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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

Activity 1.01 – comparing sales data for two stores

ABC Corporation is a retail company with two big stores for grocery and stationery products. The company is planning to create an ambitious marketing campaign next year. As a data analyst, your task is to derive the following insights from the data and relay those insights to the sales team so that they can plan the campaign effectively:

  • Which store has greater sales for the quarter?
  • Which store has the highest sales for grocery products?
  • Which store has the highest sales for March?
  • For how many days were the sales of stationery products greater in store 1 than in store 2?

In this activity, you will create the datasets for the two stores and use all the methods you have learned so far to answer the preceding questions. The following steps will help you complete this activity:

  1. Open a new Jupyter notebook.
  2. Load the data that corresponds to the two stores (Store1.csv and Store2.csv). These datasets are available in this book's GitHub repository at https://github.com/PacktWorkshops/The-Pandas-Workshop/tree/master/Chapter01/Datasets.
  3. Use the different methods you have learned about in this chapter to answer the questions.
  4. Print the resulting DataFrames. Note that the DataFrames you create should be in the following format:
Figure 1.63 – Final output

Figure 1.63 – Final output

With that, we have covered everything you need to know to get started with pandas.

Note

You can find the solution for this activity in the Appendix.

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