Pandas Python Library for Beginners in Data Science

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In this Guided Project, you will:

Learn how to clean data using pandas.

Learn how to do basic data preprocessing.

Learn how to handle quantitative data (numeric data) and qualitative data (text data) with pandas.

Clock1 hour
BeginnerBeginner
CloudNo download needed
VideoSplit-screen video
Comment DotsEnglish
LaptopDesktop only

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 Note 3: Pandas is not used for development. It was designed purely for data manipulation. So you will not build anything during the course of this project. Note 4: The video content is meant to be within an hour as per Coursera's guidlines. It is meant to demonstrate coding. The theory is covered in detail in the reading module titled "Project Summary"provided after the video content. Note 5: Make sure you read the "Project Summary" before attempting the final quiz. 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. You will be able to gain insight into the data, clean it, and do basic preprocessing to get the most value out of your data. 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.

Skills you will develop

Data ScienceArtificial Intelligence (AI)Python ProgrammingData AnalysisPandas

Learn step-by-step

In a video that plays in a split-screen with your work area, your instructor will walk you through these steps:

  1. Three methods of creating a series.

  2. Two methods of creating data frames.

  3. Importing/exporting different types of data files and viewing rows.

  4. Get a summary of the data & view column names and data types.

  5. Calculate mean & cumulative sum. Determine minimum & maximum values.

  6. String operations such as converting to uppercase letters , lowercase letters, swap case, finding the length of a string, splitting strings and detecting unique values.

  7. Repeating strings.

How Guided Projects work

Your workspace is a cloud desktop right in your browser, no download required

In a split-screen video, your instructor guides you step-by-step

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Frequently asked questions

Frequently Asked Questions

More questions? Visit the Learner Help Center.