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The software for this course
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The software for this course

Find out what software you will be using on this applied data science course.
© Coventry University. CC BY-NC 4.0

Before we get started, let’s look over the software you will need to complete the activities in this course.

You will be using Jupyter Notebook, an open-source web application that allows you to create and share documents that contain live Python code. This means that our Jupyter Notebooks will provide you with all the datasets and Python code you need.

  • Jupyter Notebooks: a browser-based programming environment for Python, which enables you to run your code step-by-step and view the resulting output as you go along, making it easy to spot errors and make changes to your code for testing.

Let’s look at some of the other software we will be using:

  • Python: the Python programming language is a high-level programming language, which uses English syntax and keywords, making it easily readable and therefore easy to learn if you are just starting your first steps in computer programming.

We have provided a brief introduction to programming with Python to get you started.

  • Python libraries: Python comes with a large library of code which is one of its greatest strengths. The library provides tools for arithmetic, creating graphical user interfaces, connecting to databases, plotting and visualisation, and machine learning.

You will mainly be using Pandas – a software library for data processing and analysis, which provides data structures and operations for manipulating and visualising table-like data. You can think of it as MS Excel for Python. We will also be using matplotlib, a graph plotting library for Python, to visualise the datasets in your analysis.

We will also use Folium to visualise geolocation coordinates on a map in some of the tasks. We will also find a need to obtain more information about a specific location, for this we will use Geopy to reverse geo-code geo-coordinates to find the name of the town the tweet was sent.

Now that we have got to know our tools, in the next few steps you will look at the data we will be exploring this week.

References

Fuhs, C., & Weston, D. (2019). A short introduction to computer programming using Python. Birbeck University of London. Web link

© Coventry University. CC BY-NC 4.0
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