Name: Pandas for Data Science
Brand: Duke University
Availability: OnlineOnly
Rating: 4.3 (3 reviews)

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学生对 Duke University 提供的 Pandas for Data Science 的评价和反馈

4.3

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课程概述

How can you effectively use Python to clean, sort, and store data? What are the benefits of using the Pandas library for data science? What best practices can data scientists leverage to better work with multiple types of datasets? In the third course of Data Science Python Foundations Specialization from Duke University, Python users will learn about how Pandas — a common library in Python used for data science — can ease their workflow. We recommend you should take this course after the first two courses of the specialization. However, if you hold a prerequisite knowledge of basic algebra, Python programming, and NumPy, you should be able to complete the material in this course. In the first week, we’ll discuss Python file concepts, including the programming syntax that allows you to read and write to a file. Then in the following weeks, we’ll transition into discussing Pandas more specifically and the pros and cons of using this library for specific data projects. By the end of this course, you should be able to know when to use Pandas, how to load and clean data in Pandas, and how to use Pandas for data manipulation. This will prepare you to take the next step in your data scientist journey using Python; creating larger software programs....

1 - Pandas for Data Science 的 4 个评论（共 4 个）

创建者 Jenn Q

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Jul 31, 2024

It's quite helpful in starting to use pandas and to get an idea of data projects. I really enjoy the project assignments. The only thing that I wish to be improved is the instruction of the Module 4 assignment, as it's similar to previous assignments. The instruction and entire assignment can be made better.

创建者 Dan C

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Aug 10, 2024

Another great course in this series. It is the best so far, with a strong emphasis on Pandas and using it for data exploration. I found the live coding tutorials and the assignments to be very well structured and relevant. I feel I have learned a lot in this course. Looking forward to the next courses!