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_06. We will be working with two datasets once again, both of which can be found in the data/ directory. In the fb_stock_prices_2018.csv file, we have Facebook's stock price for all trading days in 2018. This data is the OHLC data (opening, high, low, and closing price), along with the volume traded. It was gathered using the stock_analysis package that we will build in Chapter 7, Financial Analysis – Bitcoin and the Stock Market.

The data/earthquakes.csv file contains earthquake data pulled from the USGS API (https://earthquake.usgs.gov/fdsnws/event/1/) for September 18, 2018, through October 13, 2018. For each earthquake, we have the magnitude (the mag column), the scale it was measured on (the magType column), when...