Python Functions for Data Science

Course details

Explore the capabilities of Python in data science as you learn about its most essential functions. Get familiar with core Python tools that support real analysis and decision-making, with a focus on making your code more readable and reusable. Dive into data manipulation with NumPy and pandas. Master the art of visualization using matplotlib and seaborn to spot trends and relationships. Discover how to effectively aggregate, transform, and visualize your data to extract meaningful insights. Gain insights into common pitfalls and mistakes when using functions, ensuring a smooth workflow in your data science projects. This course is perfect for data scientists looking to refine their skills with Python's powerful functions. This course helps you build proficiency in handling data with Python's built-in functions and supporting libraries, preparing you to tackle complex data science challenges with confidence.

Concepts

Introduction

Use Python like a data scientist
Getting started with Python

Core Python Essentials

Inspect data for validation
Handle magnitudes and precision in data
Aggregate data with basic functions
Sort, filter, and transform your data

NumPy and SciPy Fundamentals

Create NumPy arrays in Python
Index and slice NumPy arrays
Reshape NumPy arrays
Transform and scale NumPy arrays
Extract key values with NumPy
Solve matrix-based problems with SciPy
Run statistical functions with SciPy

pandas for Data Manipulation

Create pandas series and dataframes
Extract data subsets from pandas objects
Modify pandas objects
Combine data from pandas objects
Group data from pandas objects
Transform data with pandas apply()

Visualization Essentials

Create line and scatter plots
Display categorical distributions
Explore numerical distributions
Visualize pairwise relationships
Organize your visualizations

Conclusion

Apply functions to data science