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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

Manipulating SQL data

Earlier, when we introduced SQL, we showed you a simple example where we took our existing bike_share data, created a database, and stored the data as a table in the new database. We mentioned that you can execute SQL commands by using the cursor.execute() method. Here, you will see another example, this time using a database that contains multiple tables.

Suppose you have a database for a pet supply company. You can use pd.read_sql() to issue a command to the database and return the names of all the tables. SQL databases can contain multiple tables, so there is a "master" table, called sqlite_master here, that can be queried so that you can see every other table in the database. In the following snippet, the SELECT statement says to get a variable called name and return its values where the variable called type is 'table' – in other words, a list of tables. The sqlite3.connect() statement opens a connection to the database so that...

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