increasingly important in software development. The course covers topics such as creating interactive plots, customizing plot appearance, and exporting plots to various formats. Additionally, the course provides hands-on experience in using the matplotlib and seaborn libraries, which are popular choices for data visualization in the software engineering industry.

Reading list

We've selected six books that we think will supplement your learning. Use these to develop background knowledge, enrich your coursework, and gain a deeper understanding of the topics covered in Plots Creation using Matplotlib Python.
Provides a comprehensive overview of the Python data science ecosystem, including data cleaning, analysis, visualization, and machine learning. It is an excellent resource for learners who want to learn more about the fundamentals of data science using Python.
Provides a comprehensive overview of the Python data analysis ecosystem, including data cleaning, manipulation, and analysis. It is an excellent resource for learners who want to learn more about the fundamentals of data analysis using Python.
Provides a practical introduction to data visualization. It covers a wide range of topics, from the basics of data visualization to more advanced techniques such as interactive visualization and geospatial data visualization. It is an excellent resource for learners who want to learn more about the fundamentals of data visualization.
Provides a comprehensive overview of the Python data analysis ecosystem. It covers a wide range of topics, from data cleaning and manipulation to data analysis and visualization. It is an excellent resource for learners who want to learn more about the Python data analysis ecosystem.
Provides a quick reference to the Pandas library. It is an excellent resource for learners who want to quickly look up information about the Pandas library.
Provides a quick reference to the SciPy library. It is an excellent resource for learners who want to quickly look up information about the SciPy library.

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