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Raphael Alampay
This course will teach you the fundamentals of the Pandas library in terms of data representation, processing and filtering to programmatically start working with complex datasets with ease and extreme convenience.
Pandas is a powerful library for data processing. In this course, Up and Running with Pandas, you’ll learn how to take advantage of the Pandas library to integrate data processing in your Python application.
Read more
This course will teach you the fundamentals of the Pandas library in terms of data representation, processing and filtering to programmatically start working with complex datasets with ease and extreme convenience.
Pandas is a powerful library for data processing. In this course, Up and Running with Pandas, you’ll learn how to take advantage of the Pandas library to integrate data processing in your Python application.
Read more
This course will teach you the fundamentals of the Pandas library in terms of data representation, processing and filtering to programmatically start working with complex datasets with ease and extreme convenience.
Pandas is a powerful library for data processing. In this course, Up and Running with Pandas, you’ll learn how to take advantage of the Pandas library to integrate data processing in your Python application.
First, you’ll explore how to fetch data from a medium and programmatically represent it as a data frame object as well as create your own data frame from scratch using standard tools for portability and simplicity, specifically, running it in a Jupyter notebook. Next, you’ll discover the different properties of a data frame to know your way around its various sections, observing all sorts of information from it.
Finally, you’ll learn how to do all sorts of operations against a data frame that are commonly used in most data processing scenarios such as getting statistical properties, performing arithmetic against the entire dataset and basic filtering.
When you’re finished with this course, you’ll have the skills and knowledge of the 'FREE' aspect of Pandas: fundamentals, representation, exploration, and evaluation.
Register for this course and see more details by visiting:
OpenCourser.com/course/buzd7s/up
What's inside
Syllabus
Course Overview
Introduction
Understanding Data Fundamentals with Pandas
Programmatically Representing Data with Pandas
Read more
Syllabus
Course Overview
Introduction
Understanding Data Fundamentals with Pandas
Programmatically Representing Data with Pandas
Read more
Exploring and Evaluating Data with Pandas
Good to know
Good to know
Know what's good ,
what to watch for , and
possible dealbreakers
Examines core libraries in Python that enhance data wrangling
Provides hands-on experience to understand the versatility of Pandas library in representing, manipulating and visualizing data
Builds a strong foundation in core Pandas concepts and functionalities, which can be leveraged for various data-centric tasks
Learn from experienced instructors with professional expertise in the field of data science and Python programming
Requires basic proficiency in Python programming, which may pose a barrier for beginners
Assumes familiarity with data analysis concepts and practices, which may require additional learning for those new to the field
Save this course
Save Up and Running 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 Up and Running with Pandas with these
activities:
Review previous Python programming basics
Show steps
Ensure a strong foundation in Python before starting the course, which can facilitate understanding of Pandas.
Browse courses on
Python
Show steps
-
Revisit your lecture notes or online resources on Python basics.
-
Solve a few basic Python programming exercises.
Review 'Data Manipulation with Pandas: A Guide for Beginners' by Wes McKinney
Show steps
Gain practical knowledge of Pandas for data manipulation before starting the course.
View
Python for Data Analysis: Data Wrangling with...
on Amazon
Show steps
-
Read chapters 1-3 of the book to understand the basics of Pandas.
-
Go through the examples in the book to practice using Pandas functions.
Join a Pandas study group
Show steps
Connect with other students to discuss course material, ask questions, and reinforce your understanding.
Browse courses on
Pandas
Show steps
-
Look for online forums or Discord servers dedicated to Pandas.
-
Join a study group and actively participate in discussions.
Five other activities
Expand to see all activities and additional details
Show all eight activities
Complete the 'Pandas Data Analysis for Beginners' tutorial on DataCamp
Show steps
Enhance your understanding of Pandas operations and techniques through interactive exercises.
Browse courses on
Pandas
Show steps
-
Sign up for a DataCamp account.
-
Enroll in the 'Pandas Data Analysis for Beginners' tutorial.
-
Complete all the exercises and quizzes in the tutorial.
Solve 50 Pandas problems on LeetCode
Show steps
Solidify your Pandas skills by solving a variety of coding challenges.
Browse courses on
Pandas
Show steps
-
Create a LeetCode account.
-
Search for 'Pandas' problems.
-
Solve at least 50 problems.
Create a data visualization using Pandas and Plotly
Show steps
Apply your Pandas skills to create a visually appealing representation of data, improving your understanding of Pandas and data visualization techniques.
Browse courses on
Pandas
Show steps
-
Choose a dataset and import it into a Pandas DataFrame.
-
Clean and manipulate the data using Pandas functions.
-
Create a visualization using Plotly.
Answer questions on online forums related to Pandas
Show steps
Reinforce your understanding by helping others and solidifying your knowledge about Pandas.
Browse courses on
Pandas
Show steps
-
Identify online forums where people ask questions about Pandas.
-
Actively answer questions and provide helpful explanations.
Start a personal project using Pandas to analyze real-world data
Show steps
Apply your Pandas skills to a practical project, allowing you to explore real-world applications and deepen your understanding.
Browse courses on
Pandas
Show steps
-
Identify a dataset that interests you.
-
Import the dataset into a Pandas DataFrame.
-
Analyze the data using Pandas functions and techniques.
-
Create visualizations to present your findings.
Review previous Python programming basics
Show steps
Ensure a strong foundation in Python before starting the course, which can facilitate understanding of Pandas.
Browse courses on
Python
Show steps
Show steps
Show steps
- Revisit your lecture notes or online resources on Python basics.
- Solve a few basic Python programming exercises.
Review 'Data Manipulation with Pandas: A Guide for Beginners' by Wes McKinney
Show steps
Gain practical knowledge of Pandas for data manipulation before starting the course.
View
Python for Data Analysis: Data Wrangling with...
on Amazon
Show steps
Show steps
Show steps
- Read chapters 1-3 of the book to understand the basics of Pandas.
- Go through the examples in the book to practice using Pandas functions.
Join a Pandas study group
Show steps
Connect with other students to discuss course material, ask questions, and reinforce your understanding.
Browse courses on
Pandas
Show steps
Show steps
Show steps
- Look for online forums or Discord servers dedicated to Pandas.
- Join a study group and actively participate in discussions.
Five other activities
Expand to see all activities and additional details
Show all eight activities
Complete the 'Pandas Data Analysis for Beginners' tutorial on DataCamp
Show steps
Enhance your understanding of Pandas operations and techniques through interactive exercises.
Browse courses on
Pandas
Show steps
Show steps
Show steps
- Sign up for a DataCamp account.
- Enroll in the 'Pandas Data Analysis for Beginners' tutorial.
- Complete all the exercises and quizzes in the tutorial.
Solve 50 Pandas problems on LeetCode
Show steps
Solidify your Pandas skills by solving a variety of coding challenges.
Browse courses on
Pandas
Show steps
Show steps
Show steps
- Create a LeetCode account.
- Search for 'Pandas' problems.
- Solve at least 50 problems.
Create a data visualization using Pandas and Plotly
Show steps
Apply your Pandas skills to create a visually appealing representation of data, improving your understanding of Pandas and data visualization techniques.
Browse courses on
Pandas
Show steps
Show steps
Show steps
- Choose a dataset and import it into a Pandas DataFrame.
- Clean and manipulate the data using Pandas functions.
- Create a visualization using Plotly.
Answer questions on online forums related to Pandas
Show steps
Reinforce your understanding by helping others and solidifying your knowledge about Pandas.
Browse courses on
Pandas
Show steps
Show steps
Show steps
- Identify online forums where people ask questions about Pandas.
- Actively answer questions and provide helpful explanations.
Start a personal project using Pandas to analyze real-world data
Show steps
Apply your Pandas skills to a practical project, allowing you to explore real-world applications and deepen your understanding.
Browse courses on
Pandas
Show steps
Show steps
Show steps
- Identify a dataset that interests you.
- Import the dataset into a Pandas DataFrame.
- Analyze the data using Pandas functions and techniques.
- Create visualizations to present your findings.
Career center
Learners who complete Up and Running with Pandas will develop knowledge and skills
that may be useful to these careers:
Machine Learning Researcher
Machine Learning Researcher
Machine Learning Researchers use big data technologies like Pandas to develop new machine learning algorithms and models. This course, Up and Running with Pandas, will help you get started with Pandas and show you how to use it to work with complex datasets.
Data Visualization Specialist
Data Visualization Specialist
Data Visualization Specialists use big data technologies like Pandas to create visualizations that communicate data insights. This course, Up and Running with Pandas, will help you get started with Pandas and show you how to use it to work with complex datasets.
Data Miner
Data Miner
Data Miners use big data technologies like Pandas to extract knowledge and insights from data. This course, Up and Running with Pandas, will help you get started with Pandas and show you how to use it to work with complex datasets.
Database Administrator
Database Administrator
Database Administrators design, implement, and maintain databases. Pandas is a popular big data library in Python. This course, Up and Running with Pandas, will help you get started with Pandas and show you how to use it to work with complex datasets.
Research Analyst
Research Analyst
Research Analysts use data to make recommendations and inform decisions. Pandas is a popular big data library in Python. This course, Up and Running with Pandas, will help you get started with Pandas and show you how to use it to work with complex datasets.
Software Engineer
Software Engineer
Software Engineers design, develop, and maintain software systems. Pandas is a popular big data library in Python. This course, Up and Running with Pandas, will help you get started with Pandas and show you how to use it to work with complex datasets.
Quantitative Analyst
Quantitative Analyst
Quantitative Analysts use mathematical and statistical models to analyze data and make investment decisions. This course, Up and Running with Pandas, will help you get started on your journey to becoming a Quantitative Analyst, by teaching you how to programmatically fetch, represent, explore, and evaluate data.
Data Engineer
Data Engineer
Data Engineers build and maintain the infrastructure that allows data scientists to work with big data. This course, Up and Running with Pandas, will help you get started on your journey to becoming a Data Engineer by teaching you how to programmatically fetch, represent, explore, and evaluate data.
Financial Analyst
Financial Analyst
Financial Analysts use data to make investment decisions. Using big data technologies like Pandas, they provide insights to companies. This course, Up and Running with Pandas, may help you get started on your journey to becoming a Financial Analyst by helping you to build a foundation for working with complex datasets.
Machine Learning Engineer
Machine Learning Engineer
Machine Learning Engineers use Machine Learning and big data technologies like Pandas to create and maintain artificial intelligence programs. This course, Up and Running with Pandas, may help you get started on your journey to becoming a Machine Learning Engineer by helping you to build a foundation for working with complex datasets.
Business Analyst
Business Analyst
Business Analysts use data to solve business problems. Using big data technologies like Pandas, they provide insights to companies. This course, Up and Running with Pandas, may help you get started on your journey to becoming a Business Analyst by helping you to build a foundation for working with complex datasets.
Statistician
Statistician
Statisticians collect, analyze, interpret, and present data. Using big data technologies like Pandas, they provide insights to companies. This course, Up and Running with Pandas, may help you get started on your journey to becoming a Statistician by helping you to build a foundation for working with complex datasets.
Data Analyst
Data Analyst
Data Analysts collect, analyze, interpret, and present data. Using big data technologies like Pandas, Data Analysts provide insights to companies. This course, Up and Running with Pandas, may help you get started on your journey to becoming a Data Analyst by helping you to build a foundation for working with complex datasets.
Data Scientist
Data Scientist
Data Scientists use scientific methods, processes, algorithms, and systems to extract knowledge and insights from structured and unstructured data. This course, Up and Running with Pandas, may help you get started on your journey to becoming a Data Scientist by helping you to build a foundation for working with complex datasets.
Actuary
Actuary
Actuaries use data to assess risk and uncertainty. Using big data technologies like Pandas, they provide insights to companies. This course, Up and Running with Pandas, may help you get started on your journey to becoming an Actuary by helping you to build a foundation for working with complex datasets.
For more career information including salaries, visit:
OpenCourser.com/course/buzd7s/up
Reading list
We've selected 13 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
Up and Running with Pandas.
Provides a comprehensive overview of the Python programming language, with a focus on data analysis and manipulation. It covers the basics of Python, including data structures, control flow, and functions, and then delves into more advanced topics such as data cleaning, data visualization, and machine learning.
Save
Provides a comprehensive overview of data cleaning using Python. It covers the basics of data cleaning, including data validation, data transformation, and data integration.
Provides a gentle introduction to data analysis using Pandas. It covers the basics of Pandas, includingデータフレームs, series, and indexing, and then delves into more advanced topics such as data cleaning, data manipulation, and data visualization.
Save
Offers an in-depth look into advanced Pandas techniques and best practices.
Offers a practical approach to learning Pandas for data cleaning and manipulation.
Provides a comprehensive overview of data science using Python. It covers the basics of Python, including data structures, control flow, and functions, and then delves into more advanced topics such as data cleaning, data manipulation, data visualization, and machine learning.
Save
Provides a comprehensive overview of data science using Python. It covers the basics of Python, including data structures, control flow, and functions, and then delves into more advanced topics such as data cleaning, data manipulation, data visualization, and machine learning.
Provides a comprehensive overview of machine learning using Python. It covers the basics of machine learning, including machine learning algorithms, machine learning models, and machine learning evaluation.
Provides a comprehensive overview of data science from scratch. It covers the basics of data science, including data collection, data cleaning, data analysis, and data visualization.
Provides a comprehensive overview of machine learning using Python. It covers the basics of machine learning, including machine learning algorithms, machine learning models, and machine learning evaluation.
Provides a broader perspective on data science, offering additional context and applications for the topics covered in the course.
Provides a comprehensive overview of natural language processing using Python. It covers the basics of natural language processing, including natural language processing algorithms, natural language processing models, and natural language processing evaluation.
Provides a comprehensive overview of deep learning using Python. It covers the basics of deep learning, including deep learning algorithms, deep learning models, and deep learning evaluation.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/buzd7s/up
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Time
74 hours
Level
Introductory
Via
Pluralsight
Instructor
Raphael Alampay
Language
English
Good to know
Examines core libraries in Python that enhance data wrangling
Provides hands-on experience to understand the versatility of Pandas library in representing, manipulating and visualizing data
Builds a strong foundation in core Pandas concepts and functionalities, which can be leveraged for various data-centric tasks
Learn from experienced instructors with professional expertise in the field of data science and Python programming
Requires basic proficiency in Python programming, which may pose a barrier for beginners
Assumes familiarity with data analysis concepts and practices, which may require additional learning for those new to the field
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