Book Image

Hands-On Data Analysis with Pandas - Second Edition

By : Stefanie Molin
5 (1)
Book Image

Hands-On Data Analysis with Pandas - Second Edition

5 (1)
By: Stefanie Molin

Overview of this book

Extracting valuable business insights is no longer a ‘nice-to-have’, but an essential skill for anyone who handles data in their enterprise. Hands-On Data Analysis with Pandas is here to help beginners and those who are migrating their skills into data science get up to speed in no time. This book will show you how to analyze your data, get started with machine learning, and work effectively with the Python libraries often used for data science, such as pandas, NumPy, matplotlib, seaborn, and scikit-learn. Using real-world datasets, you will learn how to use the pandas library to perform data wrangling to reshape, clean, and aggregate your data. Then, you will learn how to conduct exploratory data analysis by calculating summary statistics and visualizing the data to find patterns. In the concluding chapters, you will explore some applications of anomaly detection, regression, clustering, and classification using scikit-learn to make predictions based on past data. This updated edition will equip you with the skills you need to use pandas 1.x to efficiently perform various data manipulation tasks, reliably reproduce analyses, and visualize your data for effective decision making – valuable knowledge that can be applied across multiple domains.
Table of Contents (21 chapters)
1
Section 1: Getting Started with Pandas
4
Section 2: Using Pandas for Data Analysis
9
Section 3: Applications – Real-World Analyses Using Pandas
12
Section 4: Introduction to Machine Learning with Scikit-Learn
16
Section 5: Additional Resources
18
Solutions

Exploring an API to find and collect temperature data

In Chapter 2, Working with Pandas DataFrames, we worked on data collection and how 
to perform an initial inspection and filtering of the data; this usually gives us ideas of things that need to be addressed before we move further in our analysis. Since this chapter builds on those skills, we will get to practice some of them here as well. To begin, we will start by exploring the weather API that's provided by the NCEI. Then, in the next section, we will learn about data wrangling using temperature data that was previously obtained from this API.

Important note

To use the NCEI API, you will have to request a token by filling out this form with your email address: https://www.ncdc.noaa.gov/cdo-web/token.

For this section, we will be working in the 2-using_the_weather_api.ipynb notebook to request temperature data from the NCEI API. As we learned in Chapter 2,Working with Pandas DataFrames, we can use the requests...