import intake
intake.output_notebook()  # enables source.plot API

intake.cat

# find the entries in the catalog
list(intake.cat)

# select an entry
# same as intake.cat["us_crime"]
intake.cat.us_crime

# detailed info - touches data
s = intake.cat.us_crime()
s.discover()

s.plots

# the included quick-plot
intake.cat.us_crime.plot.example()

# load all data into memory
df = intake.cat.us_crime.read()

# now we have a pandas dataframe
df.head()

# Analysis:
# fraction of all theft that was vehicle theft across all years
df['Motor vehicle theft'].sum() / df['Larceny-theft'].sum()

intake.gui

intake.gui.add('sea.yaml')

s = intake.gui.item()
s.discover()  # access information on the selected item.

s.plot.basic()