Book Image

Hands-On Data Analysis with Pandas

By : Stefanie Molin
Book Image

Hands-On Data Analysis with Pandas

By: Stefanie Molin

Overview of this book

Data analysis has become a necessary skill in a variety of domains where knowing how to work with data and extract insights can generate significant value. Hands-On Data Analysis with Pandas will show you how to analyze your data, get started with machine learning, and work effectively with 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 powerful pandas library to perform data wrangling to reshape, clean, and aggregate your data. Then, you will be able 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. By the end of this book, you will be equipped with the skills you need to use pandas to ensure the veracity of your data, visualize it for effective decision-making, and reliably reproduce analyses across multiple datasets.
Table of Contents (21 chapters)
Free Chapter
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

Chapter materials

The materials for this chapter can be found on GitHub at https://github.com/stefmolin/Hands-On-Data-Analysis-with-Pandas/tree/master/ch_03. There are five notebooks that we will work through, each numbered according to when they will be used. We will begin with a discussion about wide versus long format data in 1-wide_vs_long.ipynb. Then, we will collect daily temperature data from the NCEI API, which can be found at https://www.ncdc.noaa.gov/cdo-web/webservices/v2, in the 2-using_the_weather_api.ipynb notebook. The documentation for the Global Historical Climatology Network - Daily (GHCND) dataset we will be using can be found here: https://www1.ncdc.noaa.gov/pub/data/cdo/documentation/GHCND_documentation.pdf.

The NCEI is part of the National Oceanic and Atmospheric Administration (NOAA). As indicated by the URL for the API, this resource was created when the...