Basic Examples (1)
Retrieve the default content element, which is a Dataset on the Titanic:
Scope & Additional Elements (6)
Retrieve the content relating to the Dinghy Association:
Retrieve the content relating to the Titanic:
Retrieve the content relating to Major League Soccer:
Retrieve the content relating to planets:
Retrieve the content relating to Eastern cities:
Retrieve the content relating to IDWeight:
Visualizations (4)
Create a stack of cylinders showing the approximate circumference of all of the planetary moons, coloring them according to the planet they circle:
Create a graphic showing the (log) salary trajectories of players on the Houston Dynamo:
Break down comparative survival on the Titanic by cabin class and sex:
Break down comparative survival on the Titanic by cabin class and sex and age decade; lump together people age 50 and over:
Get the Wolfram Knowledgebase Entities corresponding with several eastern European cities, deleting any that WolframAlpha does not recognize:
Show the cities on a map:
Show the cities on a relief map of eastern Europe, representing them as bubbles that correspond to their population:
Analysis (4)
Compute the mean mass of the moons of Mars:
Compute the median guaranteed compensation of MLS players by club in 2017; restrict the output to 10 rows and color the data light green:
Join the "cabins" data with the passenger data to obtain a single Dataset that includes the square footage of the cabin occupied by each passenger and whether they had a window:
Use machine learning to create a model of the probability of survival on the Titanic:
Split the data into training and testing:
To prepare the data for classification, group the data by survival and drop the survived column:
Assess classifier performance: