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Dhiraj Kumar
This course will teach you advanced parts of this library. When you’re
finished with this course, you’ll have the skills and knowledge of
DataFrames and Pandas needed to analyze your data with Pandas.
Read more
This course will teach you advanced parts of this library. When you’re finished with this course, you’ll have the skills and knowledge of DataFrames and Pandas needed to analyze your data with Pandas.
Read more
This course will teach you advanced parts of this library. When you’re finished with this course, you’ll have the skills and knowledge of DataFrames and Pandas needed to analyze your data with Pandas.
Learn to handle complex data frames, analyze your data with Pandas, and dive into the advanced parts of this library. In this course, DataFrames with Pandas, you’ll gain the ability to analyze your data with Pandas. First, you’ll explore DataFrame Attributes. Next, you’ll discover Reshaping, Sorting, and Transposing DataFrames. Finally, you’ll learn how serialization works in DataFrames. When you’re finished with this course, you’ll have the skills and knowledge of DataFrames and Pandas needed to analyze your data with Pandas.
Register for this course and see more details by visiting:
OpenCourser.com/course/dsmhn0/dataframes
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What's inside
Syllabus
Course Overview
DataFrame Attributes
Reshaping, Sorting, and Transposing DataFrames
Serialization in DataFrames
Read more
Syllabus
Course Overview
DataFrame Attributes
Reshaping, Sorting, and Transposing DataFrames
Serialization in DataFrames
Read more
Good to know
Good to know
Know what's good ,
what to watch for , and
possible dealbreakers
Deepens an existing foundation for intermediate learners
Develops professional skills or deep expertise in a particular topic or set of topics
Teaches skills, knowledge, and/or tools that are highly relevant to industry
Taught by Dhiraj Kumar, who are recognized for their work in this topic
Explores DataFrame Attributes, which is standard in industry
Save this course
Save DataFrames 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 DataFrames with Pandas with these
activities:
Review Fundamental Pandas Concepts
Show steps
Strengthen your foundation by reviewing essential Pandas concepts before delving into advanced topics.
Browse courses on
Data Manipulation
Show steps
-
Review documentation or tutorials
-
Complete practice exercises on basic operations
Seek Guidance from Experienced DataFrame Users
Show steps
Accelerate your learning by seeking guidance and advice from experts in the field of DataFrame analysis.
Browse courses on
Mentorship
Show steps
-
Identify potential mentors
-
Reach out and request guidance
Review Wes McKinney's 'Python for Data Analysis'
Show steps
Gain deeper insights into advanced Pandas techniques by studying a reference book written by the creator of the library.
View
Python for Data Analysis: Data Wrangling with...
on Amazon
Show steps
-
Read relevant sections on DataFrames
-
Experiment with code examples provided in the book
Five other activities
Expand to see all activities and additional details
Show all eight activities
Follow Tutorials on DataFrame Manipulation
Show steps
Reinforce your understanding of DataFrame attributes and operations by following guided tutorials that provide step-by-step instructions.
Browse courses on
Data Manipulation
Show steps
-
Identify relevant tutorials
-
Follow instructions and complete exercises
-
Experiment with different DataFrame operations
Join a Study Group for DataFrame Analysis
Show steps
Engage with peers, share knowledge, and resolve challenges together by joining a study group focused on DataFrame analysis.
Show steps
-
Find or create a study group
-
Discuss topics, work on problems together
Practice Data Analysis with DataFrames
Show steps
Solidify your skills in data analysis using Pandas DataFrames through repetitive exercises and drills that challenge your understanding.
Browse courses on
Data Analysis
Show steps
-
Find practice problems or datasets
-
Analyze data using DataFrame operations
-
Interpret results and draw conclusions
Create a Demo Project for DataFrame Analysis
Show steps
Enhance your practical knowledge by creating a project that demonstrates your ability to apply DataFrame analysis techniques to solve real-world problems.
Browse courses on
Data Analysis
Show steps
-
Identify a problem or dataset
-
Design and implement a solution using DataFrames
-
Visualize and present your results
Mentor Beginner Learners in DataFrame Analysis
Show steps
Reinforce your understanding by mentoring others, answering questions, and guiding them through DataFrame analysis concepts.
Browse courses on
Mentoring
Show steps
-
Identify opportunities to mentor
-
Provide guidance and support
-
Reflect on your own understanding
Review Fundamental Pandas Concepts
Show steps
Strengthen your foundation by reviewing essential Pandas concepts before delving into advanced topics.
Browse courses on
Data Manipulation
Show steps
Show steps
Show steps
- Review documentation or tutorials
- Complete practice exercises on basic operations
Seek Guidance from Experienced DataFrame Users
Show steps
Accelerate your learning by seeking guidance and advice from experts in the field of DataFrame analysis.
Browse courses on
Mentorship
Show steps
Show steps
Show steps
- Identify potential mentors
- Reach out and request guidance
Review Wes McKinney's 'Python for Data Analysis'
Show steps
Gain deeper insights into advanced Pandas techniques by studying a reference book written by the creator of the library.
View
Python for Data Analysis: Data Wrangling with...
on Amazon
Show steps
Show steps
Show steps
- Read relevant sections on DataFrames
- Experiment with code examples provided in the book
Five other activities
Expand to see all activities and additional details
Show all eight activities
Follow Tutorials on DataFrame Manipulation
Show steps
Reinforce your understanding of DataFrame attributes and operations by following guided tutorials that provide step-by-step instructions.
Browse courses on
Data Manipulation
Show steps
Show steps
Show steps
- Identify relevant tutorials
- Follow instructions and complete exercises
- Experiment with different DataFrame operations
Join a Study Group for DataFrame Analysis
Show steps
Engage with peers, share knowledge, and resolve challenges together by joining a study group focused on DataFrame analysis.
Show steps
Show steps
Show steps
- Find or create a study group
- Discuss topics, work on problems together
Practice Data Analysis with DataFrames
Show steps
Solidify your skills in data analysis using Pandas DataFrames through repetitive exercises and drills that challenge your understanding.
Browse courses on
Data Analysis
Show steps
Show steps
Show steps
- Find practice problems or datasets
- Analyze data using DataFrame operations
- Interpret results and draw conclusions
Create a Demo Project for DataFrame Analysis
Show steps
Enhance your practical knowledge by creating a project that demonstrates your ability to apply DataFrame analysis techniques to solve real-world problems.
Browse courses on
Data Analysis
Show steps
Show steps
Show steps
- Identify a problem or dataset
- Design and implement a solution using DataFrames
- Visualize and present your results
Mentor Beginner Learners in DataFrame Analysis
Show steps
Reinforce your understanding by mentoring others, answering questions, and guiding them through DataFrame analysis concepts.
Browse courses on
Mentoring
Show steps
Show steps
Show steps
- Identify opportunities to mentor
- Provide guidance and support
- Reflect on your own understanding
Career center
Learners who complete DataFrames with Pandas will develop knowledge and skills
that may be useful to these careers:
Data Scientist
Data Scientist
Data Scientists use their expertise in machine learning, statistics, and programming to extract valuable insights from data. They use these insights to develop predictive models, solve business problems, and make informed decisions. This course, DataFrames with Pandas, can be a valuable tool for Data Scientists because it provides them with the skills they need to clean, manipulate, and analyze large datasets using the Pandas library. By mastering these techniques, Data Scientists can streamline their workflow and accelerate their research and development.
Machine Learning Engineer
Machine Learning Engineer
Machine Learning Engineers design, develop, and deploy machine learning models to solve real-world problems. They use their skills in machine learning, statistics, and programming to build models that can learn from data and make predictions. This course, DataFrames with Pandas, can be a valuable tool for Machine Learning Engineers because it provides them with the skills they need to clean, manipulate, and analyze large datasets using the Pandas library. By mastering these techniques, Machine Learning Engineers can improve the accuracy and efficiency of their models.
Business Analyst
Business Analyst
Business Analysts use their skills in data analysis, statistics, and business acumen to help organizations make better decisions. They use their knowledge of data to identify opportunities, solve problems, and improve performance. This course, DataFrames with Pandas, can be a valuable tool for Business Analysts because it provides them with the skills they need to clean, manipulate, and analyze data using the Pandas library. By mastering these techniques, Business Analysts can gain a deeper understanding of their data and make more informed recommendations to their organizations.
Operations Research Analyst
Operations Research Analyst
Operations Research Analysts use their skills in data analysis, statistics, and optimization to help organizations solve complex business problems. They use their knowledge of mathematical models to identify and solve problems in areas such as supply chain management, logistics, and healthcare. This course, DataFrames with Pandas, can be a valuable tool for Operations Research Analysts because it provides them with the skills they need to clean, manipulate, and analyze data using the Pandas library. By mastering these techniques, Operations Research Analysts can improve the efficiency and effectiveness of their operations.
Statistician
Statistician
Statisticians use their skills in data analysis, statistics, and probability to help organizations understand data and make informed decisions. They use their knowledge of statistical methods and models to design and conduct studies, analyze data, and draw conclusions. This course, DataFrames with Pandas, can be a valuable tool for Statisticians because it provides them with the skills they need to clean, manipulate, and analyze data using the Pandas library. By mastering these techniques, Statisticians can improve the accuracy and efficiency of their analysis.
Data Analyst
Data Analyst
A Data Analyst processes and interprets data to help organizations make data-driven decisions. They use their skills in data analysis, statistics, and programming to transform raw data into actionable insights. This course, DataFrames with Pandas, can be a valuable tool for Data Analysts because it teaches advanced techniques for cleaning, manipulating, and analyzing data using the Pandas library. By mastering these techniques, Data Analysts can gain a deeper understanding of their data and make more informed recommendations to their organizations.
Financial Analyst
Financial Analyst
Financial Analysts use their skills in data analysis, statistics, and finance to help organizations make investment decisions. They use their knowledge of financial data to identify opportunities, assess risks, and make recommendations. This course, DataFrames with Pandas, can be a valuable tool for Financial Analysts because it provides them with the skills they need to clean, manipulate, and analyze financial data using the Pandas library. By mastering these techniques, Financial Analysts can gain a deeper understanding of their data and make more informed investment recommendations.
Marketing Analyst
Marketing Analyst
Marketing Analysts use their skills in data analysis, statistics, and marketing to help organizations understand their customers and make better marketing decisions. They use their knowledge of marketing data to identify trends, measure campaign effectiveness, and optimize marketing strategies. This course, DataFrames with Pandas, can be a valuable tool for Marketing Analysts because it provides them with the skills they need to clean, manipulate, and analyze marketing data using the Pandas library. By mastering these techniques, Marketing Analysts can gain a deeper understanding of their data and make more informed marketing decisions.
Risk Analyst
Risk Analyst
Risk Analysts use their skills in data analysis, statistics, and risk management to help organizations identify and assess risks. They use their knowledge of risk data to develop and implement risk management strategies that can protect organizations from financial losses and other threats. This course, DataFrames with Pandas, can be a valuable tool for Risk Analysts because it provides them with the skills they need to clean, manipulate, and analyze risk data using the Pandas library. By mastering these techniques, Risk Analysts can improve the accuracy and efficiency of their risk assessments.
Product Manager
Product Manager
Product Managers use their skills in data analysis, statistics, and product development to help organizations build and launch successful products. They use their knowledge of product data to identify opportunities, define product requirements, and track product performance. This course, DataFrames with Pandas, can be a valuable tool for Product Managers because it provides them with the skills they need to clean, manipulate, and analyze product data using the Pandas library. By mastering these techniques, Product Managers can gain a deeper understanding of their data and make more informed product decisions.
Data Engineer
Data Engineer
Data Engineers design, build, and maintain the infrastructure that stores and processes data. They use their skills in data engineering, programming, and cloud computing to create and manage data pipelines that can handle large volumes of data. This course, DataFrames with Pandas, can be a valuable tool for Data Engineers because it provides them with the skills they need to clean, manipulate, and analyze data using the Pandas library. By mastering these techniques, Data Engineers can improve the efficiency and reliability of their data pipelines.
Quantitative Analyst
Quantitative Analyst
Quantitative Analysts use their skills in data analysis, statistics, and finance to help organizations make investment decisions. They use their knowledge of financial data to develop and implement quantitative models for pricing securities, managing risk, and making trading decisions. This course, DataFrames with Pandas, can be a valuable tool for Quantitative Analysts because it provides them with the skills they need to clean, manipulate, and analyze financial data using the Pandas library. By mastering these techniques, Quantitative Analysts can improve the accuracy and efficiency of their models.
Business Intelligence Analyst
Business Intelligence Analyst
Business Intelligence Analysts use their skills in data analysis, statistics, and business intelligence to help organizations make better decisions. They use their knowledge of data and business intelligence tools to identify trends, patterns, and opportunities that can help organizations improve their performance. This course, DataFrames with Pandas, can be a valuable tool for Business Intelligence Analysts because it provides them with the skills they need to clean, manipulate, and analyze data using the Pandas library. By mastering these techniques, Business Intelligence Analysts can improve the accuracy and efficiency of their analysis.
Data Visualization Engineer
Data Visualization Engineer
Data Visualization Engineers use their skills in data analysis, statistics, and visualization to help organizations communicate data insights effectively. They use their knowledge of data and visual design to create visually appealing and informative data visualizations that can help users understand complex data. This course, DataFrames with Pandas, can be a valuable tool for Data Visualization Engineers because it provides them with the skills they need to clean, manipulate, and analyze data using the Pandas library. By mastering these techniques, Data Visualization Engineers can improve the accuracy and efficiency of their visualizations.
For more career information including salaries, visit:
OpenCourser.com/course/dsmhn0/dataframes
Reading list
We've selected nine 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
DataFrames with Pandas.
Provides a comprehensive overview of data analysis with Pandas, covering topics such as data cleaning, manipulation, and visualization. It is an excellent resource for beginners and intermediate users alike.
Provides a comprehensive guide to Python for data science, including coverage of Pandas. It valuable resource for learners who want to master the fundamentals of data science and apply it with Python.
Offers a comprehensive introduction to statistical learning with Python, including coverage of Pandas. It suitable choice for learners who want to gain a deeper understanding of statistical methods and their application in data analysis.
Provides a comprehensive introduction to machine learning with Python, including coverage of Pandas. It suitable choice for learners who want to gain practical experience with machine learning algorithms and their application in data analysis.
Offers a practical approach to data analysis with Pandas, with step-by-step instructions and hands-on exercises. It great choice for learners who want to apply their Pandas skills to real-world projects.
Provides a comprehensive introduction to data science with Python and Pandas. It covers topics such as data manipulation, visualization, and machine learning. It suitable choice for learners who want to gain a broad understanding of data science.
Provides a comprehensive introduction to deep learning with Python. Although it does not cover Pandas specifically, it offers a valuable foundation for learners who want to apply deep learning techniques to data analysis tasks.
Offers a comprehensive introduction to natural language processing with Python. Although it does not cover Pandas specifically, it provides a valuable foundation for learners who want to apply natural language processing techniques to data analysis tasks.
Provides a gentle introduction to Pandas, making it suitable for beginners who are new to data analysis. It covers the basics of data manipulation, cleaning, and visualization.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/dsmhn0/dataframes
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Time
65 hours
Level
Introductory
Via
Pluralsight
Instructor
Dhiraj Kumar
Language
English
Good to know
Deepens an existing foundation for intermediate learners
Develops professional skills or deep expertise in a particular topic or set of topics
Teaches skills, knowledge, and/or tools that are highly relevant to industry
Taught by Dhiraj Kumar, who are recognized for their work in this topic
Explores DataFrame Attributes, which is standard in industry
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