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Paweł Kordek
Learn to handle complex data-sets and analyze your data in a principled way with Pandas. This course will teach you advanced parts of this library, including handling higher-dimensional data, time series, window operations, joins, and plotting.
Read more
Learn to handle complex data-sets and analyze your data in a principled way with Pandas. This course will teach you advanced parts of this library, including handling higher-dimensional data, time series, window operations, joins, and plotting.
Read more
Learn to handle complex data-sets and analyze your data in a principled way with Pandas. This course will teach you advanced parts of this library, including handling higher-dimensional data, time series, window operations, joins, and plotting.
At the core of practicing effective data science is a thorough knowledge of data analysis tools, and among them, Pandas is one of the most popular. In this course, Advanced Pandas, you will learn the skills you need to perform data analysis that is effective and full of useful insights. First, you will learn how to prepare your dataset for a smoother experience. Next, you will discover how to perform database-style joins, work with higher-dimensional data, analyze time series, and apply window operations. Finally, you will explore how to present the data by generating informative and appealing plots. When you’re finished with this course, you will have an advanced understanding of the Pandas library and the knowledge that will help you as you move forward and grow as a professional data scientist or analyst.
Register for this course and see more details by visiting:
OpenCourser.com/course/8fjyh9/advanced
What's inside
Syllabus
Course Overview
Overview
Preparing Your Dataset
Joining Multiple Data Tables
Read more
Syllabus
Course Overview
Overview
Preparing Your Dataset
Joining Multiple Data Tables
Read more
Moving Between Long and Wide Data Formats
Multi-level Indexes
Handling Time Series
Getting More Insights into Your Data with Windows
Plotting and Presenting Your Data
Good to know
Good to know
Know what's good ,
what to watch for , and
possible dealbreakers
Meant for practitioners who analyze data and derive insights from it, such as data scientists and analysts
Taught by Paweł Kordek, who is an experienced data scientist and educator
Includes practical elements, such as window operations and data plotting, that are highly relevant in the field
Develops advanced skills in Pandas, which is a popular and widely used data analysis library
Covers higher-dimensional data, time series, and database-style joins, which are essential concepts for data analysis
Requires learners to have a strong foundation in data analysis and Pandas library
Save this course
Save Advanced 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 Advanced Pandas with these
activities:
Review Python syntax and data structures
Show steps
Refreshing your Python skills will ensure that you have a strong foundation for applying Pandas effectively.
Browse courses on
Python
Show steps
-
Go through online tutorials or documentation to review Python syntax and data structures.
-
Practice writing simple Python code to reinforce your understanding.
Join a study group or discussion forum for Pandas
Show steps
Joining a study group or discussion forum allows you to connect with other learners and engage in discussions about Pandas.
Browse courses on
Pandas
Show steps
-
Find a study group or discussion forum that aligns with your interests.
-
Participate actively in discussions and ask questions.
-
Help other members of the group by sharing your knowledge and experience.
Follow a tutorial on time series analysis with Pandas
Show steps
Following a tutorial on time series analysis will provide you with the necessary skills to handle and analyze time-based data.
Browse courses on
Pandas
Show steps
-
Find a well-regarded tutorial on time series analysis with Pandas.
-
Follow the tutorial step-by-step and practice the examples provided.
-
Try to apply what you've learned to your own time series data.
Four other activities
Expand to see all activities and additional details
Show all seven activities
Start a project in Python using Pandas
Show steps
Creating a project that focuses on using Pandas will help you familiarize yourself with its functionalities and their applications.
Browse courses on
Python
Show steps
-
Decide on a project idea that you'd like to work on.
-
Collect the data that you need for your project.
-
Create a Jupyter Notebook or a Python script to start working on your project.
Read 'Python for Data Analysis' by Wes McKinney
Show steps
This book provides a comprehensive overview of Pandas and its applications in data analysis, helping you deepen your understanding and expand your skills.
View
Python for Data Analysis: Data Wrangling with...
on Amazon
Show steps
-
Read through the chapters relevant to Pandas and data analysis.
-
Work through the exercises and examples provided in the book to practice using Pandas.
-
Refer back to specific sections of the book as needed to reinforce your understanding or refresh your memory.
Practice using Pandas window operations
Show steps
Practicing window operations in Pandas will help you master essential data manipulation techniques.
Browse courses on
Pandas
Show steps
-
Start by creating a DataFrame with sample data.
-
Use the 'rolling' or 'expanding' functions to apply window operations to your DataFrame.
-
Experiment with different window sizes and aggregation functions to observe the effects on your data.
Create a data visualization using Pandas
Show steps
Creating a data visualization will help you present your data in a clear and visually appealing way, enhancing its impact and understanding.
Browse courses on
Pandas
Show steps
-
Choose a dataset that you want to visualize.
-
Use Pandas to clean and prepare your data for visualization.
-
Select appropriate charts or graphs to represent your data effectively.
-
Customize the visualization to make it visually appealing and informative.
Review Python syntax and data structures
Show steps
Refreshing your Python skills will ensure that you have a strong foundation for applying Pandas effectively.
Browse courses on
Python
Show steps
Show steps
Show steps
- Go through online tutorials or documentation to review Python syntax and data structures.
- Practice writing simple Python code to reinforce your understanding.
Join a study group or discussion forum for Pandas
Show steps
Joining a study group or discussion forum allows you to connect with other learners and engage in discussions about Pandas.
Browse courses on
Pandas
Show steps
Show steps
Show steps
- Find a study group or discussion forum that aligns with your interests.
- Participate actively in discussions and ask questions.
- Help other members of the group by sharing your knowledge and experience.
Follow a tutorial on time series analysis with Pandas
Show steps
Following a tutorial on time series analysis will provide you with the necessary skills to handle and analyze time-based data.
Browse courses on
Pandas
Show steps
Show steps
Show steps
- Find a well-regarded tutorial on time series analysis with Pandas.
- Follow the tutorial step-by-step and practice the examples provided.
- Try to apply what you've learned to your own time series data.
Four other activities
Expand to see all activities and additional details
Show all seven activities
Start a project in Python using Pandas
Show steps
Creating a project that focuses on using Pandas will help you familiarize yourself with its functionalities and their applications.
Browse courses on
Python
Show steps
Show steps
Show steps
- Decide on a project idea that you'd like to work on.
- Collect the data that you need for your project.
- Create a Jupyter Notebook or a Python script to start working on your project.
Read 'Python for Data Analysis' by Wes McKinney
Show steps
This book provides a comprehensive overview of Pandas and its applications in data analysis, helping you deepen your understanding and expand your skills.
View
Python for Data Analysis: Data Wrangling with...
on Amazon
Show steps
Show steps
Show steps
- Read through the chapters relevant to Pandas and data analysis.
- Work through the exercises and examples provided in the book to practice using Pandas.
- Refer back to specific sections of the book as needed to reinforce your understanding or refresh your memory.
Practice using Pandas window operations
Show steps
Practicing window operations in Pandas will help you master essential data manipulation techniques.
Browse courses on
Pandas
Show steps
Show steps
Show steps
- Start by creating a DataFrame with sample data.
- Use the 'rolling' or 'expanding' functions to apply window operations to your DataFrame.
- Experiment with different window sizes and aggregation functions to observe the effects on your data.
Create a data visualization using Pandas
Show steps
Creating a data visualization will help you present your data in a clear and visually appealing way, enhancing its impact and understanding.
Browse courses on
Pandas
Show steps
Show steps
Show steps
- Choose a dataset that you want to visualize.
- Use Pandas to clean and prepare your data for visualization.
- Select appropriate charts or graphs to represent your data effectively.
- Customize the visualization to make it visually appealing and informative.
Career center
Learners who complete Advanced Pandas will develop knowledge and skills
that may be useful to these careers:
Statistician
Statistician
Statisticians collect, analyze, interpret, and present data to help organizations make informed decisions. The Advanced Pandas course can help aspiring Statisticians develop the skills needed to succeed in this role, as it teaches how to perform data analysis on complex datasets, including handling time series, applying window operations, and generating informative plots. This course may be particularly relevant for Statisticians who work with large and complex datasets and need advanced data analysis techniques to uncover meaningful insights.
Data Scientist
Data Scientist
Data Scientists use their knowledge of mathematics, statistics, and computer science to extract insights from data, build models, and make predictions. The Advanced Pandas course can help aspiring Data Scientists develop the skills needed to succeed in this role, as it teaches how to perform data analysis on complex datasets, including handling time series, applying window operations, and generating informative plots. This course may be particularly relevant for Data Scientists who work with large and complex datasets and need advanced data analysis techniques to build accurate and effective models.
Data Analyst
Data Analyst
Data Analysts model, analyze, and interpret data in order to extract useful and actionable insights that can help organizations make informed business decisions. The Advanced Pandas course can help aspiring Data Analysts develop the skills needed to succeed in this role, as it teaches how to perform data analysis on complex datasets, including handling time series, applying window operations, and generating informative plots. This course may be particularly relevant for Data Analysts who work with large and complex datasets and need advanced data analysis techniques to uncover meaningful insights.
Market Analyst
Market Analyst
Market Analysts use data analysis techniques to identify trends and opportunities in the market. The Advanced Pandas course can help aspiring Market Analysts develop the skills needed to succeed in this role, as it teaches how to perform data analysis on complex datasets, including handling time series, applying window operations, and generating informative plots. This course may be particularly relevant for Market Analysts who work with large and complex datasets and need advanced data analysis techniques to make accurate market forecasts.
Business Analyst
Business Analyst
Business Analysts use data analysis techniques to identify and solve business problems. The Advanced Pandas course can help aspiring Business Analysts develop the skills needed to succeed in this role, as it teaches how to perform data analysis on complex datasets, including handling time series, applying window operations, and generating informative plots. This course may be particularly relevant for Business Analysts who work with large and complex datasets and need advanced data analysis techniques to develop effective business solutions.
Financial Analyst
Financial Analyst
Financial Analysts use data analysis techniques to evaluate investments and make recommendations to clients. The Advanced Pandas course can help aspiring Financial Analysts develop the skills needed to succeed in this role, as it teaches how to perform data analysis on complex datasets, including handling time series, applying window operations, and generating informative plots. This course may be particularly relevant for Financial Analysts who work with large and complex datasets and need advanced data analysis techniques to make sound investment decisions.
Biostatistician
Biostatistician
Biostatisticians use statistical methods to design and analyze studies, interpret data, and make inferences about the health of populations. The Advanced Pandas course can help aspiring Biostatisticians develop the skills needed to succeed in this role, as it teaches how to perform data analysis on complex datasets, including handling time series, applying window operations, and generating informative plots. This course may be particularly relevant for Biostatisticians who work with large and complex datasets and need advanced data analysis techniques to conduct rigorous research.
Actuary
Actuary
Actuaries use mathematical and statistical methods to assess risk and uncertainty. The Advanced Pandas course can help aspiring Actuaries develop the skills needed to succeed in this role, as it teaches how to perform data analysis on complex datasets, including handling time series, applying window operations, and generating informative plots. This course may be particularly relevant for Actuaries who work with large and complex datasets and need advanced data analysis techniques to develop accurate risk models.
Epidemiologist
Epidemiologist
Epidemiologists investigate the causes and patterns of disease in populations. The Advanced Pandas course can help aspiring Epidemiologists develop the skills needed to succeed in this role, as it teaches how to perform data analysis on complex datasets, including handling time series, applying window operations, and generating informative plots. This course may be particularly relevant for Epidemiologists who work with large and complex datasets and need advanced data analysis techniques to identify and track disease outbreaks.
Fraud Analyst
Fraud Analyst
Fraud Analysts investigate and prevent fraud. The Advanced Pandas course may be useful for aspiring Fraud Analysts who want to develop skills in data analysis and data handling. The course teaches how to perform data analysis on complex datasets, including handling time series, applying window operations, and generating informative plots. This knowledge can be beneficial for Fraud Analysts who work on projects that involve data analysis or data visualization.
Software Engineer
Software Engineer
Software Engineers design, develop, and maintain software applications. The Advanced Pandas course may be useful for aspiring Software Engineers who want to develop skills in data analysis and data handling. The course teaches how to perform data analysis on complex datasets, including handling time series, applying window operations, and generating informative plots. This knowledge can be beneficial for Software Engineers who work on projects that involve data analysis or data visualization.
Database Administrator
Database Administrator
Database Administrators design, implement, and maintain databases. The Advanced Pandas course may be useful for aspiring Database Administrators who want to develop skills in data analysis and data handling. The course teaches how to perform data analysis on complex datasets, including handling time series, applying window operations, and generating informative plots. This knowledge can be beneficial for Database Administrators who work on projects that involve data analysis or data visualization.
Risk Analyst
Risk Analyst
Risk Analysts identify, assess, and manage risks. The Advanced Pandas course may be useful for aspiring Risk Analysts who want to develop skills in data analysis and data handling. The course teaches how to perform data analysis on complex datasets, including handling time series, applying window operations, and generating informative plots. This knowledge can be beneficial for Risk Analysts who work on projects that involve data analysis or data visualization.
Data Engineer
Data Engineer
Data Engineers design, build, and maintain data pipelines and infrastructure. The Advanced Pandas course may be useful for aspiring Data Engineers who want to develop skills in data analysis and data handling. The course teaches how to perform data analysis on complex datasets, including handling time series, applying window operations, and generating informative plots. This knowledge can be beneficial for Data Engineers who work on projects that involve data analysis or data visualization.
Quantitative Analyst
Quantitative Analyst
Quantitative Analysts use mathematical and statistical methods to analyze financial data and make investment decisions. The Advanced Pandas course may be useful for aspiring Quantitative Analysts who want to develop skills in data analysis and data handling. The course teaches how to perform data analysis on complex datasets, including handling time series, applying window operations, and generating informative plots. This knowledge can be beneficial for Quantitative Analysts who work on projects that involve data analysis or data visualization.
For more career information including salaries, visit:
OpenCourser.com/course/8fjyh9/advanced
Reading list
We've selected ten 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
Advanced Pandas.
Is the definitive reference for Pandas, written by its creator. It provides a comprehensive guide to all aspects of using Pandas, from basic data manipulation to advanced techniques.
Este libro es la referencia definitiva para Pandas, escrita por su creador. Proporciona una guía completa de todos los aspectos del uso de Pandas, desde la manipulación básica de datos hasta técnicas avanzadas.
Save
Este libro proporciona una descripción general completa de Pandas, que cubre sus funciones principales y técnicas avanzadas, incluida la limpieza de datos, la manipulación, la visualización y el análisis estadístico.
Save
Provides a comprehensive overview of Pandas and its applications to data analysis.
Save
Provides a practical guide to using Pandas for data science.
Provides a comprehensive guide to time series analysis using Pandas. It covers topics such as data cleaning, manipulation, visualization, and forecasting.
Provides a comprehensive overview of deep learning using Python, including a section on using Pandas.
Provides a comprehensive overview of natural language processing using Python, including a section on using Pandas.
Provides a broad overview of data science, including a section on using Pandas.
Provides a comprehensive overview of machine learning using Python, including a section on using Pandas.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/8fjyh9/advanced
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Time
150 hours
Level
Intermediate
Via
Pluralsight
Instructor
Paweł Kordek
Language
English
Good to know
Meant for practitioners who analyze data and derive insights from it, such as data scientists and analysts
Taught by Paweł Kordek, who is an experienced data scientist and educator
Includes practical elements, such as window operations and data plotting, that are highly relevant in the field
Develops advanced skills in Pandas, which is a popular and widely used data analysis library
Covers higher-dimensional data, time series, and database-style joins, which are essential concepts for data analysis
Requires learners to have a strong foundation in data analysis and Pandas library
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