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Biswanath Halder

In this course, you’ll learn how to use Pandas index objects for advanced data analysis. You'll learn how to create and use numerical, interval, period, categorical, date-time, time-delta, and multi-indexing in Pandas to retrieve and manipulate data.

To build any business solution using data, the first step that you need to perform is data analysis. Pandas is a Python library that has numerous functionalities to simplify data analysis. Pandas Index objects offer some of these advanced functionalities to make data analysis easier.

Read more

In this course, you’ll learn how to use Pandas index objects for advanced data analysis. You'll learn how to create and use numerical, interval, period, categorical, date-time, time-delta, and multi-indexing in Pandas to retrieve and manipulate data.

To build any business solution using data, the first step that you need to perform is data analysis. Pandas is a Python library that has numerous functionalities to simplify data analysis. Pandas Index objects offer some of these advanced functionalities to make data analysis easier.

In this course, Index Objects with Pandas, you’ll learn how to use Pandas index objects for advanced data analysis. First, you'll learn the basics of data-frames and various indexing strategies in Pandas. Next, you'll discover how to create and use numerical, interval, period, and categorical indexing in Pandas to retrieve data from a data-frame. Then, you'll see how to use date-time and time-delta indexing to extract and manipulate time-series data. Finally, you'll dive into how to use multi-indexing in Pandas to organize data hierarchically.

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What's inside

Syllabus

Course Overview
Introduction to Indexing Objects in Pandas
Pandas Index Objects for Time Series Data
Interval, Categorical, and Period Indexing in Pandas
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Multi-indexing in Pandas

Good to know

Know what's good
, what to watch for
, and possible dealbreakers
Explores advanced functionalities of Pandas Index objects for data analysis, which is standard in data science
Taught by Biswanath Halder, who is an recognized instructor in data science
Suitable for learners with background knowledge in Pandas and data analysis
Covers essential concepts and techniques for advanced data analysis with Pandas Index objects
Provides a strong foundation for learners looking to enhance their data analysis skills

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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 Index Objects with Pandas with these activities:
Watch tutorials on Pandas indexing
Watching tutorials will provide you with a visual and interactive way to learn about Pandas indexing.
Browse courses on Data Manipulation
Show steps
  • Search for tutorials on Pandas indexing on YouTube or Coursera.
  • Watch at least three tutorials.
  • Take notes on the key concepts and techniques.
Read 'Python Data Analysis Handbook' by Wes McKinney
This book provides a comprehensive overview of data analysis using Python, covering topics such as data manipulation, visualization, and machine learning.
Show steps
  • Read the book's introduction and first three chapters.
  • Complete the exercises in Chapters 4-6.
  • Create a data analysis project using the techniques you learned.
Join a study group for Pandas
Joining a study group will allow you to collaborate with other learners and reinforce your understanding.
Browse courses on Pandas
Show steps
  • Search for a study group on platforms like Meetup or Discord.
  • Join the group and attend regular meetings.
  • Participate in discussions and ask questions.
Four other activities
Expand to see all activities and additional details
Show all seven activities
Solve Pandas exercises on LeetCode
Solving coding exercises on LeetCode will help you improve your proficiency in using Pandas for data manipulation.
Browse courses on Pandas
Show steps
  • Register for a LeetCode account.
  • Search for Pandas exercises.
  • Solve at least 10 exercises.
Build a data visualization using Pandas
Building a data visualization will allow you to apply your Pandas skills to a practical problem.
Browse courses on Pandas
Show steps
  • Choose a dataset to work with.
  • Load the dataset into a Pandas DataFrame.
  • Clean and prepare the data.
  • Create a visualization using a library like Matplotlib or Seaborn.
  • Interpret the results and draw conclusions.
Write a blog post about Pandas indexing
Writing a blog post will help you solidify your understanding of Pandas indexing and share your knowledge with others.
Browse courses on Data Manipulation
Show steps
  • Choose a specific aspect of Pandas indexing to focus on.
  • Research the topic and gather relevant information.
  • Write a draft of your blog post.
  • Proofread and edit your post.
  • Publish your post on a blogging platform.
Answer questions on a Pandas forum
Mentoring others will reinforce your knowledge and help you develop your communication skills.
Browse courses on Pandas
Show steps
  • Join a Pandas forum, such as the Pandas Discussion Forum.
  • Monitor the forum for questions.
  • Provide helpful and detailed responses to questions.

Career center

Learners who complete Index Objects with Pandas will develop knowledge and skills that may be useful to these careers:
Data Analyst
Data Analysts use their knowledge of data analysis tools and techniques to transform raw data into insights for businesses. This course, Index Objects with Pandas, can help you develop the skills needed to succeed as a Data Analyst. You'll learn how to use Pandas index objects to retrieve and manipulate data from dataframes, which is essential for data analysis. Additionally, you'll learn how to use date-time and time-delta indexing to extract and manipulate time-series data, which is a common task for Data Analysts.
Data Engineer
Data Engineers design, build, and maintain the infrastructure that stores and processes data for businesses. This course, Index Objects with Pandas, can help you develop the skills needed to succeed as a Data Engineer. You'll learn how to use Pandas index objects to efficiently retrieve and manipulate data from dataframes, which is a common task for Data Engineers. Additionally, you'll learn how to use date-time and time-delta indexing to extract and manipulate time-series data, which is often stored in data warehouses.
Business Analyst
Business Analysts use data analysis to help businesses make better decisions. This course, Index Objects with Pandas, can help you develop the skills needed to succeed as a Business Analyst. You'll learn how to use Pandas index objects to retrieve and manipulate data from dataframes, which is essential for data analysis. Additionally, you'll learn how to use date-time and time-delta indexing to extract and manipulate time-series data, which is often used to track business performance.
Data Scientist
Data Scientists use data analysis to build predictive models and solve business problems. This course, Index Objects with Pandas, can help you develop the skills needed to succeed as a Data Scientist. You'll learn how to use Pandas index objects to retrieve and manipulate data from dataframes, which is essential for data analysis. Additionally, you'll learn how to use date-time and time-delta indexing to extract and manipulate time-series data, which is often used to build predictive models.
Statistician
Statisticians use data analysis to draw conclusions about the world around us. This course, Index Objects with Pandas, can help you develop the skills needed to succeed as a Statistician. You'll learn how to use Pandas index objects to retrieve and manipulate data from dataframes, which is essential for data analysis. Additionally, you'll learn how to use date-time and time-delta indexing to extract and manipulate time-series data, which is often used to study trends and patterns.
Financial Analyst
Financial Analysts use data analysis to help businesses make investment decisions. This course, Index Objects with Pandas, can help you develop the skills needed to succeed as a Financial Analyst. You'll learn how to use Pandas index objects to retrieve and manipulate data from dataframes, which is essential for data analysis. Additionally, you'll learn how to use date-time and time-delta indexing to extract and manipulate time-series data, which is often used to track financial performance.
Market Research Analyst
Market Research Analysts use data analysis to help businesses understand their customers and make marketing decisions. This course, Index Objects with Pandas, can help you develop the skills needed to succeed as a Market Research Analyst. You'll learn how to use Pandas index objects to retrieve and manipulate data from dataframes, which is essential for data analysis. Additionally, you'll learn how to use date-time and time-delta indexing to extract and manipulate time-series data, which is often used to track marketing campaigns.
Operations Research Analyst
Operations Research Analysts use data analysis to help businesses improve their operations. This course, Index Objects with Pandas, can help you develop the skills needed to succeed as an Operations Research Analyst. You'll learn how to use Pandas index objects to retrieve and manipulate data from dataframes, which is essential for data analysis. Additionally, you'll learn how to use date-time and time-delta indexing to extract and manipulate time-series data, which is often used to track operational performance.
Software Engineer
Software Engineers design, build, and maintain software applications. This course, Index Objects with Pandas, may be useful for Software Engineers who want to develop data analysis applications. You'll learn how to use Pandas index objects to retrieve and manipulate data from dataframes, which is essential for data analysis. Additionally, you'll learn how to use date-time and time-delta indexing to extract and manipulate time-series data, which is often used in data analysis applications.
Web Developer
Web Developers design and build websites. This course, Index Objects with Pandas, may be useful for Web Developers who want to develop data-driven websites. You'll learn how to use Pandas index objects to retrieve and manipulate data from dataframes, which is essential for data analysis. Additionally, you'll learn how to use date-time and time-delta indexing to extract and manipulate time-series data, which is often used to track website traffic.
Data Visualization Analyst
Data Visualization Analysts use data analysis to create visualizations that communicate insights to stakeholders. This course, Index Objects with Pandas, may be useful for Data Visualization Analysts who want to develop more effective visualizations. You'll learn how to use Pandas index objects to retrieve and manipulate data from dataframes, which is essential for data analysis. Additionally, you'll learn how to use date-time and time-delta indexing to extract and manipulate time-series data, which is often used to create time-series visualizations.
Database Administrator
Database Administrators design, build, and maintain databases. This course, Index Objects with Pandas, may be useful for Database Administrators who want to develop data analysis applications. You'll learn how to use Pandas index objects to retrieve and manipulate data from dataframes, which is essential for data analysis. Additionally, you'll learn how to use date-time and time-delta indexing to extract and manipulate time-series data, which is often stored in databases.
Actuary
Actuaries use data analysis to assess risk and uncertainty. This course, Index Objects with Pandas, may be useful for Actuaries who want to develop more sophisticated risk models. You'll learn how to use Pandas index objects to retrieve and manipulate data from dataframes, which is essential for data analysis. Additionally, you'll learn how to use date-time and time-delta indexing to extract and manipulate time-series data, which is often used to model risk over time.
Epidemiologist
Epidemiologists use data analysis to investigate the causes and distribution of disease. This course, Index Objects with Pandas, may be useful for Epidemiologists who want to develop more effective disease surveillance systems. You'll learn how to use Pandas index objects to retrieve and manipulate data from dataframes, which is essential for data analysis. Additionally, you'll learn how to use date-time and time-delta indexing to extract and manipulate time-series data, which is often used to track the spread of disease.
Health Data Analyst
Health Data Analysts use data analysis to improve the quality and efficiency of healthcare delivery. This course, Index Objects with Pandas, may be useful for Health Data Analysts who want to develop more effective healthcare data analysis applications. You'll learn how to use Pandas index objects to retrieve and manipulate data from dataframes, which is essential for data analysis. Additionally, you'll learn how to use date-time and time-delta indexing to extract and manipulate time-series data, which is often used to track patient outcomes over time.

Reading list

We've selected 14 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 Index Objects with Pandas.
Comprehensive guide to using Python for data science. It covers data cleaning, data wrangling, data visualization, and machine learning. It also discusses how to use Python in a data science environment.
Provides a detailed introduction to Pandas, one of the most popular Python libraries for data analysis. It covers a wide range of topics, including data cleaning, data manipulation, data visualization, and data mining.
Guide to using Pandas for machine learning. It covers data cleaning, data wrangling, data visualization, and machine learning with Pandas. It also discusses how to use Pandas in a machine learning environment.
Is for users of all levels. While beginners will appreciate the introduction to Pandas, experienced users can use this book as a reference. It provides ready-to-use recipes on data manipulation, advanced data structures, data analysis, data visualization, and performance optimization in Pandas.
Provides a comprehensive overview of Pandas. It starts with the basics of data-frames and data manipulation. Then, it discusses advanced topics such as time series analysis, data visualization, and data mining. It good reference book for Pandas users of all levels.
Provides an introduction to machine learning techniques that can be used with Python. It covers a wide range of topics, including data cleaning, data visualization, data mining, and machine learning.
Provides an overview of data science techniques that are commonly used in a business context. It covers a wide range of topics, including data cleaning, data visualization, data mining, and machine learning.
Provides a comprehensive overview of data science techniques that are commonly used in a business context. It covers a wide range of topics, including data cleaning, data visualization, data mining, and machine learning.
Provides an introduction to data mining techniques that can be used with Python. It covers a wide range of topics, including data cleaning, data visualization, data mining, and machine learning.
Provides an introduction to machine learning techniques that can be used with Python. It covers a wide range of topics, including data cleaning, data visualization, data mining, and machine learning.
Provides an introduction to deep learning techniques that can be used with Python. It covers a wide range of topics, including data cleaning, data visualization, data mining, and machine learning.
Provides an introduction to deep learning techniques that can be used with Python. It covers a wide range of topics, including data cleaning, data visualization, data mining, and machine learning.
Starts off with a discussion on data-frames and their different operations. Then, it discusses time series, cross-sectional, hierarchical, and panel data in detail. Each chapter includes examples that will help the novice user to get up to speed with data manipulation in Pandas.
Covers the basics of using Python for data analysis. It covers loading data in different formats, cleaning data, data visualization, and machine learning. While it is not Pandas-specific, it will be a helpful resource if you are new to Python and data analysis.

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