Data Exploration in PythonAllen B. Downey
Basic Data Types in Python: A Quick Exploration Take this quiz to test your understanding of the basic data types that are built into Python, like numbers, strings, bytes, and Booleans.Python’s Basic Data Types Python has several built-in data types that you can use out of the box be...
This course will cover the process of exploring and analyzing data, from understanding what’s included in a dataset to incorporating exploration findings into a data science workflow.Using data on unemployment figures and plane ticket prices, you’ll leverage Python to summarize and validate data, ...
Analytics Part three of a comprehensive, practical guide to CLV techniques and real-world use-cases Katherine Munro November 17, 2023 12 min read Squashing the Average: A Dive into Penalized Quantile Regression for Python Data Science How to build penalized quantile regression models (with code!...
This is the second post in our Data Exploration with Python series. Before reading this post, make sure to check out Data Exploration with Python, Part 1! Mise en place (noun): In a professional kitchen, the disciplined organization and preparation of equipment and food before service begins....
auto_awesome_motion View Active Events es·9y ago· 90 views arrow_drop_up1 Copy & Edit Copied from private notebook (+2,-0) NotebookInputOutput Runtime play_arrow 26m 6s Language Python Competition Notebook House Prices - Advanced Regression Techniques...
Techniques of Outlier Detection and Treatment Let us now look at techniques of outlier detection and treatment for data exploration. What is an Outlier? Data analysts and data scientists commonly use outliers. They need close attention, or else they can result in wildly wrong estimations. Simply...
At its heart, Seaborn strives to make visualization a core component of the data exploration and analysis process. scikit-learn: This comprehensive machine learning library is built on SciPy and NumPy. It has applications for statistical modeling, such as regression, clustering, classification, and ...
Jupyter Notebooks offer a good environment for using pandas to do data exploration and modeling, but pandas can also be used in text editors just as easily. Jupyter Notebooks give us the ability to execute code in a particular cell as opposed to running the entire file. This saves a lot of...
In this article, we’ll explore 10advanced Python tricksthat every data professional should know. Whether you’re simplifying repetitive tasks, optimizing your workflows, or just making your code more readable, these techniques will give you a solid edge in your data science work. ...