Pandas Python Library for Beginners in Data Science from Coursera

Note 1: As a beginner you are not yet ready to work with real world data. So real world data is not used in this project.

Note2 : If you are already familiar with pandas and want to work with real world data, check out the intermediate course here: https://www.coursera.org/projects/intermediate-pandas-python-library-data-science

This guided project is for college students or those who have not heard of pandas before and want to learn about the syntax in pandas, one of the most important python libraries for data analysis.

By the end of this project, you will master the basics of pandas. While you are watching me code, you will get a cloud desktop with all the required software pre-installed. This will allow you to code along with me. After all, we learn best with active, hands-on learning.

Special Features:

1) This project provides plenty of challenges with solutions to encourage you to practice using pandas.

2) Libraries are automatically imported each time you begin a new session. Just open the project and start learning!

3) The real world applications of each function is explained.

4) After you complete this project, you get a jupyter notebook of all the work you covered (including gifs). It acts as a useful learning tool that you can refer to at any time in the future.

5) Best practices and tips are provided to ensure that you learn how to use pandas efficiently.

6) Animated gifs are used to aid in the learning process.

7) Important terminology and definitions are explained.

8) Simple language is used throughout the project, so that you can focus on coding. (Eg: Quantitative data is referred to simply as numeric data.)

Note: This course works best for learners who are based in the North America region. We’re currently working on providing the same experience in other regions.

What's inside

Syllabus

Project Overview

By the end of this project, you will master the basics of Pandas. You will be able to gain insight into the data, clean it, and do basic pre-processing to get the most value out of your data. Plenty of challenges are provided along the way to ensure you get lots of practice. Note: Ensure that you read the " Additional Information & Summary" module before attempting the quiz.

Good to know

Know what's good

, what to watch for

, and possible dealbreakers

Intended for learners taking their first steps with a prominent data science library

Meant for learners who are unfamiliar with pandas

Not suitable for beginners who want to work with real-world data

Provides an intermediate course for learners who are already familiar with pandas and want to work with real-world data

Provides exercises with solutions to encourage practice

Offers a notebook of covered work for future reference

Reviews summary

Pandas library for beginners

Learners say Pandas Python Library for Beginners in Data Science is a guided project course that provides a basic introduction to the Pandas library. While the interface is somewhat clunky and some learners felt the course was too easy, clear instruction, step-by-step guidance, and challenge questions help beginners grasp basic functions. The course is particularly well-suited for those with a Python foundation. Topics include methods, functions, data frames, and series.

Best for beginners with little to no Pandas experience.

"Good for complete beginners"

"Perfect beginner course to try hands on and get started with pandas"

"Great start for learning basic pandas functions"

The guided project makes learning easier.

"such a great guided project."

"Wonderful learning in coursera guided projects."

"Absolute , Beginner friendly Guided Project ."

Some Python experience is recommended.

"Prerequisites: Python, Basic Statistics."

"For a student who does not already understand data analysis I would not recommend this course as it doesn't explain or give any examples of what a real dataframe is used for"

Content is very basic and may be too simple for some learners.

"Too basic, nothing new to learn"

"This course showed only a selection of Pandas functions, without linking them to what a person would actually do with them"

"I wish there has been an introduction WHY we use Pandas and what for, I feel like that part is missing"

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 Pandas Python Library for Beginners in Data Science with these activities:

Review Python syntax before getting started

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Review of the syntax and basic concepts of Python, the language of the Pandas library, will help you maximize your learning intake.

Browse courses on Python Syntax

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Read through the Python intro slides from module 1.
Review sample Python programs and their functionalities.
If possible, try running through some sample Python programs on your own.

Read the Pandas Cookbook

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The Pandas Cookbook provides a collection of ready-to-use recipes for working with Pandas.

View Python for Data Analysis: Data Wrangling with... on Amazon

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Find a copy of the Pandas Cookbook online or in a library.
Read the book cover-to-cover.
Try out the recipes in the book.

Review basic Python skills

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Knowing the basics of Python is extremely important before starting to learn Pandas.

Browse courses on Python

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Review the basics of Python online or in a book.
Try out some basic Python exercises.

12 other activities

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Follow a tutorial on Pandas

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Tutorials provide a structured way to learn about Pandas and its features.

Browse courses on Pandas

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Find a tutorial on Pandas that is appropriate for your level of experience.
Follow the steps in the tutorial.
Try out the examples in the tutorial.

Do practice problems for Pandas

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Practice problems will reinforce your understanding of Pandas syntax and help you become more proficient in using it.

Browse courses on Pandas

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Find a set of practice problems online or in a textbook.
Work through the problems, using the Pandas documentation as needed.
Check your answers against the provided solutions.

Join a study group for Pandas

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Study groups provide a supportive environment to learn about Pandas and ask questions.

Browse courses on Pandas

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Find a study group for Pandas online or in your local area.
Attend the study group meetings regularly.
Participate in the discussions and ask questions.

Attend a Pandas workshop

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Workshops provide a structured opportunity to work on Pandas projects with guidance from experts.

Browse courses on Pandas

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Find a Pandas workshop in your local area or online.
Register for the workshop.
Attend the workshop.

Complete coding challenges based on Pandas tutorials

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Hands-on coding challenges will greatly improve your understanding of the concepts you learn in the tutorials.

Browse courses on Pandas

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Go through the coding challenges provided within the tutorials as you progress.
Attempt to solve the coding challenges on your own before checking the provided solutions.
Review the provided solutions to ensure your understanding.

Create a data visualization in Pandas

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Creating a data visualization will help you to understand how to use Pandas to explore and present data.

Browse courses on Data Visualization

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Choose a dataset to visualize.
Load the dataset into Pandas.
Create a data visualization using Pandas.
Interpret the results of your visualization.

Follow a Youtube tutorial on data cleaning using Pandas

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Supplemental tutorials on specific topics can provide additional insights and perspectives, enriching your learning experience.

Browse courses on Pandas

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Search for a tutorial on YouTube or other online platforms.
Choose a tutorial that aligns with your learning needs.
Follow the tutorial step-by-step and apply the concepts to your own data.

Start a Pandas project

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Projects allow you to apply your Pandas skills to real-world problems.

Browse courses on Pandas

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Define the scope of your project.
Gather the necessary data.
Clean and prepare the data.
Analyze the data using Pandas.
Present your results.

Create a cheat sheet summarizing Pandas functions

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Creating a cheat sheet can help reinforce your understanding of Pandas functions and serve as a quick reference.

Browse courses on Pandas

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Review the Pandas documentation and tutorials.
Identify the most important functions and their usage.
Create a cheat sheet that includes the function name, syntax, and a brief description.

Contribute to the Pandas GitHub repository

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Contributing to open source helps you appreciate the practical applications of Pandas.

Browse courses on Pandas

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Find a project on GitHub that you are interested in contributing to.
Fork the project and make changes.
Create a pull request for your changes.

Start a small project that utilizes Pandas for data analysis

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Applying Pandas in a practical project will solidify your understanding and enhance your ability to use it effectively.

Browse courses on Pandas

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Identify a dataset that aligns with your interests.
Develop a research question or hypothesis.
Use Pandas to analyze the data and answer your question or test your hypothesis.
Write a brief report summarizing your findings.

Join a study group focused on Pandas

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Joining a study group can provide support, encourage collaboration, and foster a deeper understanding of Pandas.

Browse courses on Pandas

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Find a study group or organize one with classmates.
Meet regularly to discuss concepts, work on problems, and share insights.
Complete assignments or projects collaboratively.

Career center

Learners who complete Pandas Python Library for Beginners in Data Science will develop knowledge and skills that may be useful to these careers:

Data Scientist

Data Scientists use scientific methods and data analysis techniques to extract knowledge and insights from data. This course can help Data Scientists master the basics of Pandas, a powerful Python library for data analysis. By learning how to use Pandas, Data Scientists can gain insight into their data, clean it more efficiently, and perform basic pre-processing to get the most value out of their data.

See salaries and explore the career path for Data Scientist

Statistical Analyst

Statistical Analysts use statistical methods to collect, analyze, and interpret data. This course can help Statistical Analysts master the basics of Pandas, a powerful Python library for data analysis. By learning how to use Pandas, Statistical Analysts can gain insight into their data, clean it more efficiently, and perform basic pre-processing to get the most value out of their data.

See salaries and explore the career path for Statistical Analyst

Data Analyst

A Data Analyst is responsible for cleaning, processing, and analyzing data to identify trends and patterns. This course can help Data Analysts master the basics of Pandas, a powerful Python library for data analysis. By learning how to use Pandas, Data Analysts can gain insight into their data, clean it more efficiently, and perform basic pre-processing to get the most value out of their data.

See salaries and explore the career path for Data Analyst

Research Analyst

Research Analysts collect, analyze, and interpret data to identify trends and patterns. This course can help Research Analysts master the basics of Pandas, a powerful Python library for data analysis. By learning how to use Pandas, Research Analysts can gain insight into their data, clean it more efficiently, and perform basic pre-processing to get the most value out of their data.

See salaries and explore the career path for Research Analyst

Quantitative Analyst

Quantitative Analysts use mathematical and statistical models to analyze financial data. This course can help Quantitative Analysts master the basics of Pandas, a powerful Python library for data analysis. By learning how to use Pandas, Quantitative Analysts can gain insight into their data, clean it more efficiently, and perform basic pre-processing to get the most value out of their data.

See salaries and explore the career path for Quantitative Analyst

Financial Analyst

Financial Analysts use data analysis techniques to evaluate and make recommendations on investments. This course can help Financial Analysts master the basics of Pandas, a powerful Python library for data analysis. By learning how to use Pandas, Financial Analysts can gain insight into their data, clean it more efficiently, and perform basic pre-processing to get the most value out of their data.

See salaries and explore the career path for Financial Analyst

Business Analyst

Business Analysts use data analysis techniques to identify opportunities and solve problems for businesses. This course can help Business Analysts master the basics of Pandas, a powerful Python library for data analysis. By learning how to use Pandas, Business Analysts can gain insight into their data, clean it more efficiently, and perform basic pre-processing to get the most value out of their data.

See salaries and explore the career path for Business Analyst

Machine Learning Engineer

Machine Learning Engineers design and develop machine learning models to solve real-world problems. This course can help Machine Learning Engineers master the basics of Pandas, a powerful Python library for data analysis. By learning how to use Pandas, Machine Learning Engineers can gain insight into their data, clean it more efficiently, and perform basic pre-processing to get the most value out of their data.

See salaries and explore the career path for Machine Learning Engineer

Actuary

Actuaries use mathematical and statistical models to assess risk and uncertainty. This course can help Actuaries master the basics of Pandas, a powerful Python library for data analysis. By learning how to use Pandas, Actuaries can gain insight into their data, clean it more efficiently, and perform basic pre-processing to get the most value out of their data.

See salaries and explore the career path for Actuary

Data Engineer

Data Engineers design and build data pipelines to store and process data. This course can help Data Engineers master the basics of Pandas, a powerful Python library for data analysis. By learning how to use Pandas, Data Engineers can gain insight into their data, clean it more efficiently, and perform basic pre-processing to get the most value out of their data.

See salaries and explore the career path for Data Engineer

Sales Analyst

Sales Analysts use data analysis techniques to evaluate and make recommendations on sales strategies. This course may be useful for Sales Analysts who want to learn more about the basics of Pandas, a powerful Python library for data analysis. By learning how to use Pandas, Sales Analysts can gain insight into their data, clean it more efficiently, and perform basic pre-processing to get the most value out of their data.

See salaries and explore the career path for Sales Analyst

Software Engineer

Software Engineers design, develop, and maintain software applications. This course may be useful for Software Engineers who want to learn more about data analysis and how to use Pandas, a powerful Python library for data analysis. By learning how to use Pandas, Software Engineers can gain insight into their data, clean it more efficiently, and perform basic pre-processing to get the most value out of their data.

See salaries and explore the career path for Software Engineer

Marketing Analyst

Marketing Analysts use data analysis techniques to evaluate and make recommendations on marketing campaigns. This course may be useful for Marketing Analysts who want to learn more about the basics of Pandas, a powerful Python library for data analysis. By learning how to use Pandas, Marketing Analysts can gain insight into their data, clean it more efficiently, and perform basic pre-processing to get the most value out of their data.

See salaries and explore the career path for Marketing Analyst

Product Manager

Product Managers are responsible for the development and management of products. This course may be useful for Product Managers who want to learn more about data analysis and how to use Pandas, a powerful Python library for data analysis. By learning how to use Pandas, Product Managers can gain insight into their data, clean it more efficiently, and perform basic pre-processing to get the most value out of their data.

See salaries and explore the career path for Product Manager

Data Science Manager

Data Science Managers lead and manage teams of data scientists and analysts. This course may be useful for Data Science Managers who want to learn more about the basics of Pandas, a powerful Python library for data analysis. By learning how to use Pandas, Data Science Managers can gain insight into their data, clean it more efficiently, and perform basic pre-processing to get the most value out of their data.

See salaries and explore the career path for Data Science Manager