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    • Python Pandas

    Python Pandas Courses Online

    Learn Pandas for data manipulation in Python. Understand how to use Pandas for data cleaning, transformation, and analysis.

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    Explore the Python Pandas Course Catalog

    • C

      Coursera Project Network

      Data Visualization & Storytelling in Python

      Skills you'll gain: Data Storytelling, Plotly, Data Presentation, Matplotlib, Interactive Data Visualization, Seaborn, Data Visualization, Data Visualization Software, Statistical Visualization, Scatter Plots

      Beginner · Guided Project · Less Than 2 Hours

    • P

      Pontificia Universidad Católica de Chile

      Python para Ciencia de Datos

      Skills you'll gain: Descriptive Analytics, Data-Driven Decision-Making, Data Analysis, Data Visualization Software, Predictive Analytics, Business Analytics, Database Management, Data Science, Relational Databases, Data Processing, Forecasting, Data Manipulation, Python Programming

      Build toward a degree

      3.8
      Rating, 3.8 out of 5 stars
      ·
      63 reviews

      Beginner · Course · 1 - 4 Weeks

    • U

      University of California San Diego

      Big Data Integration and Processing

      Skills you'll gain: Apache Spark, PySpark, Apache Hadoop, Data Integration, Big Data, Data Pipelines, Data Processing, Data Management, NoSQL, Analytics, Splunk, Database Systems, MongoDB, Pandas (Python Package), SQL

      4.4
      Rating, 4.4 out of 5 stars
      ·
      2.4K reviews

      Beginner · Course · 1 - 3 Months

    • U

      University of Michigan

      Design Computing: 3D Modeling in Rhinoceros with Python/Rhinoscript

      Skills you'll gain: Data Structures, 3D Modeling, Computational Logic, Computer Graphics, Visualization (Computer Graphics), Design, Digital Design, Python Programming, Scripting, Computer Programming

      4.9
      Rating, 4.9 out of 5 stars
      ·
      98 reviews

      Beginner · Course · 1 - 3 Months

    • D

      Duke University

      Scripting with Python and SQL for Data Engineering

      Skills you'll gain: Web Scraping, MySQL, SQL, JSON, Scripting, Data Manipulation, Data Structures, Database Software, Database Management, Databases, Data Import/Export, Data Storage Technologies, Spatial Analysis, Python Programming

      4.4
      Rating, 4.4 out of 5 stars
      ·
      100 reviews

      Intermediate · Course · 1 - 4 Weeks

    • G

      Google

      Regression Analysis: Simplify Complex Data Relationships

      Skills you'll gain: Regression Analysis, Statistical Analysis, Advanced Analytics, Correlation Analysis, Analytics, Data Analysis, Statistical Methods, Predictive Modeling, Statistical Modeling, Supervised Learning, Statistics, Statistical Machine Learning, Variance Analysis, Machine Learning Methods, Python Programming

      4.7
      Rating, 4.7 out of 5 stars
      ·
      497 reviews

      Advanced · Course · 1 - 3 Months

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      U

      University of California San Diego

      Combinatorics and Probability

      Skills you'll gain: Combinatorics, Probability, Algorithms, Mathematical Modeling, Statistics, Applied Mathematics, Python Programming, Simulations

      4.6
      Rating, 4.6 out of 5 stars
      ·
      861 reviews

      Beginner · Course · 1 - 3 Months

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      É

      École Polytechnique Fédérale de Lausanne

      Big Data Analysis with Scala and Spark

      Skills you'll gain: Apache Spark, Apache Hadoop, Scala Programming, Distributed Computing, Big Data, Data Manipulation, Data Processing, Performance Tuning, Data Analysis

      4.6
      Rating, 4.6 out of 5 stars
      ·
      2.6K reviews

      Intermediate · Course · 1 - 4 Weeks

    • Placeholder
      U

      University of Toronto

      Visual Perception for Self-Driving Cars

      Skills you'll gain: Computer Vision, Image Analysis, Deep Learning, Artificial Neural Networks, Visualization (Computer Graphics), Artificial Intelligence, Machine Learning, Python Programming, NumPy, Linear Algebra

      4.7
      Rating, 4.7 out of 5 stars
      ·
      577 reviews

      Advanced · Course · 1 - 3 Months

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      U

      University of California San Diego

      Bioinformatics

      Skills you'll gain: Bioinformatics, Dimensionality Reduction, Unsupervised Learning, Data Analysis, Markov Model, Life Sciences, Infectious Diseases, Statistical Analysis, Medical Science and Research, Big Data, Computational Logic, Computer Programming Tools, Machine Learning, Machine Learning Methods, Computational Thinking, Graph Theory, Analysis, Taxonomy, Tree Maps, Scientific Methods

      4.3
      Rating, 4.3 out of 5 stars
      ·
      1.2K reviews

      Beginner · Specialization · 3 - 6 Months

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      A

      Arizona State University

      Python: A Guided Journey from Introduction to Application

      Skills you'll gain: Supervised Learning, Unsupervised Learning, Matplotlib, Generative AI, NumPy, Object Oriented Programming (OOP), Deep Learning, Image Analysis, Plot (Graphics), Machine Learning Algorithms, Object Oriented Design, Integrated Development Environments, Pandas (Python Package), Development Environment, Data Structures, Event-Driven Programming, Python Programming, Programming Principles, Scripting, User Interface (UI)

      4
      Rating, 4 out of 5 stars
      ·
      50 reviews

      Beginner · Specialization · 3 - 6 Months

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      N

      New York Institute of Finance

      Using Machine Learning in Trading and Finance

      Skills you'll gain: Tensorflow, Keras (Neural Network Library), Financial Trading, Data Pipelines, Applied Machine Learning, Technical Analysis, Machine Learning, Statistical Machine Learning, Artificial Intelligence and Machine Learning (AI/ML), Market Data, Financial Market, Time Series Analysis and Forecasting

      3.9
      Rating, 3.9 out of 5 stars
      ·
      369 reviews

      Intermediate · Course · 1 - 3 Months

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    In summary, here are 10 of our most popular python pandas courses

    • Data Visualization & Storytelling in Python: Coursera Project Network
    • Python para Ciencia de Datos: Pontificia Universidad Católica de Chile
    • Big Data Integration and Processing: University of California San Diego
    • Design Computing: 3D Modeling in Rhinoceros with Python/Rhinoscript: University of Michigan
    • Scripting with Python and SQL for Data Engineering: Duke University
    • Regression Analysis: Simplify Complex Data Relationships: Google
    • Combinatorics and Probability: University of California San Diego
    • Big Data Analysis with Scala and Spark: École Polytechnique Fédérale de Lausanne
    • Visual Perception for Self-Driving Cars: University of Toronto
    • Bioinformatics: University of California San Diego

    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 software library for data analysis that is used with the open source Python programming language. By loading data sets into a Pandas DataFrame, a user can manipulate, analyze, and visualize that data for exploratory data analysis. Python Pandas is important to learn about because its flexibility, speed, and power in data processing makes it one of the most widely used Python libraries in data science.

    Pandas is built on the NumPy package, which is the numerical Python library for scientific computing, arrays, and linear algebra. As an example, if you wanted to predict an economic trend with a statistical model, Pandas could be used to import your data set, NumPy machine learning (ML) algorithms could perform the linear regression, and the data visualization library Matplotlib could be used to create your plots and charts. For unstructured data analysis, you could use NLTK (Natural Language Toolkit) to perform text mining for business intelligence applications.‎

    Python Pandas skills have many applications in the real world, as data science is increasingly applied to everything from economics and statistics to neuroscience and advertising. Data scientists are responsible for analyzing massive datasets, designing machine learning algorithms and predictive models, and helping management harness these data-driven insights to answer important business questions.

    Although they often need to be familiar with many data frameworks and programming languages, many data scientists rely on Pandas, NumPy, and other Python programming skills as a foundation for their exploratory data analysis. According to Glassdoor, the national average salary for a data scientist is $113,309 per year.‎

    Yes! Coursera offers a wide range of online courses, Specializations, and professional certificates in data science, including courses that teach the use of Python Pandas for data processing, data analytics, and data visualizations. You can take courses from top-ranked institutions like the University of Michigan as well as industry-leading organizations like IBM, so you can rest assured you’ll get a high-quality education. Coursera’s Guided Projects also allow you to build these skills by completing hands-on tutorials with expert instructors in topics like linear regression and data processing with Python, giving you another way to learn online.‎

    It's necessary to have basic computer skills including how to navigate a cloud desktop and install a computer program before starting to learn Python pandas. It's possible to start learning pandas without any prior knowledge of coding or Python, but having these skills will make learning pandas easier. It's also helpful to have good problem-solving skills, experience organizing and analyzing data, and basic math skills. Experience with statistics can also be helpful but not required. And having prior experience using Jupyter Notebook can also be helpful since you'll likely use it to store and access code as you learn Python pandas.‎

    People who enjoy working with data or coding are well suited for roles in Python pandas, as are people who are analytical thinkers. Important soft skills for someone in a role that uses Python panda include good communication skills, both written and verbal as well as with visualization software; problem-solving skills to troubleshoot technical problems or data errors and collaborate with team members to solve a project issue; and attention to detail to pick out small clues that help draw meaningful conclusions from data.‎

    Learning Python pandas is likely right for you if you plan to enter or are already in the data science field, particularly in roles that require data analysis or software development. You can approach learning pandas in one of two ways: either learning how to access the pandas library without conducting data analysis or using pandas while conducting data analysis. The former is more basic and is for you if want to learn how to clean data, do basic data preprocessing, and handle numeric and text data with pandas. The latter is for you if you are learning data analysis and want to apply real-world exploratory data analysis techniques to advance your knowledge and skills.‎

    Online Python Pandas courses offer a convenient and flexible way to enhance your knowledge or learn new Python Pandas skills. Choose from a wide range of Python Pandas courses offered by top universities and industry leaders tailored to various skill levels.‎

    When looking to enhance your workforce's skills in Python Pandas, it's crucial to select a course that aligns with their current abilities and learning objectives. Our Skills Dashboard is an invaluable tool for identifying skill gaps and choosing the most appropriate course for effective upskilling. For a comprehensive understanding of how our courses can benefit your employees, explore the enterprise solutions we offer. Discover more about our tailored programs at Coursera for Business here.‎

    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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