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Ryan Ahmed
In this project, we will analyze life expectancy data by performing data wrangling & exploratory data analysis (EDA). Pandas is a powerful open source data analysis tools in python. Exploratory Data Analysis (EDA) is a process of analyzing data to gain valuable insights such as statistical summary & visualizations.
Register for this course and see more details by visiting:
OpenCourser.com/course/p10yjt/practical
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What's inside
Syllabus
Project Overview
Hello everyone and welcome to this new hands-on project on Data Wrangling and exploratory data analysis with Pandas. Exploratory Data Analysis (EDA) is a process of analyzing data to gain valuable insights such as statistical summary and visualizations. Pandas is a powerful open-source data analysis tool in python. This project is practical and directly applicable to many industries. You can add this project to your portfolio of projects which is essential for your next job interview.
Good to know
Good to know
Know what's good ,
what to watch for , and
possible dealbreakers
Introduces Exploratory Data Analysis (EDA), an essential skill for data analysis
Utilizes Pandas, a popular and powerful data analysis library in Python, for hands-on practice
Provides a practical and applicable project that can be added to a portfolio for job interviews
Taught by an instructor, Ryan Ahmed, who is not explicitly recognized for their work in this domain
Involves analyzing real-life data, making the learning process more relevant and engaging
Save this course
Save Practical Data Wrangling with Pandas 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 Practical Data Wrangling with Pandas with these
activities:
Gather course materials
Show steps
Preparing and collecting all necessary materials before you begin the course will help you feel organized and ready to take on this learning experience.
Browse courses on
Materials
Show steps
-
Gather supplies such as paper, pens, and highlighters
-
Get copies of the textbooks and online materials
-
Make copies of any supplemental materials
Review DataFrame and Series
Show steps
This course covers Pandas library, making sure you are comfortable with at least the foundational aspects of working with DataFrames and Series can help ensure your success.
Browse courses on
Pandas
Show steps
-
Review the documentation for these topics
-
Complete a few practice exercises
-
Create a small data analysis project
Explore tutorials on Exploratory Data Analysis
Show steps
Before you begin this course, you will be able to perform basic tasks in data analysis.
Browse courses on
Exploratory Data Analysis
Show steps
-
Find a few tutorials on Exploratory Data Analysis
-
Follow the steps in the tutorials
-
Try to apply what you learn to your own data
Four other activities
Expand to see all activities and additional details
Show all seven activities
Read a book on data analysis
Show steps
This will allow you to learn from the experts and gain a deeper understanding of the concepts covered in the course.
View
Python for Data Analysis: Data Wrangling with...
on Amazon
Show steps
-
Purchase or borrow a copy of the book
-
Read the book
-
Take notes and highlight important passages
-
Complete the exercises at the end of each chapter
Use Pandas to analyze your own data
Show steps
This will allow you to apply the concepts you learn in the course to a real-world dataset and will help you to improve your skills in data analysis.
Browse courses on
Pandas
Show steps
-
Find a dataset that you are interested in
-
Load the dataset into a Pandas DataFrame
-
Use Pandas to explore the data
-
Create visualizations to summarize your findings
Create a data visualization project
Show steps
This will give you an opportunity to apply your skills in data analysis and visualization to a real-world problem.
Browse courses on
Data Visualization
Show steps
-
Choose a dataset that you are interested in
-
Load the dataset into a Pandas DataFrame
-
Explore the data and identify trends
-
Create visualizations to communicate your findings
-
Write a report to summarize your project
Write a blog post about your experience
Show steps
This is an opportunity to reflect on the content of the course, reinforce your learning, and share your knowledge with others.
Show steps
-
Choose a topic that you want to write about
-
Do some research on the topic
-
Write a draft of your blog post
-
Edit and revise your blog post
-
Publish your blog post
Gather course materials
Show steps
Preparing and collecting all necessary materials before you begin the course will help you feel organized and ready to take on this learning experience.
Browse courses on
Materials
Show steps
Show steps
Show steps
- Gather supplies such as paper, pens, and highlighters
- Get copies of the textbooks and online materials
- Make copies of any supplemental materials
Review DataFrame and Series
Show steps
This course covers Pandas library, making sure you are comfortable with at least the foundational aspects of working with DataFrames and Series can help ensure your success.
Browse courses on
Pandas
Show steps
Show steps
Show steps
- Review the documentation for these topics
- Complete a few practice exercises
- Create a small data analysis project
Explore tutorials on Exploratory Data Analysis
Show steps
Before you begin this course, you will be able to perform basic tasks in data analysis.
Browse courses on
Exploratory Data Analysis
Show steps
Show steps
Show steps
- Find a few tutorials on Exploratory Data Analysis
- Follow the steps in the tutorials
- Try to apply what you learn to your own data
Four other activities
Expand to see all activities and additional details
Show all seven activities
Read a book on data analysis
Show steps
This will allow you to learn from the experts and gain a deeper understanding of the concepts covered in the course.
View
Python for Data Analysis: Data Wrangling with...
on Amazon
Show steps
Show steps
Show steps
- Purchase or borrow a copy of the book
- Read the book
- Take notes and highlight important passages
- Complete the exercises at the end of each chapter
Use Pandas to analyze your own data
Show steps
This will allow you to apply the concepts you learn in the course to a real-world dataset and will help you to improve your skills in data analysis.
Browse courses on
Pandas
Show steps
Show steps
Show steps
- Find a dataset that you are interested in
- Load the dataset into a Pandas DataFrame
- Use Pandas to explore the data
- Create visualizations to summarize your findings
Create a data visualization project
Show steps
This will give you an opportunity to apply your skills in data analysis and visualization to a real-world problem.
Browse courses on
Data Visualization
Show steps
Show steps
Show steps
- Choose a dataset that you are interested in
- Load the dataset into a Pandas DataFrame
- Explore the data and identify trends
- Create visualizations to communicate your findings
- Write a report to summarize your project
Write a blog post about your experience
Show steps
This is an opportunity to reflect on the content of the course, reinforce your learning, and share your knowledge with others.
Show steps
Show steps
Show steps
- Choose a topic that you want to write about
- Do some research on the topic
- Write a draft of your blog post
- Edit and revise your blog post
- Publish your blog post
Career center
Learners who complete Practical Data Wrangling with Pandas will develop knowledge and skills
that may be useful to these careers:
Data Analyst
Data Analyst
Data analysts have a deep understanding of how to explore data to gain valuable insights. They are crucial to any organization that wants to use its data to its full potential. By learning about data wrangling and exploratory data analysis with Pandas, you'll develop the skills you need to be a successful data analyst. This course will also help you master foundational data analysis tools and techniques that are essential for success in this role.
Data Scientist
Data Scientist
Data scientists are the leaders in the field of data analysis. They use their expertise in data wrangling and exploratory data analysis to develop new data insights and solutions. By taking this course, you'll learn about the powerful open-source data analysis tool Pandas, which will help you succeed as a data scientist. This course will also teach you foundational data analysis techniques that are essential for this role.
Data Visualization Analyst
Data Visualization Analyst
Data visualization analysts create visual representations of data to help people understand complex data. By learning about data wrangling and exploratory data analysis with Pandas, you'll develop the skills you need to be a successful data visualization analyst. This course will also help you master foundational data analysis tools and techniques that are essential for success in this role.
Business Analyst
Business Analyst
Business analysts work with data to help organizations make better decisions. By learning about data wrangling and exploratory data analysis with Pandas, you'll develop the skills you need to be a successful business analyst. This course will also help you master foundational data analysis tools and techniques that are essential for success in this role.
Financial Analyst
Financial Analyst
Financial analysts use data to make investment decisions. By learning about data wrangling and exploratory data analysis with Pandas, you'll develop the skills you need to be a successful financial analyst. This course will also help you master foundational data analysis tools and techniques that are essential for success in this role.
Quantitative Analyst
Quantitative Analyst
Quantitative analysts use data to make investment decisions. By learning about data wrangling and exploratory data analysis with Pandas, you'll develop the skills you need to be a successful quantitative analyst. This course will also help you master foundational data analysis tools and techniques that are essential for success in this role.
Statistician
Statistician
Statisticians collect, analyze, and interpret data to gain insights. By learning about data wrangling and exploratory data analysis with Pandas, you'll develop the skills you need to be a successful statistician. This course will also help you master foundational data analysis tools and techniques that are essential for success in this role.
Machine Learning Engineer
Machine Learning Engineer
Machine learning engineers use data to train machine learning models that can solve business problems. By learning about data wrangling and exploratory data analysis with Pandas, you'll develop the skills you need to be a successful machine learning engineer. This course will also help you master foundational data analysis tools and techniques that are essential for success in this role.
Fraud Analyst
Fraud Analyst
Fraud analysts use data to detect and prevent fraud. By learning about data wrangling and exploratory data analysis with Pandas, you'll gain an understanding of data analysis techniques that are essential for success in this role. This course will also teach you foundational data analysis tools and techniques that are useful for fraud analysts.
Operations Research Analyst
Operations Research Analyst
Operations research analysts use data to improve organizational efficiency. By learning about data wrangling and exploratory data analysis with Pandas, you'll gain an understanding of data analysis techniques that are essential for success in this role. This course will also teach you foundational data analysis tools and techniques that are useful for operations research analysts.
Risk Analyst
Risk Analyst
Risk analysts use data to assess and manage risk. By learning about data wrangling and exploratory data analysis with Pandas, you'll gain an understanding of data analysis techniques that are essential for success in this role. This course will also teach you foundational data analysis tools and techniques that are useful for risk analysts.
Data Engineer
Data Engineer
Data engineers build and maintain data pipelines that store and process data. By learning about data wrangling and exploratory data analysis with Pandas, you'll gain an understanding of how data is stored and processed, which will be essential for success in this role. This course will also teach you foundational data analysis techniques that are useful for data engineers.
Actuary
Actuary
Actuaries use data to assess risk and make financial decisions. By learning about data wrangling and exploratory data analysis with Pandas, you'll gain an understanding of data analysis techniques that are essential for success in this role. This course will also teach you foundational data analysis tools and techniques that are useful for actuaries.
Economist
Economist
Economists use data to study economic trends and make policy recommendations. By learning about data wrangling and exploratory data analysis with Pandas, you'll gain an understanding of data analysis techniques that are essential for success in this role. This course will also teach you foundational data analysis tools and techniques that are useful for economists.
Market Research Analyst
Market Research Analyst
Market research analysts use data to understand consumer behavior and trends. By learning about data wrangling and exploratory data analysis with Pandas, you'll gain an understanding of data analysis techniques that are essential for success in this role. This course will also teach you foundational data analysis tools and techniques that are useful for market research analysts.
For more career information including salaries, visit:
OpenCourser.com/course/p10yjt/practical
Reading list
We've selected eight 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
Practical Data Wrangling with Pandas.
Provides a comprehensive overview of data science. It covers data wrangling, Exploratory Data Analysis (EDA), machine learning, and more. This book can be a valuable resource for those who want to learn about the entire data science process, from data collection to modeling and deployment.
Comprehensive guide to deep learning using Python. It covers convolutional neural networks, recurrent neural networks, and more. This book can be a valuable resource for those who want to learn about deep learning and how to apply it to practical problems.
Practical guide to machine learning using Python. It covers supervised learning algorithms, such as linear regression, logistic regression, and decision trees, unsupervised learning algorithms, such as principal component analysis and k-means clustering, and more. This book can be a valuable resource for those who want to apply machine learning techniques in their data analysis projects.
Provides a comprehensive overview of Exploratory Data Analysis (EDA) using Pandas. It covers data exploration, visualization, and statistical analysis. This book can be a great resource for learning about EDA and how to use Pandas for this purpose.
Comprehensive guide to using Python for data analysis. It covers data wrangling, manipulation, and visualization using Pandas, NumPy, and Matplotlib. This book can provide a solid foundation for data analysis in Python, which is beneficial for this course.
Save
Practical guide to using Pandas for data analysis. It provides real-world examples and case studies to demonstrate how Pandas can be used to solve data analysis problems. This book can be a valuable resource for those who want to learn how to apply Pandas in practice.
Save
Provides a concise overview of Pandas for data analysis. It covers the essential features and functionality of Pandas. This book can be a good starting point for those who are new to Pandas.
Save
Beginner-friendly guide to Pandas. It provides clear explanations and examples for data analysis tasks. This book can be a helpful resource for those who are new to Pandas or data analysis.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/p10yjt/practical
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Effort
2 hours
Level
Introductory
Via
Coursera
Institution
Coursera Project Network
Instructor
Ryan Ahmed
Language
English
Good to know
Introduces Exploratory Data Analysis (EDA), an essential skill for data analysis
Utilizes Pandas, a popular and powerful data analysis library in Python, for hands-on practice
Provides a practical and applicable project that can be added to a portfolio for job interviews
Taught by an instructor, Ryan Ahmed, who is not explicitly recognized for their work in this domain
Involves analyzing real-life data, making the learning process more relevant and engaging
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