Python 可以成为数据准备的强大工具。在本课程中，我们将快速介绍如何连接到各种数据库类型。然后，我们将开始使用 pandas Python 包进行数据准备。我们将查看清理缺失和外围数据以及数据可视化和探索的示例。除了 pandas 包，我们还将使用 scikit-learn Python 包查看机器学习的预处理数据。
在开始本课程之前，您应该对 Python 和数据方法有深入的了解。查看介绍部分中的先决条件和相关课程课程作为起点。
MP4 | Video: h264, 1280×720 | Audio: AAC, 44.1 KHz, 2 Ch
Genre: eLearning | Language: English | Duration: 37 Lessons (2h) | Size: 1.28 GB
This course explores the tools available in the Python language for data preparation.
Python can be a powerful tool for data preparation. In this course, we will quickly cover how to connect to various database types. Then, we will jump into using the pandas Python package for data preparation. We will look at examples of cleansing missing and outlying data as well as data visualizations and exploration. In addition to the pandas package, we will also look at preprocessing data for machine learning using the scikit-learn Python package.
Before beginning this course, you should have a strong knowledge of Python and data approaches. Check out the Prerequisite and Related Courses lesson in the Introduction section for a starting point.
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