Python Pandas courses can help you learn data manipulation, data analysis, and data visualization techniques. You can build skills in handling large datasets, performing statistical analysis, and cleaning data for better insights. Many courses introduce tools like Jupyter Notebooks and Matplotlib, that support applying your skills in real-world data projects. You'll also explore key topics such as time series analysis, merging datasets, and using functions to automate repetitive tasks, making your data workflows more efficient.

Skills you'll gain: Data Import/Export, Programming Principles, Web Scraping, File I/O, Python Programming, Jupyter, Data Structures, Data Processing, Pandas (Python Package), Data Manipulation, JSON, Computer Programming, Restful API, NumPy, Object Oriented Programming (OOP), Scripting, Application Programming Interface (API), Automation, Data Analysis
Beginner · Course · 1 - 3 Months

Skills you'll gain: Exploratory Data Analysis, Model Evaluation, Data Transformation, Data Analysis, Data Cleansing, Data Manipulation, Data Import/Export, Predictive Modeling, Data Preprocessing, Regression Analysis, Data Science, Statistical Analysis, Pandas (Python Package), Scikit Learn (Machine Learning Library), Data-Driven Decision-Making, Matplotlib, Data Visualization, NumPy, Python Programming
Intermediate · Course · 1 - 3 Months

Duke University
Skills you'll gain: Pandas (Python Package), Version Control, Git (Version Control System), Data Manipulation, Software Development Tools, Development Environment, Data Structures, Python Programming, Data Analysis Software, NumPy, Virtual Environment
Beginner · Course · 1 - 4 Weeks

Skills you'll gain: Pandas (Python Package), NumPy, Data Manipulation, Data Preprocessing, Package and Software Management, Data Analysis, Data Transformation, Data Integration, JSON, Object Oriented Programming (OOP), Data Wrangling, Data Science, Python Programming, Computer Programming, Programming Principles, Data Import/Export, Software Design, Data Validation, Computational Logic, Data Structures
Beginner · Specialization · 3 - 6 Months

Skills you'll gain: Pandas (Python Package), Data Import/Export, Matplotlib, Pivot Tables And Charts, Jupyter, Data Visualization Software, Data Visualization, Microsoft Excel, Data Analysis, Text Mining, Data Manipulation, Data Cleansing, NumPy, Data Analysis Software, Data Wrangling, Time Series Analysis and Forecasting, Python Programming, Data Preprocessing, Data Structures, Development Environment
Intermediate · Specialization · 3 - 6 Months

Red Hat
Skills you'll gain: Object Oriented Programming (OOP), JSON, Python Programming, Debugging, Data Structures, Red Hat Enterprise Linux, Computer Programming, Statistical Programming, Web Development, Scripting, Scripting Languages, Development Environment, Text Mining, Software Installation
Intermediate · Course · 3 - 6 Months

Duke University
Skills you'll gain: Pandas (Python Package), Data Cleansing, Data Manipulation, Data Preprocessing, Data Quality, NumPy, File I/O, Data Integration, Python Programming, Data Import/Export, Data Analysis, Exploratory Data Analysis, Debugging
Beginner · Course · 1 - 4 Weeks

University of Pennsylvania
Skills you'll gain: Matplotlib, Data Analysis, Pandas (Python Package), Data Visualization, Data Science, Data Cleansing, Pivot Tables And Charts, Data Visualization Software, Data Preprocessing, Data Manipulation, Scatter Plots, NumPy, Exploratory Data Analysis, Jupyter, Data Import/Export, Histogram, Python Programming, Data Structures, Programming Principles
Beginner · Course · 1 - 4 Weeks

Skills you'll gain: Pandas (Python Package), Pivot Tables And Charts, Data Manipulation, Data Import/Export, NumPy, Time Series Analysis and Forecasting, Business Reporting, Jupyter, Data Wrangling, Microsoft Excel, Data Transformation, Matplotlib, Data Analysis, Data Cleansing, Data Preprocessing, Analytics, Data Processing, Management Reporting, Business Analytics, Python Programming
Beginner · Specialization · 1 - 3 Months

Skills you'll gain: Pandas (Python Package), NumPy, Data Analysis, Data Science, Python Programming, Data Structures, Exploratory Data Analysis, Data Manipulation, Computer Programming
Beginner · Guided Project · Less Than 2 Hours

University of Michigan
Skills you'll gain: Debugging, Data Analysis, Data Preprocessing, Numerical Analysis, Critical Thinking
Intermediate · Course · 1 - 4 Weeks

Microsoft
Skills you'll gain: Web Scraping, Data Structures, Git (Version Control System), Generative AI, Version Control, Matplotlib, Devops Tools, Plotly, DevOps, Agile Methodology, Web Development, Data Ethics, Flask (Web Framework), Data Visualization, Scripting, GitHub, Debugging, Data Analysis, Automation, Cloud Computing
Beginner · Professional Certificate · 3 - 6 Months
Python Pandas is a powerful open-source data analysis and manipulation library for the Python programming language. It provides data structures like Series and DataFrames, which allow for efficient handling of structured data. Pandas is important because it simplifies complex data operations, making it easier for individuals and organizations to analyze and visualize data. With its intuitive syntax and robust functionality, Pandas is widely used in data science, finance, and many other fields where data-driven decision-making is crucial.‎
With skills in Python Pandas, you can pursue various job roles in data analysis, data science, and business intelligence. Common job titles include Data Analyst, Data Scientist, Business Analyst, and Data Engineer. These positions often require the ability to manipulate and analyze large datasets, create visualizations, and derive insights that inform business strategies. Additionally, many organizations seek professionals who can automate data processing tasks, making Python Pandas a valuable asset in the job market.‎
To learn Python Pandas effectively, you should have a foundational understanding of Python programming. Familiarity with basic data structures, functions, and libraries like NumPy is also beneficial. Additionally, knowledge of statistics and data visualization concepts can enhance your ability to analyze and present data. As you progress, you may want to explore topics like data cleaning, data transformation, and exploratory data analysis, which are essential for working with real-world datasets.‎
There are several excellent online courses available for learning Python Pandas. For a comprehensive learning experience, consider the Data Analysis with Pandas and Python Specialization, which covers fundamental to advanced topics. Alternatively, the Foundations of Data Analysis with Pandas and Python course offers a solid introduction to data analysis techniques using Pandas.‎
Yes. You can start learning python pandas on Coursera for free in two ways:
If you want to keep learning, earn a certificate in python pandas, or unlock full course access after the preview or trial, you can upgrade or apply for financial aid.‎
To learn Python Pandas, start by familiarizing yourself with Python basics if you haven't already. Next, explore online courses or tutorials that focus on Pandas, such as the BiteSize Python: NumPy and Pandas course. Practice by working on real datasets, experimenting with data manipulation and analysis techniques. Engaging in projects or challenges can also reinforce your learning and build your confidence.‎
Typical topics covered in Python Pandas courses include data structures (Series and DataFrames), data manipulation (filtering, sorting, and grouping), data cleaning techniques, merging and joining datasets, and data visualization. Additionally, courses often address time series analysis and handling missing data, which are crucial for effective data analysis. By covering these topics, learners gain a comprehensive understanding of how to work with data using Pandas.‎
For training and upskilling employees or the workforce in Python Pandas, the Data Science Foundations: NumPy, Pandas & Visualization course is an excellent choice. It provides a solid foundation in data analysis techniques and visualization, making it suitable for professionals looking to enhance their data skills. Additionally, the Python and Pandas for Data Engineering course focuses on practical applications in data engineering, which can be beneficial for teams working with large datasets.‎