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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

    • Status: [object Object]
      AI skills
      M

      Meta

      Meta Marketing Analytics

      Skills you'll gain: Data Storytelling, Business Metrics, Key Performance Indicators (KPIs), Marketing Analytics, Bayesian Statistics, Descriptive Statistics, Marketing Effectiveness, Statistical Hypothesis Testing, Target Audience, Marketing Strategies, Data Cleansing, Pandas (Python Package), Data Modeling, Data Analysis, Data Visualization Software, Spreadsheet Software, A/B Testing, Data Collection, Marketing, Interviewing Skills

      4.7
      Rating, 4.7 out of 5 stars
      ·
      3.6K reviews

      Beginner · Professional Certificate · 3 - 6 Months

    • C

      Coursera Project Network

      Create Your First Web App with Python and Flask

      Skills you'll gain: Flask (Web Framework), Web Development, Web Applications, Web Development Tools, Object-Relational Mapping, Database Application, Back-End Web Development, Python Programming

      4.5
      Rating, 4.5 out of 5 stars
      ·
      541 reviews

      Intermediate · Guided Project · Less Than 2 Hours

    • J

      Johns Hopkins University

      Genomic Data Science

      Skills you'll gain: Bioinformatics, Unix Commands, Biostatistics, Exploratory Data Analysis, Statistical Analysis, Unix, Data Science, Data Management, Statistical Methods, Command-Line Interface, Statistical Hypothesis Testing, Linux Commands, Science and Research, Statistical Modeling, Data Structures, Data Analysis, R Programming, Computational Thinking, Statistical Programming, Jupyter

      4.5
      Rating, 4.5 out of 5 stars
      ·
      6.6K reviews

      Intermediate · Specialization · 3 - 6 Months

    • U

      University of Colorado Boulder

      BiteSize Python for Intermediate Learners

      Skills you'll gain: Matplotlib, Object Oriented Programming (OOP), Plotly, Seaborn, Data Visualization Software, Object Oriented Design, Pandas (Python Package), NumPy, Statistical Visualization, Interactive Data Visualization, Data Presentation, Data Storytelling, Software Documentation, Data Structures, Maintainability, Programming Principles, Software Design, Data Import/Export, Data Manipulation, Data Cleansing

      Intermediate · Specialization · 3 - 6 Months

    • I

      Imperial College London

      Mathematics for Machine Learning: PCA

      Skills you'll gain: Dimensionality Reduction, NumPy, Probability & Statistics, Jupyter, Statistics, Geometry, Linear Algebra, Data Transformation, Python Programming, Advanced Mathematics, Machine Learning, Machine Learning Algorithms, Calculus

      4
      Rating, 4 out of 5 stars
      ·
      3.1K reviews

      Intermediate · Course · 1 - 4 Weeks

    • U

      University of Washington

      Machine Learning: Regression

      Skills you'll gain: Regression Analysis, Predictive Modeling, Supervised Learning, Statistical Modeling, Applied Machine Learning, Machine Learning Algorithms, Feature Engineering, Machine Learning, Statistical Methods, Dimensionality Reduction, Python Programming, Data Validation

      4.8
      Rating, 4.8 out of 5 stars
      ·
      5.6K reviews

      Mixed · Course · 1 - 3 Months

    • Placeholder
      D

      DeepLearning.AI

      AI Python for Beginners

      Skills you'll gain: Artificial Intelligence, Jupyter, Python Programming, Data Analysis, OpenAI, Application Development, Generative AI, Scripting, Automation, Computer Programming, Application Programming Interface (API), Development Environment, Debugging, Data Structures

      4.8
      Rating, 4.8 out of 5 stars
      ·
      60 reviews

      Beginner · Course · 1 - 4 Weeks

    • Placeholder
      I

      IBM

      IBM Data Analyst Capstone Project

      Skills you'll gain: Dashboard, Exploratory Data Analysis, Data Wrangling, Statistical Analysis, Data Cleansing, IBM Cognos Analytics, Data Collection, Data Analysis, Looker (Software), Web Scraping, Data Storytelling, Data Transformation, Box Plots, Pandas (Python Package), Scatter Plots, Histogram

      4.7
      Rating, 4.7 out of 5 stars
      ·
      1.2K reviews

      Advanced · Course · 1 - 3 Months

    • Placeholder
      Status: Free
      Free
      U

      University of California San Diego

      Biology Meets Programming: Bioinformatics for Beginners

      Skills you'll gain: Bioinformatics, Programming Principles, Computational Thinking, Analysis

      4.2
      Rating, 4.2 out of 5 stars
      ·
      1.6K reviews

      Beginner · Course · 1 - 4 Weeks

    • Placeholder
      C

      Codio

      Programming in Python: A Hands-on Introduction

      Skills you'll gain: Object Oriented Programming (OOP), Programming Principles, Computer Programming, Scripting Languages, Data Import/Export, Data Structures, Python Programming, Software Design Patterns, Scripting, Computational Logic, Computer Science, File Management

      4.5
      Rating, 4.5 out of 5 stars
      ·
      420 reviews

      Beginner · Specialization · 3 - 6 Months

    • Placeholder
      U

      University of Michigan

      Fitting Statistical Models to Data with Python

      Skills you'll gain: Statistical Modeling, Statistical Methods, Bayesian Statistics, Statistical Inference, Statistical Software, Statistical Analysis, Statistical Programming, Regression Analysis, Predictive Modeling, Data Analysis, Exploratory Data Analysis, Data Manipulation

      4.4
      Rating, 4.4 out of 5 stars
      ·
      696 reviews

      Intermediate · Course · 1 - 4 Weeks

    • Placeholder
      U

      Universidad Austral

      Estructuras de datos en Python

      Skills you'll gain: Data Structures, Python Programming, JSON, File Management, Scripting, Scripting Languages, Data Import/Export, Debugging

      4.6
      Rating, 4.6 out of 5 stars
      ·
      407 reviews

      Beginner · Course · 1 - 4 Weeks

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

    • Meta Marketing Analytics: Meta
    • Create Your First Web App with Python and Flask: Coursera Project Network
    • Genomic Data Science: Johns Hopkins University
    • BiteSize Python for Intermediate Learners: University of Colorado Boulder
    • Mathematics for Machine Learning: PCA: Imperial College London
    • Machine Learning: Regression: University of Washington
    • AI Python for Beginners: DeepLearning.AI
    • IBM Data Analyst Capstone Project: IBM
    • Biology Meets Programming: Bioinformatics for Beginners: University of California San Diego
    • Programming in Python: A Hands-on Introduction: Codio

    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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