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The Pandas Workshop

The Pandas Workshop

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

Solution 6.2

In this activity, you are analyzing data from this year's survey of abalone oysters for the National Marine Fisheries Service. In particular, you want to get some summary values for the dimensions of male and female samples in the data, depending on the number of rings in the shells. The ring count is a measure of age, and reviewing this data provides comparisons to previous years to understand the health of the population. The data contains a number of observations, including sex, length, diameter, weight, shell weight, and the number of rings:

  1. For this activity, all you will need is the pandas library. Load it in the first cell of the notebook:
    import pandas as pd
  2. Read the abalone.csv file into a DataFrame called abalone and view the first five rows:
    abalone = pd.read_csv('..//Datasets//abalone.csv')
    abalone.head()

The output should look as follows:

Figure 15.21 – The first five rows of the abalone oyster dataset...

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