Exploring Financial Data using Nasdaq Data Link API

  • Guided Project
  • 0.6 hours
  • Intermediate
  • Python

Practice retrieving financial data from APIs, manipulating it with Pandas, and visualizing trends using Python.

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Overview

In this project, you'll become a financial analyst exploring real-world economic data to uncover market trends. Using Python, you'll interact with the NASDAQ Data Link API to retrieve comprehensive financial datasets. You'll then apply data wrangling techniques using Pandas and leverage visualization libraries to identify insights. Through hands-on experience with these vital tools and techniques, you'll develop skills in API usage, JSON data handling, data manipulation, and trend visualization. Showcasing these abilities will enhance your portfolio and prepare you for data-driven finance roles. Objective: Retrieve and analyze financial data using Python and the NASDAQ Data Link API to uncover market trends and insights essential for investment strategies.

What You'll Learn

  • ✓ Retrieve specific economic indicators from the Nasdaq Data Link API to analyze market trends.
  • ✓ Use authentication to ensure consistent data access.
  • ✓ Implement optional query parameters to refine data retrieval.
  • ✓ Integrate the API data with Pandas for efficient data wrangling and analysis.

Before You Start

  • ✓ Applying Python programming fundamentals to make API requests and handle responses
  • ✓ Sending GET requests with query parameters using the requests library
  • ✓ Extracting and manipulating JSON data from API responses
  • ✓ Using Pandas DataFrames to efficiently analyze and visualize API data

Project Steps

10 steps

  1. 1 Introduction
  2. 2 API documentation and credentials
  3. 3 Working with the Endpoint and Parameters to Query the API
  4. 4 Processing the JSON Data into a DataFrame
  5. 5 Understanding the Dataset
  6. 6 Filtering the DataFrame for Analysis
  7. 7 Enhancing the DataFrame
  8. 8 Understanding Financial Trends Over Time
  9. 9 Geographical Region Analysis
  10. 10 Next steps
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