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After you’ve let Watson do the hard work, let yourself take the glory with interactive charts.
Maybe you spend a lot of time in Facebook doing this in your spare time, but to record everything and make it useful to your business is too much work.
Fortunately, this is what cognitive computing can do for you when you run a Jupyter Notebook using the Watson Python SDK.
As you explore different combinations, you’ll uncover hidden insights in the data, find the best way to prove your findings, and share them with others.
Data science and cognitive computing are a powerful combination.
In the code pattern Discover hidden Facebook usage insights, we show you how, with a single Jupyter Notebook, you can use the Watson Python SDK to enrich your Facebook data with: Once you’ve enriched the data, you can explore it with interactive charting using Pixie Dust.
Facebook will provide you with many metrics about each of your posts and provides links to the articles or photos.It would lets us code in hours what other programming languages would take days to code.Assuming everyone is new to python I will go through each and every step of installing python and its dependencies to get our app running.1) Find a suitable package of python to install on your system here.On Git Hub, you’ll find a developer journey that demonstrates how to take a CSV file with Facebook metrics and enrich it with attributes discovered with Watson Visual Recognition, Tone Analyzer, and Natural Language Understanding.Once you have all that information in a pandas Data Frame, you can process it with Python code and visualize it with Pixie Dust.After converting data into insigthful information, we will plot this information using plotly API to give visually attractive results.Tags: Adult Dating, affair dating, sex dating