Introduction to Financial Data Manipulation with Python

Lab Steps

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Starting the Lab's Jupyter Notebook

The hands-on lab is part of this learning path

Working with Python Visualization Tools
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DifficultyBeginner
Time Limit1h
Students24
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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 PandasData 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
About the Author
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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.