vjigg · 05-Май-22 07:14(2 года 8 месяцев назад, ред. 26-Дек-22 01:48)
Pandas Fundamentals ► Advanced Pandas Год выпуска: 2018 Производитель: Pluralsight Сайт производителя://app.pluralsight.com/profile/author/pawel-kordek Автор: Paweł Kordek Продолжительность: 3h 50m Тип раздаваемого материала: Видеоурок Язык: Английский Описание:
Quick and expressive data analysis requires good tools and knowledge of them. In this course, you'll explore the world of data science by learning core Pandas functionalities, including its IO capabilities, plotting methods, and DataFrames. As an individual working with data, from business analysts to data scientists, you desire a quick feedback loop that enables you to materialize and easily visualize your ideas. Time spent on developing and debugging programs or clicking around spreadsheets is often wasted. In this course, Pandas Fundamentals, you'll learn how to quickly read the data, perform desired analysis, and output it in a neat format along with pleasant plots. First, you'll explore data input and output. Next, you'll discover how to index and filter your data. Finally, you'll delve into how to work with groups, along with creating plots. After finishing this course, you'll have the necessary knowledge to manipulate data in basic forms, and be able to utilize your time more efficiently when figuring out how to transform your data to reach the desired effect. Software required: Anaconda Python.Learn to handle complex data-sets and analyze your data in a principled way with Pandas. This course will teach you advanced parts of this library, including handling higher-dimensional data, time series, window operations, joins, and plotting. At the core of practicing effective data science is a thorough knowledge of data analysis tools, and among them, Pandas is one of the most popular. In this course, Advanced Pandas, you will learn the skills you need to perform data analysis that is effective and full of useful insights. First, you will learn how to prepare your dataset for a smoother experience. Next, you will discover how to perform database-style joins, work with higher-dimensional data, analyze time series, and apply window operations. Finally, you will explore how to present the data by generating informative and appealing plots. When you’re finished with this course, you will have an advanced understanding of the Pandas library and the knowledge that will help you as you move forward and grow as a professional data scientist or analyst. Related Topics:
Pandas Playbook Building Image Processing Applications Using scikit-image Building Data Visualizations Using Matplotlib Working with Multidimensional Data Using NumPy Interpreting Data with Python | Path Building Machine Learning Solutions with scikit-learn | Path Machine Learning Literacy — Practical Application | Path Machine Learning Literacy | Path Deep Learning Literacy — Practical Application | Path Deep Learning Literacy | Path Feature Engineering | Path Data Analytics Literacy ► Data Science Literacy | Path Python for Data Analysts | Path Core Python | Path
Содержание
Pandas Fundamentals (Paweł Kordek, 2017)1. Course Overview
2. Getting Started
3. Exploring Pandas Data Input Capabilities
4. Indexing and Filtering
5. Operations on Groups
6. Outputting Data
7. Plotting Advanced Pandas (Paweł Kordek, 2018)1. Course Overview
2. Overview
3. Preparing Your Dataset
4. Joining Multiple Data Tables
5. Moving Between Long and Wide Data Formats
6. Multi-level Indexes
7. Handling Time Series
8. Getting More Insights into Your Data with Windows
9. Plotting and Presenting Your Data
