Programming Languages

Module 5: Working with Numpy Arrays & Simple APIs

Learning Objectives:

  • Explain the use of the HTTP protocol using the Requests Library method
  • Describe how the URL Request Response HTTP protocol works
  • Learn to apply simple, open-source APIs
  • Perform basic webscraping using Python
  • Work with different file formats using Python
  • Explain the difference between APIs and REST APIs
  • Summarize how APIs receive and send information

Introduction

MBA students need to understand arrays and simple APIs in python. Arrays are useful for storing data, and understanding simple APIs in Python will allow students to use code to communicate with other programs. Being able to effectively use arrays and APIs in Python can help MBA students save time by performing functions faster and more efficiently, and it also enables them to make better decisions using data-driven analysis. Having the ability to understand arrays and APIs in Python is therefore essential for MBA students who wish to become successful in their field.

Discussion of Python Arrays & APIs

  • Arrays
  • APIs

Numpy 1D Arrays

Numpy 2D arrays are multi-dimensional data structures used in the Python programming language. They can be used to store and manipulate complex data such as matrices and multidimensional datasets. The basic format of a Numpy 2D array is an array of lists, with each list representing a single row in the array. This structure allows for easy manipulation of the data within the array, such as retrieval, sorting, filtering, and more. Numpy arrays are most commonly used for scientific computing and machine learning tasks, where they can be very effective tools given their multi-dimensional nature.


Numpy 2D Arrays

Numpy is an open-source library for the Python programming language that is used for scientific computing and data analysis. It offers a wide range of features including multidimensional arrays, powerful numerical processing capabilities, and sophisticated mathematical functions. Numpy is one of the core libraries used in most scientific computing projects, as it provides an easy way to manipulate large amounts of data in a structured manner. Numpy is an essential tool for many data science and machine learning projects, allowing users to quickly develop algorithms for analyzing and manipulating data. Additionally, it can be used to create powerful visualizations that reveal patterns and correlations in datasets. Numpy is a powerful library that helps developers make the most out of their data.

 

Simple APIs - Part 1

Simple APIs, or Application Programming Interfaces, are a set of tools that allow developers to easily interact with and access data from external sources. They provide a straightforward way for developers to communicate with various web services and databases without writing complex and lengthy code. In Python, these APIs can be used to access data from popular web services such as Google Maps, Twitter, and YouTube. Additionally, Simple APIs are a way to build powerful web applications that leverage data from various sources. By using simple APIs, developers can quickly develop interactive applications that can analyze large amounts of data in an organized manner. With the help of Simple APIs, developers can easily access the data they need in order to make informed decisions and create powerful applications.

Simple APIs - Part 2

Examples of APIs in Python include the Google Maps API, which allows developers to access data associated with the Google Maps service such as geographic coordinates, street addresses, road networks, and satellite imagery. The Twitter API is another popular example that enables developers to access tweets and other information related to the Twitter network.

Conclusion

Arrays and simple api's are a great way to manipulate data. You can access data very easily, making it perfect for small projects or prototypes. In addition, arrays and APIs are relatively easy to learn and use, making them ideal for beginners who want to get started in coding. Python offers a wide range of array and API functions. With its simple syntax and flexibility, Python can help you create powerful data manipulation programs quickly and efficiently. Overall, arrays and simple APIs are useful tools for manipulating data in Python. So if you're interested in exploring the world of programming, start with arrays and simple APIs using Python!

Discussion of Python Arrays & APIs

  • Arrays
  • APIs