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Hands-On Data Analysis with Pandas

Efficiently perform data collection, wrangling, analysis, and visualization using Python

Paperback Engels 2019
Verkooppositie 2168
Verwachte levertijd ongeveer 12 werkdagen


- Understand how data analysts and scientists gather and analyze data
- Perform data analysis and data wrangling using Python
- Combine, group, and aggregate data from multiple sources
- Create data visualizations with pandas, matplotlib, and seaborn
- Apply machine learning (ML) algorithms to identify patterns and make predictions
- Use Python data science libraries to analyze real-world datasets
- Use pandas to solve common data representation and analysis problems
- Build Python scripts, modules, and packages for reusable analysis code

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.

- Perform efficient data analysis and manipulation tasks using pandas
- Apply pandas to different real-world domains with the help of step-by-step demonstrations
- Get accustomed to using pandas as an effective data exploration tool.


Trefwoorden:Data analyse, Python, Pandas
Aantal pagina's:716


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Over Stefanie Molin

Stefanie Molin is a data scientist and software engineer at Bloomberg LP in NYC, tackling tough problems in information security, particularly revolving around anomaly detection, building tools for gathering data, and knowledge sharing. She has extensive experience in data science, designing anomaly detection solutions, and utilizing machine learning in both R and Python in the AdTech and FinTech industries. She holds a B.S. in operations research from Columbia University's Fu Foundation School of Engineering and Applied Science, with minors in economics, and entrepreneurship and innovation. In her free time, she enjoys traveling the world, inventing new recipes, and learning new languages spoken among both people and computers.

Andere boeken door Stefanie Molin


1 Introduction to Data Analysis
2 Working with Pandas DataFrames
3 Data Wrangling with Pandas
4 Aggregating Pandas DataFrames
5 Visualizing Data with Pandas and Matplotlib
6 Plotting with Seaborn and Customization Techniques
7 Financial Analysis - Bitcoin and the Stock Market
8 Rule-Based Anomaly Detection
9 Getting Started with Machine Learning in Python
10 Making Better Predictions - Optimizing Models
11 Machine Learning Anomaly Detection
12 The Road Ahead

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