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  2. Python Pandas

Python Pandas Courses

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.

Popular Python Pandas Courses and Certifications


  • I

    IBM

    Python for Data Science, AI & Development

    Skills you'll gain: Data Import/Export, Python Programming, NumPy, Scripting, Data Collection, Data Analysis

    4.6 stars, 44K reviews, Beginner, Course, 1 - 3 Months

    ★ 4.6 (44K) · Beginner · Course · 1 - 3 Months

    Status: Free trial
    Free trial
  • I

    IBM

    Data Analysis with Python

    Skills you'll gain: Data Wrangling, Exploratory Data Analysis, Model Evaluation, Data Cleansing, Data Preprocessing, Data Manipulation, Data Analysis, Data Processing, Model Training, Scatter Plots, Statistical Analysis, Predictive Modeling, Regression Analysis, Statistical Methods, Data Transformation, Feature Engineering, Data Import/Export, Scientific Visualization, Data Visualization, Python Programming

    4.7 stars, 20K reviews, Intermediate, Course, 1 - 3 Months

    ★ 4.7 (20K) · Intermediate · Course · 1 - 3 Months

    Status: Free trial
    Free trial
  • M

    Madecraft

    Python Functions for Data Science

    Skills you'll gain: NumPy, Matplotlib, Pandas (Python Package), Plot (Graphics), Seaborn, Data Visualization, Jupyter, Data Science, Statistical Visualization, Data Visualization Software, Statistical Analysis, Data Wrangling, Data Manipulation, Data Analysis, Scatter Plots, Exploratory Data Analysis, Statistical Programming, Python Programming, Data Transformation, Data Processing

    Intermediate · Course · 1 - 3 Months

    Category: New
    New
    Status: Free trial
    Free trial
  • G

    Google

    Google Data Analysis with Python

    Skills you'll gain: Pandas (Python Package), NumPy, Data Manipulation, Code Reusability, Data Preprocessing, Data Wrangling, Package and Software Management, Data Analysis, Data Processing, Data Integration, JSON, Object Oriented Programming (OOP), Data Science, Data Structures, Python Programming, Exploratory Data Analysis, Programming Principles, Data Import/Export, Data Storage, Computational Logic

    4.7 stars, 201 reviews, Beginner, Specialization, 3 - 6 Months

    ★ 4.7 (201) · Beginner · Specialization · 3 - 6 Months

    Category: Bestseller
    Bestseller
    Status: Free trial
    Free trial
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  • P

    Packt

    Data Analysis with Pandas and Python

    Skills you'll gain: Pandas (Python Package), Data Import/Export, Matplotlib, Plot (Graphics), Pivot Tables And Charts, Jupyter, Data Visualization Software, Microsoft Excel, Data Analysis, Spreadsheet Software, Text Mining, Data Wrangling, Data Manipulation, Data Cleansing, Data Presentation, Data Processing, Data Integration, Programming Principles, Graphing, Time Series Analysis and Forecasting

    4.6 stars, 43 reviews, Intermediate, Specialization, 3 - 6 Months

    ★ 4.6 (43) · Intermediate · Specialization · 3 - 6 Months

    Status: Free trial
    Free trial
  • What brings you to Coursera today?

  • C

    Coursera

    Python for Data Analysis: Pandas & NumPy

    Skills you'll gain: Pandas (Python Package), NumPy, Data Analysis, Data Science, Python Programming, Data Structures, Data Manipulation, Analysis

    4.5 stars, 393 reviews, Beginner, Guided Project, Less Than 2 Hours

    ★ 4.5 (393) · Beginner · Guided Project · Less Than 2 Hours

  • D

    Duke University

    Pandas for Data Science

    Skills you'll gain: Pandas (Python Package), Data Cleansing, Data Manipulation, Data Preprocessing, Data Wrangling, NumPy, File I/O, Query Languages, Data Transformation, Data Integration, Python Programming, Data Analysis, Debugging

    4.3 stars, 16 reviews, Beginner, Course, 1 - 4 Weeks

    ★ 4.3 (16) · Beginner · Course · 1 - 4 Weeks

    Status: Free trial
    Free trial
  • U

    University of Michigan

    NumPy and Pandas Basics for Future Data Scientists

    Skills you'll gain: Debugging, Data Analysis, Data Preprocessing, Numerical Analysis, Critical Thinking

    4.2 stars, 14 reviews, Intermediate, Course, 1 - 4 Weeks

    ★ 4.2 (14) · Intermediate · Course · 1 - 4 Weeks

    Status: Free trial
    Free trial
  • L

    Logical Operations

    Python Data Science: pandas, Matplotlib, and Seaborn

    Skills you'll gain: Seaborn, Matplotlib, Data Transformation, Plot (Graphics), Pandas (Python Package), Data Manipulation, Data Visualization Software, NumPy, Data Visualization, Data Analysis, Scatter Plots, Data Science, Jupyter, Graphing, Data Processing, Box Plots, Python Programming, Computer Programming, Computer Programming Tools, Software Development

    Mixed · Course · 1 - 4 Weeks

    Status: Free trial
    Free trial
  • J

    JetBrains

    Python: Mastering Pandas Essentials

    Skills you'll gain: Pandas (Python Package), Exploratory Data Analysis, Data Manipulation, Data Transformation, Data Visualization, Data Wrangling, Pivot Tables And Charts, Data Analysis, Statistical Visualization, Data Import/Export, Data Cleansing, Data Processing, Data Preprocessing, Data Structures, Python Programming, Analysis, Data Management, Integrated Development Environments, Back-End Web Development, Software Development

    4.9 stars, 193 reviews, Intermediate, Course, 1 - 3 Months

    ★ 4.9 (193) · Intermediate · Course · 1 - 3 Months

    Category: New
    New
    Status: Free trial
    Free trial
  • M

    Microsoft

    Microsoft Python Development

    Skills you'll gain: Web Scraping, Git (Version Control System), Data Structures, GitHub, Generative AI, Matplotlib, Data Visualization, Web Development, Version Control, Debugging, Data Literacy, Scripting, Flask (Web Framework), Plotly, Data Ethics, Containerization, DevOps, Automation, Data Analysis, Cloud Computing

    4.4 stars, 773 reviews, Beginner, Professional Certificate, 3 - 6 Months

    ★ 4.4 (773) · Beginner · Professional Certificate · 3 - 6 Months

    Category: Job ready
    Job ready
    Status: Free trial
    Free trial
  • C

    Coursera

    Mastering Data Analysis with Pandas

    Skills you'll gain: Pandas (Python Package), Data Analysis, Data Manipulation, Python Programming

    4.6 stars, 182 reviews, Beginner, Guided Project, Less Than 2 Hours

    ★ 4.6 (182) · Beginner · Guided Project · Less Than 2 Hours

1234…180

Best Python Pandas courses from IBM

Top-rated Python Pandas courses offered by IBM on Coursera.

  1. 1
    Python for Data Science, AI & Development
    IBMBeginner1 - 3 Months4.6(43,834)IBM
  2. 2
    Data Analysis with Python
    IBMIntermediate1 - 3 Months4.7(19,798)IBM

Best Python Pandas certificate programs

Earn a certificate in Python Pandas from top universities and companies.

  1. 1
    Google Data Analysis with Python
    GoogleBeginner3 - 6 Months4.7(201)Specialization
  2. 2
    Data Analysis with Pandas and Python
    PacktIntermediate3 - 6 Months4.6(43)Specialization
  3. 3
    Microsoft Python Development
    MicrosoftBeginner3 - 6 Months4.4(773)Professional Certificate

Best Python Pandas courses for beginners

Top-rated beginner-friendly Python Pandas courses with no prerequisites.

  1. 1
    Python for Data Analysis: Pandas & NumPy
    CourseraBeginnerLess Than 2 Hours4.5(393)No prerequisites
  2. 2
    Pandas for Data Science
    Duke UniversityBeginner1 - 4 Weeks4.3(16)No prerequisites
  3. 3
    Mastering Data Analysis with Pandas
    CourseraBeginnerLess Than 2 Hours4.6(182)No prerequisites

Skills you can learn in Data Analysis

Analytics (85)
Big Data (64)
Python Programming (47)
Business Analytics (40)
R Programming (37)
Statistical Analysis (36)
Sql (33)
Data Model (29)
Data Mining (27)
Exploratory Data Analysis (26)
Data Modeling (21)
Data Manipulation (20)

Frequently Asked Questions about Python Pandas

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:

  1. Preview the first module of many python pandas courses at no cost. This includes video lessons, readings, graded assignments, and Coursera Coach (where available).
  2. Start a 7-day free trial for Specializations or Coursera Plus. This gives you full access to all course content across eligible programs within the timeframe of your trial.

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.‎

This FAQ content has been made available for informational purposes only. Learners are advised to conduct additional research to ensure that courses and other credentials pursued meet their personal, professional, and financial goals.

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