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Learn to code for data analysis
Learn to code for data analysis

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1 Weather data

This week you will be looking at investigating historic weather data.

An image of filter like diagonal strips across various skies such as an orange sunset, a storm and a clear blue sky.
Figure 1

Of course, such data is hugely important for research into the large-scale, long-term shift in our planet’s weather patterns and average temperatures – climate change. However, such data is also incredibly useful for more mundane planning purposes. To demonstrate the learning this week, I, Rob Griffiths, will be using historic weather data to try and plan a summer holiday in the UK. You’ll use the data too and get a chance to work on your own project at the end of the week.

The dataset we’ll use to do this will come from the Weather Underground [Tip: hold Ctrl and click a link to open it in a new tab. (Hide tip)] , which creates weather forecasts from data sent to them by a worldwide network of over 100,000 weather enthusiasts who have personal weather stations on their house or in their garden.

In addition to creating weather forecasts from that data, the Weather Underground also keeps that data as historic weather records allowing members of the public to download weather datasets for a particular time period and location. These datasets are downloaded as CSV files, explained in the next step.

Datasets are rarely ‘clean’ and fit for purpose, so it will be necessary to clean up the data and ‘mould it’ for your purposes. You will then learn how to visualise data by creating graphs using the plot() function.