In a few short minutes we will show you how to query, discover and access hundreds of new data sets. You can also try our interactive Quick-Start Notebook hosted on Binder.
Let’s get started!
Once we have our package installed, we need to do is get our Analytics package imported.
:::python from demyst.analytics import Analytics analytics = Analytics()
Load Input File
Let’s load a CSV of publicly available business information into a Pandas DataFrame:
Prepare Input File
Now let’s use our validate function to see if the Demyst Platform recognizes any of our column types:
At the moment the DataFrame is unusable, but we can address this quickly by mapping the columns to the types Demyst recognizes:
Now we are ready to access some data!
Search Relevant Data Products
Now let’s take our prepared input file and feed it to our search function. The first thing you will notice is that Juptyer is going to ask you for a Username and Password. Head on over to the Demyst Console and sign up if you don’t have credentials!
You can now browse through hundreds of data providers that could match against your input file.
Enrich Input File
Now let’s choose some data products and enrich our input file:
owler_search data products to enrich our business dataset. We pass those into the enrich_and_download function which takes our input dataframe and provider list to enrich against.
That should get you accessing data! If you run into any problems feel free to reach out to firstname.lastname@example.org!