This is the code repository for Mastering Exploratory Analysis with pandas, published by Packt.
Build an end-to-end data analysis workflow with Python
The pandas is a Python library that lets you manipulate, transform, and analyze data. It is a popular framework for exploratory data visualization and analyzing datasets and data pipelines based on their properties.
This book covers the following exciting features:
- Learn how to read different kinds of data into pandas DataFrames for data analysis
- Manipulate, transform, and apply formulas to data imported into pandas DataFrames
- Use pandas to analyze and visualize different kinds of data to gain real-world insights
- Extract transformed data form pandas DataFrames and convert it into the formats your application expects
- Manipulate model time-series data, perform algorithmic trading, derive results on fixed and moving windows, and more
If you feel this book is for you, get your copy today!
All of the code is organized into folders. For example, Chapter02.
The code will look like the following:
df = pd.read_csv('IMDB.csv', encoding = "ISO-8859-1")
df.head()
Following is what you need for this book:
If you are a budding data scientist looking to learn the popular pandas library, or a Python developer looking to step into the world of data analysis, this book is the ideal resource you need to get started. Some programming experience in Python will be helpful to get the most out of this course
With the following software and hardware list you can run all code files present in the book (Chapter 1-4).
| Chapter | Software required | OS required |
|---|---|---|
| 1-4 | Python 2.7x and above | Windows/Ubuntu |
We also provide a PDF file that has color images of the screenshots/diagrams used in this book. Click here to download it.
Harish Garg is a data analyst, author, and software developer who is really passionate about data science and Python. He is a graduate of Udacity's Data Analyst Nanodegree program. He has 17 years of industry experience in data analysis using Python, developing and testing enterprise and consumer software, managing projects and software teams, and creating training material and tutorials. He also worked for 11 years for Intel Security (previously McAfee, Inc.). He regularly contributes articles and tutorials on data analysis and Python. He is also active in the open data community and is a contributing member of the Data4Democracy open data initiative. He has written data analysis pieces for the Takshashila think tank.
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