Example #1
0
urbansim_package().info()

# Working with datasets
import os
import urbansim
us_path = urbansim.__path__[0]
from opus_core.storage_factory import StorageFactory
storage = StorageFactory().get_storage('tab_storage',
    storage_location = os.path.join(us_path, "data/tutorial"))

from opus_core.datasets.dataset import Dataset
households = Dataset(in_storage = storage,
                         in_table_name = 'households', 
                         id_name='household_id',
                         dataset_name='household')
households.get_attribute_names()
households.get_id_attribute()
households.size()
households.get_attribute("income")
households.get_attribute_names()
households.load_dataset()
households.get_attribute_names()
#households.plot_histogram("income", bins = 10)
#households.r_histogram("income")
#households.r_scatter("persons", "income")
households.correlation_coefficient("persons", "income")
households.correlation_matrix(["persons", "income"])
households.summary()
households.add_primary_attribute(data=[4,6,9,2,4,8,2,1,3,2], name="location")
households.get_attribute_names()
households.modify_attribute(name="location", data=[0,0], index=[0,1])
Example #2
0
urbansim_package().info()

# Working with datasets
import os
import urbansim
us_path = urbansim.__path__[0]
from opus_core.storage_factory import StorageFactory
storage = StorageFactory().get_storage('tab_storage',
    storage_location = os.path.join(us_path, "data/tutorial"))

from opus_core.datasets.dataset import Dataset
households = Dataset(in_storage = storage,
                         in_table_name = 'households', 
                         id_name='household_id',
                         dataset_name='household')
households.get_attribute_names()
households.get_id_attribute()
households.size()
households.get_attribute("income")
households.get_attribute_names()
households.load_dataset()
households.get_attribute_names()
#households.plot_histogram("income", bins = 10)
#households.r_histogram("income")
#households.r_scatter("persons", "income")
households.correlation_coefficient("persons", "income")
households.correlation_matrix(["persons", "income"])
households.summary()
households.add_primary_attribute(data=[4,6,9,2,4,8,2,1,3,2], name="location")
households.get_attribute_names()
households.modify_attribute(name="location", data=[0,0], index=[0,1])