Data Wrangling with Python 3

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In this course, Data Wrangling with Python 3, you'll learn about various functions and procedures that will help you get your data in order, providing a clean and well-constructed dataset for further data analysis and machine learning.

Machine Learning and Data analytics in general follows the garbage-in/garbage-out principle. If you want to learn from or predict based on your data, you need to make sure that data is well constructed and cleaned. This course, Data Wrangling with Python 3, is aimed at helping you do exactly that. First, you’ll see how to merge data from different sources using the methods concat, append, and merge. Next, you’ll discover how to combine data into groups. The primary function used here is groupby. In the next two sections, you’ll explore how to transform and normalize data. You’ll learn why these processes are necessary, and then proceed to see how they work in practice. Finally, you’ll examine important processes such as One Hot Encoding, which enables further processing during data analysis. When you’re finished with this course, you’ll have thorough knowledge of data wrangling which will help you immensely during your data analysis and machine learning projects.

What's inside

Syllabus

Course Overview

Concatenating and Merging Data from Different Sources

Combining Data into Groups

Normalizing Data with Pandas

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Guides students in cleaning and structuring data for further analysis, a crucial step in machine learning and data analytics

Taught by Pratheerth Padman, an experienced instructor who specializes in data wrangling and related topics

Reviews summary

Essential python data wrangling fundamentals

According to students, 'Data Wrangling with Python 3' provides a solid and practical foundation for preparing data for analysis and machine learning. Many learners found the explanations of core Pandas functions like concat, append, merge, and groupby to be exceptionally clear. The course is praised for its hands-on exercises and immediate applicability of concepts. While it excels as an introductory course, some students noted that pacing can be fast in certain sections and wished for more advanced real-world scenarios or deeper dives for those with prior experience. The section on One Hot Encoding was frequently highlighted as particularly well-explained.

It serves as an excellent starting point for new data wranglers.

"A solid introduction to data wrangling... Good for those with basic Python knowledge looking to level up."

"Excellent course! Perfectly structured... Highly recommend for aspiring data professionals."

"I found it to be a good starting point for data wrangling with Python, covering all the basics well."

The course offers practical skills that are immediately applicable.

"Highly recommend for practical Python skills."

"The practical application of normalization and reshaping was valuable. It gave me a good foundation for my ML projects."

"Practical and immediately applicable. I learned how to clean and prepare data efficiently for my projects."

Fundamental Pandas operations are explained with exceptional clarity.

"The explanations of `concat`, `append`, and `merge` were incredibly clear, and the hands-on exercises made sure I truly understood the concepts."

"Absolutely essential for data science... The `groupby` operations and various merging techniques are now second nature to me."

"I found the 'Combining Data into Groups' module particularly useful for my workflow."

Some learners find the course's pace occasionally too fast.

"Some parts felt a bit fast-paced, but rewatching was always an option."

"I felt that some explanations were a bit superficial, and there wasn't enough troubleshooting for common errors."

"I needed to rewatch certain sections to fully grasp the concepts before moving on."

The course may not meet the needs of intermediate or advanced learners.

"Decent course, but it's very much an introductory level. If you've done some data analysis with Pandas before, much of this will be review."

"Disappointed with the depth. While it introduces concepts, it doesn't go deep enough into practical scenarios or advanced techniques."

"I wished there was more on handling messy real-world data beyond the basics."

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 Data Wrangling with Python 3 with these activities:

Review SQL

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Ensure a renewed familiarity with fundamental SQL syntax and concepts to enhance comprehension of data wrangling techniques and operations.

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Revisit basic SQL commands
Practice writing SQL queries

Review Python basics

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Ensure you have a solid foundation in Python before starting the course.

Browse courses on Python

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Go over Python syntax and data types
Practice writing simple Python programs

Hands-on Data Wrangling Exercises

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Reinforce data wrangling skills through practical exercises, solidifying techniques covered in the course.

Browse courses on Data Manipulation

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Load and explore real-world datasets
Apply data wrangling techniques to clean and normalize data

Eight other activities

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Work through Pandas exercises

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Sharpen your data wrangling skills by working through these exercises.

Browse courses on Data Wrangling

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Review the data you'll be working with
Perform basic data cleaning and manipulation tasks

Follow tutorials on advanced data manipulation techniques

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Expand your knowledge of Python libraries and techniques for data wrangling.

Browse courses on Data Manipulation

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Identify areas where you need to improve your skills
Find tutorials that cover these topics
Follow the tutorials and practice the techniques

Solve LeetCode problems on data structures

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Strengthen your data structures and algorithm skills, which are essential for data wrangling.

Browse courses on Data Structures

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Review common data structures and algorithms
Attempt LeetCode problems of varying difficulty

Explore Advanced Data Wrangling Techniques

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Expand knowledge beyond the course by exploring additional data wrangling techniques and algorithms through guided tutorials.

Browse courses on Data Profiling

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Identify suitable tutorials
Follow tutorials and implement techniques

Connect with experts in the field

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Gain valuable insights and guidance from professionals with experience in data wrangling and analysis.

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Write a blog post on data cleaning best practices

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Share your knowledge and reinforce your understanding by creating a resource that benefits others.

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Research and gather information on data cleaning best practices
Organize your thoughts and outline the blog post
Write and edit the blog post

Data Cleaning Project

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Apply data wrangling skills to a real-world dataset, improving its quality and preparing it for analysis or modeling.

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Acquire a suitable dataset
Apply data cleaning techniques
Evaluate data quality before and after cleaning

Build a data visualization dashboard

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Showcase your data wrangling skills by creating an interactive dashboard that presents insights from your data.

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Gather and clean the data
Choose appropriate visualization techniques
Build the dashboard using a visualization library

Career center

Learners who complete Data Wrangling with Python 3 will develop knowledge and skills that may be useful to these careers:

Data Analyst

Data Analysts collect and interpret data to help organizations make informed decisions. They use their skills in data wrangling, analysis, and visualization to identify trends, patterns, and insights in data. The course Data Wrangling with Python 3 can help Data Analysts develop the skills they need to effectively clean, transform, and analyze data, enabling them to make more accurate and reliable conclusions.

See salaries and explore the career path for Data Analyst

Data Scientist

Data Scientists use their expertise in data wrangling, analysis, and machine learning to solve business problems and gain insights from data. The course Data Wrangling with Python 3 can help Data Scientists build a strong foundation in data wrangling techniques, enabling them to prepare and clean data effectively for further analysis and modeling.

See salaries and explore the career path for Data Scientist

Machine Learning Engineer

Machine Learning Engineers design, develop, and deploy machine learning models to solve real-world problems. The course Data Wrangling with Python 3 can help Machine Learning Engineers develop the skills they need to effectively prepare and clean data for machine learning, ensuring that their models are trained on high-quality data.

See salaries and explore the career path for Machine Learning Engineer

Data Engineer

Data Engineers design, develop, and maintain data pipelines and infrastructure to support data analysis and machine learning. The course Data Wrangling with Python 3 can help Data Engineers develop the skills they need to effectively clean, transform, and normalize data, ensuring that data is ready for analysis and modeling.

See salaries and explore the career path for Data Engineer

Business Analyst

Business Analysts use data to help organizations make better decisions. They use their skills in data analysis, visualization, and communication to identify opportunities, solve problems, and improve performance. The course Data Wrangling with Python 3 can help Business Analysts develop the skills they need to effectively clean, transform, and analyze data, enabling them to make more informed and data-driven recommendations.

See salaries and explore the career path for Business Analyst

Statistician

Statisticians collect, analyze, interpret, and present data to help organizations make informed decisions. They use their skills in data wrangling, analysis, and visualization to identify trends, patterns, and insights in data. The course Data Wrangling with Python 3 can help Statisticians develop the skills they need to effectively clean, transform, and analyze data, enabling them to make more accurate and reliable conclusions.

See salaries and explore the career path for Statistician

Data Visualization Analyst

Data Visualization Analysts use their skills in data wrangling, visualization, and communication to create visual representations of data that help stakeholders understand and make decisions. The course Data Wrangling with Python 3 can help Data Visualization Analysts develop the skills they need to effectively clean, transform, and prepare data for visualization, ensuring that their visualizations are accurate and informative.

See salaries and explore the career path for Data Visualization Analyst

Financial Analyst

Financial Analysts use their skills in data analysis and modeling to evaluate investments, make recommendations, and manage risk. The course Data Wrangling with Python 3 can help Financial Analysts develop the skills they need to effectively clean, transform, and analyze financial data, enabling them to make more informed and data-driven decisions.

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Market Researcher

Market Researchers use their skills in data collection, analysis, and interpretation to understand consumer behavior and market trends. The course Data Wrangling with Python 3 can help Market Researchers develop the skills they need to effectively clean, transform, and analyze market data, enabling them to make more informed and data-driven decisions.

See salaries and explore the career path for Market Researcher

Operations Research Analyst

Operations Research Analysts use their skills in data analysis, modeling, and optimization to improve the efficiency and effectiveness of business operations. The course Data Wrangling with Python 3 can help Operations Research Analysts develop the skills they need to effectively clean, transform, and analyze data, enabling them to make more informed and data-driven recommendations.

See salaries and explore the career path for Operations Research Analyst

Risk Analyst

Risk Analysts use their skills in data analysis and modeling to identify, assess, and mitigate risks. The course Data Wrangling with Python 3 can help Risk Analysts develop the skills they need to effectively clean, transform, and analyze risk data, enabling them to make more informed and data-driven decisions.

See salaries and explore the career path for Risk Analyst

Software Engineer

Software Engineers design, develop, and maintain software applications. While not directly related to data wrangling, the course Data Wrangling with Python 3 may be useful for Software Engineers who work with data-intensive applications or who need to develop data processing pipelines.

See salaries and explore the career path for Software Engineer

Web Developer

Web Developers design, develop, and maintain websites and web applications. While not directly related to data wrangling, the course Data Wrangling with Python 3 may be useful for Web Developers who work with data-driven websites or who need to develop data processing pipelines.

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Data Management Consultant

Data Management Consultants help organizations manage and use their data effectively. They use their skills in data wrangling, analysis, and governance to help organizations improve their data quality, data security, and data governance practices. The course Data Wrangling with Python 3 can help Data Management Consultants develop the skills they need to effectively clean, transform, and analyze data, enabling them to make more informed and data-driven recommendations.

See salaries and explore the career path for Data Management Consultant

Database Administrator

Database Administrators design, develop, and maintain databases. While not directly related to data wrangling, the course Data Wrangling with Python 3 may be useful for Database Administrators who need to develop data processing pipelines or who work with data-intensive databases.

See salaries and explore the career path for Database Administrator