Introduction to Financial Data Manipulation with Python
Lab Steps
The hands-on lab is part of this learning path
Ready for the real environment experience?
Description
The goal of this lab is to build and explore a dataset of financial returns using data related to the closing price of three stocks quoted on the NASDAQ 100 index. You will mainly use two Python libraries to accomplish this objective: Pandas and Matplotlib.
Your data management and manipulation skills will be challenged, and by the end of this lab, you should have a deep understanding of how Pandas and Matplotlib work.
Before starting this lab, you are strongly encouraged to take the following courses: Working with Pandas, Data Wrangling with Pandas, and Data Visualisation with Python using Matplotlib.
Learning Objectives
Upon completion of this lab you will be able to:
- Create and manage datasets using pandas
- Manipulate and transform your data
- Explore your data in a graphical dimension
Intended Audience
This lab is intended for:
- Those interested in performing data analytics with Python
- Anyone involved in data manipulation pipelines
Prerequisites
You should possess:
- An intermediate understanding of Python
- Basic knowledge of the following libraries: Pandas, Matplotlib, NumPy
Andrea is a Data Scientist at Cloud Academy. He is passionate about statistical modeling and machine learning algorithms, especially for solving business tasks.
He holds a PhD in Statistics, and he has published in several peer-reviewed academic journals. He is also the author of the book Applied Machine Learning with Python.