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Cleaning Data

Python Data Playbook

Chris Achard

Cleaning the dataset is an essential part of any data project, but it can be challenging. This course will teach you the basics of cleaning datasets with pandas, and will teach you techniques that you can apply immediately in real world projects.

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Cleaning the dataset is an essential part of any data project, but it can be challenging. This course will teach you the basics of cleaning datasets with pandas, and will teach you techniques that you can apply immediately in real world projects.

At the core of any successful project that involves a real world dataset is a thorough knowledge of how to clean that dataset from missing, bad, or inaccurate data. In this course, Cleaning Data: Python Data Playbook, you'll learn how to use pandas to clean a real world dataset. First, you'll learn how to understand, view, and explore the data you have. Next, you'll explore how to access just the data that you want to keep in your dataset. Finally, you'll discover different ways to handle bad and missing data. When you're finished with this course, you'll have a foundational knowledge of cleaning real world datasets with pandas that will help you as you move forward to working on real world data science or machine learning problems.

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What's inside

Syllabus

Course Overview
Understanding Your Data
Removing and Fixing Columns with pandas
Indexing and Filtering Datasets
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Handling Bad, Missing, and Duplicate Data

Good to know

Know what's good
, what to watch for
, and possible dealbreakers
Develops foundational data cleaning skills for real world projects with Python
Taught by experienced instructors who specialize in data cleaning
Presents a structured approach to cleaning datasets, including understanding the data, removing unwanted columns, handling missing and duplicate data
Utilizes industry-standard Python libraries, such as pandas, for data cleaning
Provides hands-on practice and guided exercises throughout the course
Suitable for learners with prior experience in Python and 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 Cleaning Data: Python Data Playbook with these activities:
Review Data Cleaning Best Practices
Refresh your knowledge of data cleaning best practices, ensuring you are utilizing the most effective techniques in your projects.
Browse courses on Data Cleaning
Show steps
  • Review articles or books on data cleaning.
  • Identify and note key principles and best practices.
Review Python Basics
Review Python fundamentals to reinforce your understanding of basic syntax and data structures.
Show steps
Explore Pandas Data Cleaning Techniques
Seek out and follow tutorials that provide practical examples of pandas data cleaning techniques, solidifying your understanding.
Show steps
  • Identify specific areas of data cleaning you want to improve.
  • Search for tutorials that address those areas.
  • Follow the tutorials and apply the techniques to practice datasets.
Five other activities
Expand to see all activities and additional details
Show all eight activities
Pandas Exercises
Practice manipulating datasets with pandas to improve your proficiency in data cleaning techniques.
Show steps
  • Load a sample dataset into a pandas DataFrame.
  • Explore the data using head() and info().
  • Handle missing data using fillna() or dropna().
Data Cleaning Toolkit
Compile a collection of resources, tools, and techniques for data cleaning, creating a valuable reference for future projects.
Show steps
  • Identify and gather relevant resources.
  • Organize the resources into a structured format.
  • Create documentation that explains the purpose and usage of each resource.
Data Cleaning Peer Review
Engage with peers to review and provide feedback on each other's data cleaning approaches, enhancing your critical thinking and communication skills.
Show steps
  • Find a peer to collaborate with.
  • Select a dataset for cleaning.
  • Clean the dataset independently.
  • Exchange and review each other's cleaned datasets, providing constructive feedback.
Data Cleaning Project
Apply your data cleaning skills to a real-world dataset, demonstrating your ability to manage and prepare data for analysis.
Show steps
  • Obtain a dataset that requires cleaning.
  • Explore the dataset and identify issues that need to be addressed.
  • Apply data cleaning techniques to address the identified issues.
  • Validate the cleaned dataset and ensure it meets the requirements for your analysis.
Data Cleaning Challenge
Participate in a data cleaning challenge to test your skills against others and push your limits in handling complex datasets.
Browse courses on Data Cleaning
Show steps
  • Identify a data cleaning challenge or competition.
  • Prepare your environment and tools.
  • Clean the provided dataset using your best techniques.
  • Validate your cleaned dataset and submit it for evaluation.

Career center

Learners who complete Cleaning Data: Python Data Playbook will develop knowledge and skills that may be useful to these careers:
Data Analyst
Data Analysts help businesses make data-driven decisions by collecting, cleaning, and analyzing data. This course, Cleaning Data: Python Data Playbook, can help you develop the skills needed to succeed as a Data Analyst. The course will teach you how to use pandas to clean real-world datasets, a skill that is essential for any Data Analyst.
See salaries and explore the career path for Data Analyst
Machine Learning Engineer
Machine Learning Engineers build and maintain machine learning models. They use data to train models that can make predictions or decisions. This course, Cleaning Data: Python Data Playbook, can help you develop the skills needed to succeed as a Machine Learning Engineer. The course will teach you how to use pandas to clean real-world datasets, a skill that is essential for any Machine Learning Engineer.
See salaries and explore the career path for Machine Learning Engineer
Data Engineer
Data Engineers design and build data pipelines. They clean, transform, and load data into data warehouses and data lakes. This course, Cleaning Data: Python Data Playbook, can help you develop the skills needed to succeed as a Data Engineer. The course will teach you how to use pandas to clean real-world datasets, a skill that is essential for any Data Engineer.
See salaries and explore the career path for Data Engineer
Statistician
Statisticians collect, analyze, and interpret data. They use statistical methods to draw conclusions about the data and make predictions. This course, Cleaning Data: Python Data Playbook, can help you develop the skills needed to succeed as a Statistician. The course will teach you how to use pandas to clean real-world datasets, a skill that is essential for any Statistician.
See salaries and explore the career path for Statistician
Data Scientist
Data Scientists use data to solve business problems. They collect, clean, and analyze data to build models that can predict future outcomes. This course, Cleaning Data: Python Data Playbook, can help you develop the skills needed to succeed as a Data Scientist. The course will teach you how to use pandas to clean real-world datasets, which is a skill that is essential for any Data Scientist.
See salaries and explore the career path for Data Scientist
Business Analyst
Business Analysts use data to help businesses make better decisions. They analyze data to identify trends and patterns, and they develop recommendations for how to improve business operations. This course, Cleaning Data: Python Data Playbook, can help you develop the skills needed to succeed as a Business Analyst. The course will teach you how to use pandas to clean real-world datasets, a skill that is essential for any Business Analyst.
See salaries and explore the career path for Business Analyst
Financial Analyst
Financial Analysts use data to make investment decisions. They analyze financial data to identify undervalued stocks and bonds. This course, Cleaning Data: Python Data Playbook, can help you develop the skills needed to succeed as a Financial Analyst. The course will teach you how to use pandas to clean real-world datasets, a skill that is essential for any Financial Analyst.
See salaries and explore the career path for Financial Analyst
Marketing Analyst
Marketing Analysts use data to measure the effectiveness of marketing campaigns. They analyze data to identify trends and patterns, and they develop recommendations for how to improve marketing campaigns. This course, Cleaning Data: Python Data Playbook, can help you develop the skills needed to succeed as a Marketing Analyst. The course will teach you how to use pandas to clean real-world datasets, a skill that is essential for any Marketing Analyst.
See salaries and explore the career path for Marketing Analyst
Product Manager
Product Managers develop and launch new products. They use data to make decisions about what features to include in a product and how to market it. This course, Cleaning Data: Python Data Playbook, can help you develop the skills needed to succeed as a Product Manager. The course will teach you how to use pandas to clean real-world datasets, a skill that is essential for any Product Manager.
See salaries and explore the career path for Product Manager
Risk Analyst
Risk Analysts use data to identify and manage risks. They analyze data to identify potential threats and vulnerabilities, and they develop recommendations for how to mitigate risks. This course, Cleaning Data: Python Data Playbook, can help you develop the skills needed to succeed as a Risk Analyst. The course will teach you how to use pandas to clean real-world datasets, a skill that is essential for any Risk Analyst.
See salaries and explore the career path for Risk Analyst
Data Visualization Analyst
Data Visualization Analysts use data to create visual representations of data. They use charts and graphs to help people understand data and make decisions. This course, Cleaning Data: Python Data Playbook, can help you develop the skills needed to succeed as a Data Visualization Analyst. The course will teach you how to use pandas to clean real-world datasets, a skill that is essential for any Data Visualization Analyst.
See salaries and explore the career path for Data Visualization Analyst
Operations Research Analyst
Operations Research Analysts use data to make decisions about how to improve business operations. They analyze data to identify bottlenecks and inefficiencies, and they develop recommendations for how to improve operations. This course, Cleaning Data: Python Data Playbook, can help you develop the skills needed to succeed as an Operations Research Analyst. The course will teach you how to use pandas to clean real-world datasets, a skill that is essential for any Operations Research Analyst.
See salaries and explore the career path for Operations Research Analyst
Quantitative Analyst
Quantitative Analysts use data to make investment decisions. They analyze financial data to identify undervalued stocks and bonds. This course, Cleaning Data: Python Data Playbook, can help you develop the skills needed to succeed as a Quantitative Analyst. The course will teach you how to use pandas to clean real-world datasets, a skill that is essential for any Quantitative Analyst.
See salaries and explore the career path for Quantitative Analyst
Software Engineer
Software Engineers design and develop software applications. They use data to improve the performance and reliability of software applications. This course, Cleaning Data: Python Data Playbook, can help you develop the skills needed to succeed as a Software Engineer. The course will teach you how to use pandas to clean real-world datasets, a skill that is essential for any Software Engineer.
See salaries and explore the career path for Software Engineer
Healthcare Analyst
Healthcare Analysts use data to improve the quality of healthcare. They analyze data to identify trends and patterns, and they develop recommendations for how to improve healthcare delivery. This course, Cleaning Data: Python Data Playbook, can help you develop the skills needed to succeed as a Healthcare Analyst. The course will teach you how to use pandas to clean real-world datasets, a skill that is essential for any Healthcare Analyst.
See salaries and explore the career path for Healthcare Analyst

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 Cleaning Data: Python Data Playbook.
Cover image
Python for Data Analysis
Save
Provides a solid foundation for using pandas for data manipulation. Useful for gaining a deeper understanding of the concepts and techniques covered in the course.
Python for Data Analysis: Data Wrangling with...
Paperback
$$
Python for Data Analysis
Kindle Edition
$$
Python for Data Analysis: Data Wrangling with...
Paperback
$$$
Cover image
Practical Data Privacy
Save
Provides a comprehensive overview of data cleaning techniques and best practices. Useful as a reference tool.
Practical Data Privacy
Kindle Edition
$$
Cover image
Mastering Reinforcement Learning with Python
Save
Offers advanced techniques and best practices for data cleaning with Python. Useful for those seeking a more in-depth understanding of the subject.
Mastering Reinforcement Learning with Python: Build...
Paperback
$$
Mastering Reinforcement Learning with Python: Build...
Kindle Edition
$$
Cover image
Python Data Science Handbook
Save
Offers a comprehensive overview of data science tools and techniques using Python. Provides additional context and depth to the topics covered in the course.
Python Data Science Handbook: Essential Tools for...
Paperback
$$$
Cover image
R for Data Science
Save
Provides a comprehensive overview of data cleaning and exploration using R. Useful for those interested in exploring alternative tools and techniques.
R for Data Science: Import, Tidy, Transform,...
Paperback
$$
(Deutsch) R für Data Science: Daten importieren, bereinigen,...
Kindle Edition
$$$
Cover image
Data Science from Scratch
Save
Provides a foundational understanding of data science concepts and algorithms. Useful as a prerequisite or supplementary resource for those new to the field.
Data Science from Scratch: First Principles with...
Paperback
$$
Data Science from Scratch: First Principles with...
Kindle Edition
$$
Data Science from Scratch: First Principles with...
Paperback
$$

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Course image
Time
68 hours
Level
Introductory
Via
Pluralsight
Instructor
Chris Achard
Language
English
This course belongs to a collection called Python for Data Analysts. It's comprised of 11 courses:
  1. Building Your First Python Analytics Solution
  2. Create and Share Analytics with Jupyter Notebooks
  3. Python for Data Analysts
  4. Programming Python Using an IDE
  5. Leveraging Online Resources for Python Analytics
  6. Importing Data: Python Data Playbook
  7. Cleaning Data: Python Data Playbook (viewing)
  8. Pygal 2: Python Data Playbook
  9. Understanding Databases with SQLAlchemy 1: Python Data Playbook
  10. Web Scraping: Python Data Playbook
  11. Data Wrangling with Python 3
Good to know
Develops foundational data cleaning skills for real world projects with Python
Taught by experienced instructors who specialize in data cleaning
Presents a structured approach to cleaning datasets, including understanding the data, removing unwanted columns, handling missing and duplicate data
Utilizes industry-standard Python libraries, such as pandas, for data cleaning
Provides hands-on practice and guided exercises throughout the course
Suitable for learners with prior experience in Python and data analysis
Share and help others discover this course.
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