Sign In Start Free Trial
Account

Add to playlist

Create a Playlist

Modal Close icon
You need to login to use this feature.
  • The Pandas Workshop
  • Toc
  • feedback
The Pandas Workshop

The Pandas Workshop

By : Blaine Bateman, Saikat Basak , Thomas Joseph, William So
4.8 (16)
close
The Pandas Workshop

The Pandas Workshop

4.8 (16)
By: Blaine Bateman, Saikat Basak , Thomas Joseph, William So

Overview of this book

The Pandas Workshop will teach you how to be more productive with data and generate real business insights to inform your decision-making. You will be guided through real-world data science problems and shown how to apply key techniques in the context of realistic examples and exercises. Engaging activities will then challenge you to apply your new skills in a way that prepares you for real data science projects. You’ll see how experienced data scientists tackle a wide range of problems using data analysis with pandas. Unlike other Python books, which focus on theory and spend too long on dry, technical explanations, this workshop is designed to quickly get you to write clean code and build your understanding through hands-on practice. As you work through this Python pandas book, you’ll tackle various real-world scenarios, such as using an air quality dataset to understand the pattern of nitrogen dioxide emissions in a city, as well as analyzing transportation data to improve bus transportation services. By the end of this data analytics book, you’ll have the knowledge, skills, and confidence you need to solve your own challenging data science problems with pandas.
Table of Contents (21 chapters)
close
1
Part 1 – Introduction to pandas
6
Part 2 – Working with Data
11
Part 3 – Data Modeling
15
Part 4 – Additional Use Cases for pandas

Chapter 12: Using Time in pandas

In this chapter, you will focus entirely on one kind of data that is, on one hand, quite common in data analysis but, on the other hand, requires a number of special considerations – time series. pandas provides many methods specifically for working with time series. Here, you will learn about time-aware data types (such as datetime and Timedelta). In Chapter 13, Exploring Time Series, you will learn how to use these in the index to enable advanced capabilities such as resampling to different time intervals, interpolating, and modeling as a function of time.

You will cover the following topics as you work through this chapter:

  • What are datetimes?
  • Activity 12.01 – understanding power usage
  • Datetime math operations
bookmark search playlist download font-size

Change the font size

margin-width

Change margin width

day-mode

Change background colour

Close icon Search
Country selected

Close icon Your notes and bookmarks

Delete Bookmark

Modal Close icon
Are you sure you want to delete it?
Cancel
Yes, Delete