Book Image

The Pandas Workshop

By : Blaine Bateman, Saikat Basak, Thomas V. Joseph, William So
5 (1)
Book Image

The Pandas Workshop

5 (1)
By: Blaine Bateman, Saikat Basak, Thomas V. 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)
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

Activity 8.01 – Using data visualization for exploratory data analysis

In this activity, we will apply what we have learned in this chapter to building different types of plots in order to perform an exploratory data analysis on a sale price. We will work on the Manufactured Housing Survey dataset, published by the United States Census Bureau, that can be found in the GitHub repository at https://raw.githubusercontent.com/PacktWorkshops/The-pandas-Workshop/master/Chapter08/Data/PUF2020final_v1coll.csv.

Note

More details about the Ames Housing dataset can be found at https://www.census.gov/data/datasets/2020/econ/mhs/puf.html.

The goal of this activity is to analyze the different factors contributing to a sale price in the housing market. We will use different types of plots in order to achieve it.

Your tasks will be as follows:

  1. Open a Jupyter notebook.
  2. Import the pandas, numpy, and matplotlib packages.
  3. Load the CSV file as a DataFrame.
  4. For the...