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David Dalsveen
By the end of this project, you will use Python to wrangle two datasets to visualize the relationships among the data. Datasets are collections of data that may exist in a database, a csv file, or an ordinary file.
Python is a popular language to use work with dataset data. It has tools to read data in various formats, and libraries to visualize the datasets.
Register for this course and see more details by visiting:
OpenCourser.com/course/eouz1h/working
What's inside
Syllabus
Project Overview
By the end of this project, you will use Python to wrangle two datasets to visualize the relationships among the data. Datasets are collections of data that may exist in a database, a csv file, or an ordinary file.
Good to know
Good to know
Know what's good ,
what to watch for , and
possible dealbreakers
Taught by David Dalsveen, who are recognized for their work in data wrangling and visualization
Introduces the Python programming language, a popular choice for working with data and visualization
Provides hands-on practice with data wrangling and visualization techniques
Suitable for beginners looking to build a foundation in data wrangling and visualization
Part of a series of courses on data science, offering a comprehensive learning path for those interested in the field
Save this course
Save Working with Datasets to your list so you can find it easily later:
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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 Working with Datasets with these
activities:
Follow the tutorials on the official Python website
Show steps
The official Python website provides a wealth of tutorials on Python's data analysis libraries, which will help you to learn the basics of these libraries.
Browse courses on
Python
Show steps
-
Find the tutorials on the official Python website.
-
Work through the tutorials at your own pace.
Read the book 'Python for Data Analysis'
Show steps
The book 'Python for Data Analysis' provides a comprehensive overview of Python's data analysis libraries, which will help you to get the most out of the course.
View
Python for Data Analysis
on Amazon
Show steps
-
Read the book from cover to cover.
-
Work through the exercises in the book.
Practice using Python to read and visualize data
Show steps
Practice using Python to read and visualize data, which will help reinforce your understanding of the concepts covered in the course.
Browse courses on
Python
Show steps
-
Find a dataset that you're interested in working with.
-
Use Python to read the dataset into a pandas DataFrame.
-
Use matplotlib or seaborn to create visualizations of the data.
Four other activities
Expand to see all activities and additional details
Show all seven activities
Join a study group with other students
Show steps
Joining a study group will allow you to learn from other students and get help with the course material.
Show steps
-
Find a study group to join.
-
Attend the study group meetings regularly.
-
Participate in the discussions and ask questions.
Create a data visualization project
Show steps
Create a data visualization project to showcase your skills in using Python to read, wrangle, and visualize data.
Browse courses on
Data Visualization
Show steps
-
Choose a dataset that you're interested in working with.
-
Use Python to read the dataset into a pandas DataFrame.
-
Use matplotlib or seaborn to create visualizations of the data.
-
Write a report that describes your project and the insights that you gained from the data.
Participate in a data visualization contest
Show steps
Participating in a data visualization contest will challenge you to use your skills in Python to read, wrangle, and visualize data.
Browse courses on
Data Visualization
Show steps
-
Find a data visualization contest to participate in.
-
Read the contest rules and guidelines.
-
Create a data visualization project that meets the contest requirements.
-
Submit your project to the contest.
Contribute to an open-source data visualization project
Show steps
Contributing to an open-source data visualization project will give you the opportunity to learn from other developers and improve your skills in Python.
Browse courses on
Data Visualization
Show steps
-
Find an open-source data visualization project to contribute to.
-
Read the project documentation and guidelines.
-
Make a contribution to the project.
-
Submit a pull request to the project.
Follow the tutorials on the official Python website
Show steps
The official Python website provides a wealth of tutorials on Python's data analysis libraries, which will help you to learn the basics of these libraries.
Browse courses on
Python
Show steps
Show steps
Show steps
- Find the tutorials on the official Python website.
- Work through the tutorials at your own pace.
Read the book 'Python for Data Analysis'
Show steps
The book 'Python for Data Analysis' provides a comprehensive overview of Python's data analysis libraries, which will help you to get the most out of the course.
View
Python for Data Analysis
on Amazon
Show steps
Show steps
Show steps
- Read the book from cover to cover.
- Work through the exercises in the book.
Practice using Python to read and visualize data
Show steps
Practice using Python to read and visualize data, which will help reinforce your understanding of the concepts covered in the course.
Browse courses on
Python
Show steps
Show steps
Show steps
- Find a dataset that you're interested in working with.
- Use Python to read the dataset into a pandas DataFrame.
- Use matplotlib or seaborn to create visualizations of the data.
Four other activities
Expand to see all activities and additional details
Show all seven activities
Join a study group with other students
Show steps
Joining a study group will allow you to learn from other students and get help with the course material.
Show steps
Show steps
Show steps
- Find a study group to join.
- Attend the study group meetings regularly.
- Participate in the discussions and ask questions.
Create a data visualization project
Show steps
Create a data visualization project to showcase your skills in using Python to read, wrangle, and visualize data.
Browse courses on
Data Visualization
Show steps
Show steps
Show steps
- Choose a dataset that you're interested in working with.
- Use Python to read the dataset into a pandas DataFrame.
- Use matplotlib or seaborn to create visualizations of the data.
- Write a report that describes your project and the insights that you gained from the data.
Participate in a data visualization contest
Show steps
Participating in a data visualization contest will challenge you to use your skills in Python to read, wrangle, and visualize data.
Browse courses on
Data Visualization
Show steps
Show steps
Show steps
- Find a data visualization contest to participate in.
- Read the contest rules and guidelines.
- Create a data visualization project that meets the contest requirements.
- Submit your project to the contest.
Contribute to an open-source data visualization project
Show steps
Contributing to an open-source data visualization project will give you the opportunity to learn from other developers and improve your skills in Python.
Browse courses on
Data Visualization
Show steps
Show steps
Show steps
- Find an open-source data visualization project to contribute to.
- Read the project documentation and guidelines.
- Make a contribution to the project.
- Submit a pull request to the project.
Career center
Learners who complete Working with Datasets will develop knowledge and skills
that may be useful to these careers:
Data Analyst
Data Analyst
A Data Analyst uses data to make business decisions. They collect, clean, and analyze data to identify trends and patterns. They also develop visualizations to communicate their findings to stakeholders. This course can help you build the skills you need to become a Data Analyst by teaching you how to wrangle and visualize data.
Machine Learning Engineer
Machine Learning Engineer
A Machine Learning Engineer builds and deploys machine learning models. They use data to train models that can make predictions or recommendations. This course can help you build the skills you need to become a Machine Learning Engineer by teaching you how to wrangle and visualize data.
Statistician
Statistician
A Statistician uses data to understand the world around them. They collect, analyze, and interpret data to make informed decisions. This course can help you build the skills you need to become a Statistician by teaching you how to wrangle and visualize data.
Data Scientist
Data Scientist
A Data Scientist uses data to solve business problems. They build models to predict future outcomes and identify opportunities for improvement. This course can help you build the skills you need to become a Data Scientist by teaching you how to wrangle and visualize data.
Product Manager
Product Manager
A Product Manager manages the development and launch of products. They work with engineers, designers, and other stakeholders to bring products to market. This course can help you build the skills you need to become a Product Manager by teaching you how to wrangle and visualize data.
Data Engineer
Data Engineer
A Data Engineer builds and maintains data pipelines. They ensure that data is clean, accurate, and accessible. This course can help you build the skills you need to become a Data Engineer by teaching you how to wrangle and visualize data.
Data Visualization Specialist
Data Visualization Specialist
A Data Visualization Specialist creates visualizations that communicate data effectively. They use charts, graphs, and other visual aids to help people understand data. This course can help you build the skills you need to become a Data Visualization Specialist by teaching you how to visualize data.
Market Researcher
Market Researcher
A Market Researcher collects and analyzes data about markets. They use this data to help businesses make decisions about products, services, and marketing campaigns. This course can help you build the skills you need to become a Market Researcher by teaching you how to wrangle and visualize data.
Information Architect
Information Architect
An Information Architect designs and organizes information systems. They ensure that information is easy to find and use. This course can help you build the skills you need to become an Information Architect by teaching you how to wrangle and visualize data.
Librarian
Librarian
A Librarian helps people find and use information. They work in libraries, schools, and other organizations. This course can help you build the skills you need to become a Librarian by teaching you how to wrangle and visualize data.
Project Manager
Project Manager
A Project Manager plans and executes projects. They work with teams to achieve specific goals. This course can help you build the skills you need to become a Project Manager by teaching you how to wrangle and visualize data.
Knowledge Manager
Knowledge Manager
A Knowledge Manager creates and manages knowledge bases. They help people find and use information. This course can help you build the skills you need to become a Knowledge Manager by teaching you how to wrangle and visualize data.
Business Analyst
Business Analyst
A Business Analyst uses data to improve business processes. They work with stakeholders to identify problems and develop solutions. This course can help you build the skills you need to become a Business Analyst by teaching you how to wrangle and visualize data.
Operations Research Analyst
Operations Research Analyst
An Operations Research Analyst uses data to improve the efficiency of operations. They work with businesses to identify problems and develop solutions. This course can help you build the skills you need to become an Operations Research Analyst by teaching you how to wrangle and visualize data.
Software Engineer
Software Engineer
A Software Engineer designs, develops, and maintains software applications. They work with teams to build and deliver software products. This course can help you build the skills you need to become a Software Engineer by teaching you how to wrangle and visualize data.
For more career information including salaries, visit:
OpenCourser.com/course/eouz1h/working
Reading list
We've selected seven 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
Working with Datasets.
Provides a comprehensive overview of Python libraries and tools for data science, including data manipulation, visualization, and machine learning. It valuable resource for learners who want to gain a deeper understanding of Python's capabilities for data analysis.
Practical guide to using Pandas, a popular Python library for data manipulation and analysis. It covers essential topics such as data cleaning, data transformation, and data visualization.
Covers data visualization techniques using Python and JavaScript. It provides a practical approach to creating interactive and informative visualizations.
Provides a comprehensive overview of natural language processing (NLP) techniques using Python. It valuable resource for learners who want to gain a deeper understanding of NLP.
Provides a comprehensive overview of machine learning algorithms and techniques using Python. It valuable resource for learners who want to gain a deeper understanding of machine learning.
Provides a hands-on introduction to data science using Python. It covers essential topics such as data cleaning, data manipulation, and data visualization.
Provides a comprehensive overview of deep learning algorithms and techniques using Python. It valuable resource for learners who want to gain a deeper understanding of deep learning.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/eouz1h/working
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Effort
2 hours
Level
Intermediate
Via
Coursera
Institution
Coursera Project Network
Instructor
David Dalsveen
Language
English
Good to know
Taught by David Dalsveen, who are recognized for their work in data wrangling and visualization
Introduces the Python programming language, a popular choice for working with data and visualization
Provides hands-on practice with data wrangling and visualization techniques
Suitable for beginners looking to build a foundation in data wrangling and visualization
Part of a series of courses on data science, offering a comprehensive learning path for those interested in the field
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