Python is a general-purpose programming language that is becoming ever more popular for data science. Companies worldwide are using Python to harvest insights from their data and gain a competitive edge. Unlike other Python tutorials, this course focuses on Python specifically for data science. In our Introduction to Python course, you’ll learn about powerful ways to store and manipulate data, and helpful data science tools to begin conducting your own analyses. Start DataCamp’s online Python curriculum now.
Lead by Hugo Bowne-Anderson, Data Scientist at DataCamp
An introduction to the basic concepts of Python. Learn how to use Python interactively and by using a script. Create your first variables and acquaint yourself with Python's basic data types.
- Variables and types
- Guess the type
- Type conversion
Learn to store, access, and manipulate data in lists: the first step toward efficiently working with huge amounts of data.
- Create a list
- Subsetting, slicing and dicing
- Extend adn delete
You'll learn how to use functions, methods, and packages to efficiently leverage the code that brilliant Python developers have written. The goal is to reduce the amount of code you need to solve challenging problems!
- Functions and arguments
- Methods
- Packages
- Selective import
NumPy is a fundamental Python package to efficiently practice data science. Learn to work with powerful tools in the NumPy array, and get started with data exploration.
- NumPy array
- Cannot contain elements with different types
- typical arithmetic operators, such as +, -, * and / have a different meaning for regular Python lists and numpy arrays
- Subsetting (index operation)
- 2D NumPy array
- Basic statistics
- Median and average
- Coercoef
- Std (standard deviation)
- Generate data
- Random generators