Showing posts from July, 2019

Nuclear Test Map For 1969 to 2017

By T. McDonald | 29/07/19 | Updated 07/10/19 Did you know that nuclear tests can be felt on the Richter scale? This investigation maps the nuclear tests registering 5.5 or greater on the Richter scale from 1969 to 2017. (Click on the markers to find out more about that test). At first it may look as if there are not many tests, but if you zoom in on one of the clusters, you will see many more markers. During the investigation it was discovered that the cause 'explosion' was actually four more nuclear explosions. Twelve test sites were discovered with six consisting of many tests, and six with less than ten occurrences. North Korea with just one test was the last nuclear explosion detected in the dataset. The average magnitude showed no real difference with nuclear a explosion was 5.86 and earthquakes at 5.87.  Furthermore, the biggest nuclear explosion was in 1973 and took place at Novaya Zemlya, Russia.  Further investigation revealed little difference between

Random Images from API with python

By T. McDonald | 2/07/19 You may have heard of API’s and wondered what you can do with them. This is a simple but satisfying use of this powerful technology. What is API? Application programming interface. What does it do? An API will allow communication between two applications. The API I am using is a publicly available web-based API , which returns data as in JSON or XML.  In other words, I send a message to a stated website and request some data, in this case images are then returned to me.  Using python 2 is a little different in the coding.  It is worth noting that the ['file'] at the end of json.loads() may be different in the website you are connecting to.  I connected to .    Hope you enjoyed this quick blog.  Please leave a comment below. 

An Outline Of The Data Pipeline

By T. McDonald | 2/07/19 The data pipeline is one way of handling data. This involves acquiring data from a source, or sources, preparing it for use, analysing it, and presenting what was discovered during the analysing to an appropriate audience. Subsequently, there are four stages to the pipeline, which I will outline in this blog: Acquisition Preparation Analyse Presentation Acquisition Before you can do anything, you will need to find some data and determine if it is suitable for the task. This involves legal issues surrounding the data such as its licensing: are you allowed to use it and if so, what are you allowed to do? There may be limitations on the use of the dataset for example. Furthermore, files come in different formats such as CSV or JSON for example. exampleFile.csv Or exampleFile.json   Meaning of the extensions: CSV = Coma Separated Values JSON = JavaScript Object Notation The above are just two examples and there will be other types.