Phoenix - Your AI AssistantUse Python to create merged datasets, analyses and visuals
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5 days
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What you get with this Offer
Disease information in England is much easier to review using Python, Python packages matplotlib or Seaborn and geopackage plotting tools from the Office of National Statistics. There are data packages to plot data at the "LSOA" level, ie "Lower Super Output Area". LSOAs cover 1500 people in 400-700 households and are often used in healthcare analyses. The TB graphic is at the subICB level (old CCG), after merging datasets.
Large datasets in csv or xls format can be cleaned and prepared to be merged in order to discover insights not obvious from one dataset alone. Other types of dataset can also be merged, using different Python coding.
Other types of data (sales, products, geographic, numeric etc) can of course also be merged, analysed and visualised as above, however my primary interest is in healthcare data and its use in strategic or operational decision making because of my career to date.
Large datasets in csv or xls format can be cleaned and prepared to be merged in order to discover insights not obvious from one dataset alone. Other types of dataset can also be merged, using different Python coding.
Other types of data (sales, products, geographic, numeric etc) can of course also be merged, analysed and visualised as above, however my primary interest is in healthcare data and its use in strategic or operational decision making because of my career to date.
What the Freelancer needs to start the work
Sources of the data to be analysed, ideally the csv or xls ready to download. A basic understanding of the audience and how the analysis and/or visualisation will be used.