Pandas Python Library for Beginners in Data Science

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In diesem angeleitetes Projekt werden Sie:

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
CloudKein Download erforderlich
VideoVideo auf geteiltem Bildschirm
Comment DotsEnglisch
LaptopNur Desktop

Note 1: If you are familiar with pandas or you want to work with real world data , check out the intermediate course here: Note 2: 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 3: 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 "Additional features and Summary"provided after the video content. Make sure you read it 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.

Kompetenzen, die Sie erwerben werden

Data ScienceArtificial Intelligence (AI)Python ProgrammingData AnalysisPandas

Schritt für Schritt lernen

In einem Video, das auf einer Hälfte Ihres Arbeitsbereichs abgespielt wird, führt Sie Ihr Dozent durch diese Schritte:

  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.

Ablauf angeleiteter Projekte

Ihr Arbeitsbereich ist ein Cloud-Desktop direkt in Ihrem Browser, kein Download erforderlich

Ihr Dozent leitet Sie in einem Video mit geteiltem Bildschirm Schritt für Schritt an.



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