Analyze a Computable Dataset
From a Database...
Data stored in local or remote relational databases can be mapped into entity stores to create computable datasets that can then be visualized and queried.
Connect to the database and construct an EntityStore for the schema:
Register the entities to access directly:
- For more information on importing from databases, see Import Tabular Data as a Computable Dataset.
Summarize the data
Visualize office information from the database in full:
Visualize the office information in the context of cities and phone numbers:
Join the customers table with the payments table by combining the “customers” class with the “payments” class:
The combined class shares properties of both individual classes:
Access the customer names and amount properties:
Turn customer payment information into key-value pairs:
Use KeyValueMap to map the keys “customer” and “amount” to the Keys and Values, respectively:
Visualize the relationship in a Dataset with column headers:
Find the average amount a customer has paid:
Find the number of customers who have spent a similar amount:
Sort the payments from high to low:
Visualize the five most expensive customers:
Unregister the entities
Unregister the EntityStore that contains the sales commerce data:
From a CSV, TSV or Other Character-Separated Data File...
Import a CSV-format data file of city trees as a computable Dataset object. SemanticImport automatically recognizes values in the rightmost “Location” column as geographic positions and turns them into computable GeoLocation objects:
- SemanticImport returns a Dataset object.
Summarize the data
Use Counts to count how many trees have given numbers of trunks:
Query the data
Use MaximalBy to find the tree with the greatest number of trunks:
Make a plot
Plot the distribution of tree diameter values:
Calculate statistical values
Find the mean tree trunk diameter:
- By default, Mean outputs the value as a fraction. Wrap the result with N to approximate a numeric value.
Extract a Dataset of all of the tree species:
Make a map
Use TakeLargestBy to get the top 10 trees with the largest diameter at breast height and output only their location:
Make a map of the locations of the 10 largest trees: