Basics

The following Python skills and techniques may be considered basic level in the context of data analysis.

Data Structures

• Lists: Know how to create and manipulate lists, and use them to store and organize data.

• Dictionaries: Know how to create and manipulate dictionaries, and use them to store and organize data in key-value pairs.

Control Structures

• Conditional Statements: Know how to use if-else statements to conditionally execute code.

• Loops: Know how to use for and while loops to iterate over data.

Functions

• Defining Functions: Know how to define functions to organize and reuse code.

• Lambda Functions: Know how to define and use lambda functions for short and simple functions.

File I/O

• Reading and Writing Files: Know how to read and write data from files using Python.

External Libraries

• NumPy: Know how to use NumPy to perform numerical operations and calculations.

• pandas: Know how to use pandas to work with structured data and perform data analysis tasks.

• Matplotlib: Know how to use Matplotlib to create basic plots and visualizations.

These skills and the associated techniques provide a strong foundation for data analysis in Python, and can be built upon with more advanced topics and libraries as needed.