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Exploring and Analyzing Fifa's Datasets Using Python

In this 1-hour long project-based course, you will learn how to load a dataset into a pandas dataframe, you will learn how to tidy a messy dataset (Data Tidying), you will get to also visualize the dataset using Matplotlib and seaborn, you will learn how to engineer new features, you will also get to learn how to merge datasets (Data Integration) By the end of this project, you will be able to fully analyze a FIFA dataset using python’s Pandas library. Throughout the tasks you will be able to identify and apply the key aspects about data analysis such as Data Cleaning, Data transformation, Data Visualization , Data tidying and feature engineering. All these skills are crucial to the world of data engineering and are very beneficial in today’s job market that is leaning more and more towards utilizing data in every way Note: This course works best for learners who are based in the North America region. We’re currently working on providing the same experience in other regions.

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This course is perfect for those eager to learn fundamental data analysis skills using Python's Pandas library

This project-based course provides hands-on experience in data cleaning, tidying, visualization, and feature engineering

Fully analyze FIFA dataset using Python Pandas, and apply key aspects of data analysis

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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 Exploring and Analyzing Fifa's Datasets Using Python with these activities:

Watch the guided tutorials in the course

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Watching the guided tutorials will help you to learn the basics of Pandas and data analysis.

Browse courses on Pandas

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Watch the guided tutorials in each module

Review the book Pandas for Data Analysis

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Reviewing this book beforehand will provide you with a solid foundation in using Pandas for data analysis.

View Python for Data Analysis: Data Wrangling with... on Amazon

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Read the first three chapters of the book
Complete the first three Jupyter notebooks in the book's GitHub repository

Complete the practice drills in the course

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Completing the practice drills will help you to practice the skills and knowledge you learn in the course.

Browse courses on Pandas

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Complete the practice drills in each module

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Participate in the peer discussion forums

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Participating in the peer discussion forums will allow you to get help from other students and to share your own knowledge.

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Post questions in the discussion forums
Answer questions from other students

Create a data analysis project using Pandas

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Working on a project will allow you to apply the skills and knowledge you learn in the course to a real-world scenario.

Browse courses on Python

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Choose a dataset to analyze
Load the dataset into a Pandas dataframe
Clean and prepare the data
Analyze the data and draw conclusions
Visualize the data

Create a data visualization using Pandas and Matplotlib

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Creating a data visualization will help you to visualize and understand the data you are analyzing.

Browse courses on Pandas

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Choose a dataset to visualize
Load the dataset into a Pandas dataframe
Create a data visualization using Matplotlib
Save your data visualization

Write a blog post about using Pandas for data analysis

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Writing a blog post will help you to solidify your understanding of Pandas and data analysis.

Browse courses on Pandas

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Choose a topic for your blog post
Research your topic
Write your blog post
Publish your blog post

Participate in data analysis competitions

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Participating in data analysis competitions will allow you to test your skills and to learn from other data analysts.

Browse courses on Pandas

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Find a data analysis competition to participate in
Build a model to solve the competition problem
Submit your model to the competition

Career center

Learners who complete Exploring and Analyzing Fifa's Datasets Using Python will develop knowledge and skills that may be useful to these careers:

Data Analyst

As a Data Analyst, you use data to solve business problems, track key performance indicators, and analyze trends and patterns that help organizations optimize marketing campaigns, improve operations, and reach new customers. This course provides a foundation in data analysis, helping you to clean, visualize, and merge datasets using Python libraries like Pandas, Matplotlib, and Seaborn. This course can help you build the skills necessary to succeed as a Data Analyst as this role requires the ability to gather, analyze, and interpret data to provide insights to stakeholders.

See salaries and explore the career path for Data Analyst

Data Engineer

Data Engineers design and build scalable, reliable, and efficient data systems and infrastructure. They ensure that data is available, accessible, and performant for data analysts and scientists to use in their work. This course provides a foundation in data engineering, helping you to learn how to load data into a Pandas dataframe, transform data using Python code, and merge datasets to create new insights. This course can be especially helpful for those interested in a career as a Data Engineer, as it provides important skills and knowledge in the field

See salaries and explore the career path for Data Engineer

Data Scientist

Data Scientists use data to build models that can predict future outcomes, identify patterns, and help organizations make better decisions. This course provides a foundation in data science, helping you to learn how to clean, visualize, and merge datasets using Python libraries like Pandas, Matplotlib, and Seaborn. This course can help you build the skills necessary to succeed as a Data Scientist as it provides the foundational skills required to work with and analyze data.

See salaries and explore the career path for Data Scientist

Machine Learning Engineer

Machine Learning Engineers build, deploy, and maintain machine learning models that can automate tasks, improve decision-making, and provide personalized experiences. This course provides a foundation in machine learning, helping you to learn how to clean, visualize, and merge datasets using Python libraries like Pandas, Matplotlib, and Seaborn. This course can help you build the skills necessary to succeed as a Machine Learning Engineer as it provides experience in working with and preparing data for machine learning models.

See salaries and explore the career path for Machine Learning Engineer

Business Analyst

Business Analysts use data to understand how businesses operate, identify opportunities for improvement, and develop strategies for growth. This course provides a foundation in business analysis, helping you to learn how to clean, visualize, and merge datasets using Python libraries like Pandas, Matplotlib, and Seaborn. This course can be helpful for those interested in a career as a Business Analyst, as it provides the skills necessary to gather, analyze, and interpret data to make recommendations for business improvement.

See salaries and explore the career path for Business Analyst

Statistician

Statisticians use data to solve problems, make predictions, and draw conclusions. This course provides a foundation in statistics, helping you to learn how to clean, visualize, and merge datasets using Python libraries like Pandas, Matplotlib, and Seaborn. This course can be helpful for those interested in a career as a Statistician, as it provides the skills necessary to work with and analyze data to make informed decisions.

See salaries and explore the career path for Statistician

Quantitative Analyst

Quantitative Analysts use data to build financial models, assess risk, and make investment decisions. This course provides a foundation in quantitative analysis, helping you to learn how to clean, visualize, and merge datasets using Python libraries like Pandas, Matplotlib, and Seaborn. This course can be helpful for those interested in a career as a Quantitative Analyst, as it provides the skills necessary to analyze data to make sound investment decisions.

See salaries and explore the career path for Quantitative Analyst

Data Visualization Engineer

Data Visualization Engineers design and build interactive data visualizations that help users to understand data and make better decisions. This course provides a foundation in data visualization, helping you to learn how to clean, visualize, and merge datasets using Python libraries like Pandas, Matplotlib, and Seaborn. This course can be especially helpful for those interested in a career as a Data Visualization Engineer, as it provides the skills necessary to create visually appealing and informative data visualizations.

See salaries and explore the career path for Data Visualization Engineer

Database Administrator

Database Administrators design, implement, and maintain databases to ensure that data is stored, organized, and accessed efficiently. This course provides a foundation in database administration, helping you to learn how to load data into a database, create and modify tables, and optimize database performance. This course can be helpful for those interested in a career as a Database Administrator.

See salaries and explore the career path for Database Administrator

Information Analyst

Information Analysts gather, analyze, and interpret data to provide insights to stakeholders. This course can provide a foundation in data analysis, helping you to learn how to clean, visualize, and merge datasets using Python libraries like Pandas, Matplotlib, and Seaborn. This course may be helpful for those interested in a career as an Information Analyst, as it provides some of the necessary skills for working with and analyzing data.

See salaries and explore the career path for Information Analyst

Data Architect

Data Architects design and implement data management solutions that meet the needs of an organization. This course provides a foundation in data architecture, helping you to learn how to design and implement data models, integrate data from multiple sources, and ensure data quality. This course may be helpful for those interested in a career as a Data Architect, as it provides some of the necessary knowledge for designing and implementing data management solutions.

See salaries and explore the career path for Data Architect

Business Intelligence Analyst

Business Intelligence Analysts use data to identify trends, patterns, and opportunities that can help organizations make better decisions. This course can provide a foundation in business intelligence, helping you to learn how to clean, visualize, and merge datasets using Python libraries like Pandas, Matplotlib, and Seaborn. This course may be helpful for those interested in a career as a Business Intelligence Analyst, as it provides some of the necessary skills for working with and analyzing data.

See salaries and explore the career path for Business Intelligence Analyst

Financial Analyst

Financial Analysts use data to evaluate financial performance, make investment recommendations, and assess risk. This course can provide a foundation in financial analysis, helping you to learn how to clean, visualize, and merge datasets using Python libraries like Pandas, Matplotlib, and Seaborn. This course may be helpful for those interested in a career as a Financial Analyst, as it provides some of the necessary skills for working with and analyzing financial data.

See salaries and explore the career path for Financial Analyst

Market Researcher

Market Researchers gather and analyze data to understand consumer behavior, market trends, and competitive landscapes. This course can provide a foundation in market research, helping you to learn how to clean, visualize, and merge datasets using Python libraries like Pandas, Matplotlib, and Seaborn. This course may be helpful for those interested in a career as a Market Researcher, as it provides some of the necessary skills for working with and analyzing data.

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Software Engineer

Software Engineers design, develop, and maintain software applications. This course can provide a foundation in software engineering, helping you to learn how to clean, visualize, and merge datasets using Python libraries like Pandas, Matplotlib, and Seaborn. This course may be helpful for those interested in a career as a Software Engineer, as it provides some of the necessary skills for working with and analyzing data in software development.

See salaries and explore the career path for Software Engineer

Reading list

We've selected 12 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 Exploring and Analyzing Fifa's Datasets Using Python.

Python for Data Analysis

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Provides a comprehensive overview of the pandas library, which is used for data cleaning, transformation, and visualization in Python. It valuable resource for understanding the core concepts and techniques of data analysis using pandas.

Exploring and Analyzing Fifa's Datasets Using Python

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