From a Database...

Import data

Connect to the database and construct an EntityStore for the schema:

Register the entities to access directly:

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...

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.

Import data

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:

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 data

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: