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Python Data Science: NumPy

Python Data Science: NumPy

本课程是 Using Data Science Tools in Python 专项课程的一部分

位教师：Bill Rosenthal

包含在中

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3个模块

深入了解一个主题并学习基础知识。

4 小时完成

灵活的计划

自行安排学习进度

3个模块

深入了解一个主题并学习基础知识。

4 小时完成

灵活的计划

自行安排学习进度

您将学到什么

In this course, you will manage and analyze data with NumPy arrays, and manipulate and modify data with NumPy arrays.

您将获得的技能

您将学习的工具

要了解的详细信息

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Petrobras, TATA, Danone, Capgemini, P&G 和 L'Oreal 的徽标

积累特定领域的专业知识

本课程是 Using Data Science Tools in Python 专项课程专项课程的一部分

在注册此课程时，您还会同时注册此专项课程。

向行业专家学习新概念
获得对主题或工具的基础理解
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该课程共有3个模块

In this course, you'll continue developing your data science skills in Python by working with one of the most fundamental data science libraries—NumPy. You'll create NumPy arrays, load and save NumPy data, and analyze data in arrays. You'll also manipulate and modify data in those arrays.

单元详情

The foundation of data science in Python® is NumPy. Most of your work will involve NumPy, whether directly or indirectly. So, you'll leverage the power of this library to manage your data and extract useful insights from that data.

涵盖的内容

1篇阅读材料5个插件

While analyzing data is an important part of the data science process, so is changing that data to meet your needs. Whether it's to prepare and clean the data, or to modify it for easier analysis and presentation, being able to transform your NumPy arrays is crucial.