Book Image

Hands-On Data Science with Anaconda

By : Yuxing Yan, James Yan
Book Image

Hands-On Data Science with Anaconda

By: Yuxing Yan, James Yan

Overview of this book

Anaconda is an open source platform that brings together the best tools for data science professionals with more than 100 popular packages supporting Python, Scala, and R languages. Hands-On Data Science with Anaconda gets you started with Anaconda and demonstrates how you can use it to perform data science operations in the real world. The book begins with setting up the environment for Anaconda platform in order to make it accessible for tools and frameworks such as Jupyter, pandas, matplotlib, Python, R, Julia, and more. You’ll walk through package manager Conda, through which you can automatically manage all packages including cross-language dependencies, and work across Linux, macOS, and Windows. You’ll explore all the essentials of data science and linear algebra to perform data science tasks using packages such as SciPy, contrastive, scikit-learn, Rattle, and Rmixmod. Once you’re accustomed to all this, you’ll start with operations in data science such as cleaning, sorting, and data classification. You’ll move on to learning how to perform tasks such as clustering, regression, prediction, and building machine learning models and optimizing them. In addition to this, you’ll learn how to visualize data using the packages available for Julia, Python, and R.
Table of Contents (15 chapters)

Introduction to the Python pandas package

The Python pandas package is very useful when dealing with data. The pandas package is a wonderful tool for data preprocessing, which is essential for data analysis. There is a humorous way of describing the importance of data cleaning: "A data scientist spends 80% of their time cleaning the data and the other 20% complaining about cleaning the data". To test if the package is preinstalled, we can type import pandas as pd after we launch Python. If we don't see any error messages, it means that the package was preinstalled. If we do, then we can use conda install pandas to install the package. To find all available functions, we could use the following three lines of Python code:

To find out about the usage or examples of individual functions, the help() function can be used. For example, for the to_pickle functionality...